This month at , we announced a wave of 麻豆原创 Business AI innovations all built on the same technology foundation that powers our that we are now delivering to our customers and partners, allowing them to add even more value in the future.

We showed how the future of enterprise software is built on an AI-native architecture, powered by 麻豆原创 app, data, and AI foundation. With this approach, we are enabling a platform shift across the tech stack in a non-disruptive fashion, empowering developers to work faster and smarter using the frameworks and tools of their choice.

麻豆原创 HANA Cloud and 麻豆原创 Business Data Cloud: powering our AI-native future

麻豆原创 HANA Cloud is the database for 麻豆原创鈥檚 AI-native software architecture and the foundation of our broader data fabric strategy. At 麻豆原创 TechEd, we announced new AI capabilities for 麻豆原创 HANA Cloud that spur AI innovation.  

For example, Model Context Protocol (MCP) support for 麻豆原创 HANA Cloud is now generally available. This provides direct access to rich multi-model engines. Agents can be grounded in full enterprise data context: navigating relationships across customers and suppliers, understanding geographic dependencies through spatial data, and performing semantic searches through vector embeddings — all within a single in-memory engine.  

We鈥檙e also expanding 麻豆原创 HANA Cloud knowledge graph engine capabilities (Q1 2026) so customers can automatically generate knowledge graphs from 麻豆原创 HANA Cloud metadata. What used to take weeks of manual modeling can now happen automatically in minutes. But that鈥檚 not all. We鈥檙e also enabling agentic memory in 麻豆原创 HANA Cloud. With long-term memory, AI agents can memorize past inputs and decisions — learning and remembering just like humans — and become continuously smarter.

These advances show that 麻豆原创 HANA Cloud is truly powering an AI-native future. .

Bringing together the power of 麻豆原创 BDC and Snowflake

We are bringing the power of Snowflake together with 麻豆原创 Business Data Cloud (麻豆原创 BDC), calling it 麻豆原创 Snowflake. This partnership enables zero copy data sharing with Snowflake via 麻豆原创 BDC Connect.

Enterprises already using Snowflake today can leverage 麻豆原创 BDC Connect to integrate their existing instances of Snowflake with 麻豆原创 BDC, giving them seamless, real-time access to combined, semantically rich 麻豆原创 with non-麻豆原创 data in 麻豆原创 BDC. 麻豆原创 Snowflake will be made generally available in Q1 2026, and 麻豆原创 BDC Connect for Snowflake in H1 2026. Find more information here.

麻豆原创-RPT-1: a new category of AI models

One of our most exciting announcements at 麻豆原创 TechEd was the launch of our first enterprise relational foundation model 麻豆原创-RPT-1, pronounced: 鈥渞apid one.鈥�

Businesses run on structured data. But large language models (LLMs) struggle with a general understanding of table structures and associated semantics. This requires the use of machine learning, or 鈥渘arrow AI,鈥� for tasks like classification, regression, and more. But classical machine learning necessitates training a model on each task, which easily can lead to hundreds of separate models.

麻豆原创-RPT-1 puts them all into one single, pre-trained model that understands relational business data and predicts business outcomes. Unlike language, image, or video models, 麻豆原创-RPT-1 accurately predicts business based on tabular data such as payment delays, supplier risks, upsell opportunities, customer churn risk, and more.

We believe that 麻豆原创-RPT-1 is a super capable foundation model today. It provides up to 2x better prediction quality compared to narrow models and 3.5x better prediction quality as compared to LLMs. .

麻豆原创-RPT-1 comes in three versions. 麻豆原创-RPT-1-small is for super-fast predictions and 麻豆原创-RPT-1-large is for highest accuracy. Both will be generally available in Q4 2025 in the generative AI hub in AI Foundation. 麻豆原创-RPT-1-OSS is the open-source version, available in Hugging Face and GitHub.

You can test 麻豆原创-RPT-1 today with your data or our use case data samples via no-code UI or via API in the new 麻豆原创-RPT-1 playground, an intuitive and interactive space to test for free and open to everyone and .

We are continuously adding new capabilities to AI Foundation and models to the generative AI hub, empowering developers to experiment with orchestration tools and leading models to scale AI development and productization across 麻豆原创 and non-麻豆原创 environments. For example, Perplexity is now generally available in the generative AI hub, so users can correlate business data with external data from the internet. Evaluation Services and Prompt Optimizer, in close collaboration with NotDiamond, are now also generally available in AI Foundation, freeing up users to adopt the most appropriate model for their use cases without the need for rewriting prompts. .

Digital sovereignty made in Germany, for Europe

Digital sovereignty is becoming increasingly important, reflecting the need for regional AI services that align with local regulations, standards, and values. As an example, Europe will benefit from its own strong, trustworthy infrastructure to support innovation, data protection, and ethical AI.

AI Foundation, including various models and all the services we offer, is already available on our own cloud infrastructure. As a next step, we are expanding our 麻豆原创 Cloud Infrastructure offering in our 麻豆原创 data center in Walldorf, Germany, to Deutsche Telekom through the Industrial AI Cloud project, providing secure, high-performance infrastructure for AI innovations across public institutions, defense, and society. 麻豆原创 delivers 麻豆原创 Cloud Infrastructure, 麻豆原创 Business Technology Platform, and applications 鈥� including our AI Foundation with frontier AI from Mistral, Cohere, and others 鈥� on Telekom鈥檚 Munich data center. Both companies uphold the highest standards of data protection, security, and reliability.

This marks a milestone as more European companies join the Industrial AI Cloud project, advancing applied AI across Europe with trusted, business-embedded solutions that unlock the full potential of industry data. See the announcement here.

Enabling customers to build, extend, share, and orchestrate AI agents

To help manage Joule Agents and Joule skills, we have introduced the concept of AI Assistants 鈥� role-based AI teammates, accessed through Joule 鈥� like a financial assistant that brings together agents for cash collection, treasury, and more. We will provide AI Assistants in Joule for every core business role, offering our users an agentic experience like never before.

Out-of-the-box Joule Agents are powerful, but we know that every company has unique requirements. We believe AI should adapt to users鈥� systems, not the other way around, so we are enabling them to use Joule Studio to extend 麻豆原创鈥檚 pre-built agents with custom fields, tools, and reasoning logic while retaining all the deeply grounded integration capabilities 麻豆原创 provides. Joule Studio also provides low-code tools to build custom agents that integrate with all other Joule Agents, Joule skills, and 麻豆原创 BDC.

Using a low-code approach, users can build Joule Agents visually with natural language and drag-and-drop. But we also want to meet the needs of developers who want ultimate flexibility. Our pro-code approach gives developers the freedom to build agents using the agentic framework of their choice 鈥� for example, LangGraph, CrewAI, Google鈥檚 Agent Development Kit, and more. 麻豆原创 Cloud SDK for AI now supports agentic development, ensuring these pro-code agents can be seamlessly integrated and giving developers the best of both worlds: deep integration and full flexibility.

No matter how you want to build agents, an important question is how to integrate them into the larger ecosystem beyond 麻豆原创. We鈥檙e making Joule Agents fully compatible with the agent-to-agent (A2A) protocol soon, so agents can discover and collaborate with each other.

A2A exposes rich semantics describing an agent鈥檚 capabilities, allowing both 麻豆原创 and third-party agents to work together seamlessly. We are collaborating with partners 鈥� AWS, Google, Microsoft, ServiceNow, and more 鈥� to standardize this protocol for full interoperability. This capability will allow Joule to orchestrate tasks across multiple agents, both 麻豆原创 and non-麻豆原创, increasing automation and productivity across the enterprise. Read more here.

To manage and govern agents across the enterprise, is now generally available, providing centralized control of 麻豆原创 and non-麻豆原创 agents. In addition, is available now for tracing agent actions, benchmarking against KPIs, and identifying bottlenecks or opportunities for agents to further improve business.

No 麻豆原创 TechEd without ABAP news

The ABAP journey continues with 麻豆原创-ABAP-1, which will be available in the generative AI hub in Q4 2025. Trained on ABAP code, it is designed to build ABAP AI use cases, enabling developers to build smarter, custom AI solutions in modern ABAP code. .

In addition, ABAP Cloud development is coming to Visual Studio (VS) Code. The new ABAP Cloud extension for VS Code delivers a streamlined, file-based development experience with built-in AI assistance. Powered by an ABAP language server, it will initially support 麻豆原创 Fiori UI service development and expand to additional ABAP Cloud scenarios over time. This brings ABAP development into the same environment where developers already build with UI5 and CAP. General availability is planned for Q2 2026. .

What鈥檚 next: embodied AI and quantum

麻豆原创 TechEd is always an opportunity to look to the future. This year, that future includes not just humans, but also autonomous devices, including humanoid robots.

By integrating Joule Agents natively with robots, 麻豆原创 is bringing business logic into the physical world, enabling a wide range of autonomous devices to operate with enterprise context. We highlighted our strategic partnerships with robotics companies and system integrators to serve customers like Sartorius, Bitzer, and Matur Fompak, demonstrating how our expanding physical AI ecosystem enables robots to understand business processes and execute complex tasks autonomously.

Early proof-of-concept deployments show Joule successfully integrated with 麻豆原创 business applications and autonomous systems across asset performance, logistics, field services, and warehouse operations. While still in the pioneering stage, these implementations illustrate how 麻豆原创 is extending Joule to serve both human users and autonomous devices, shaping the future of enterprise AI.

Read more about the partnerships and implementations here.

AI is a new compute paradigm that changes everything. But there is another compute paradigm on the horizon: quantum computing. It鈥檚 early days, but 麻豆原创 is driving the future of enterprise computing with a vision to help businesses get ready for quantum computing.

麻豆原创 is not building quantum hardware; instead, we are focusing on creating quantum algorithms for business applications. These solutions are simple to deploy 鈥� on when needed, off when not 鈥� and are designed to be hardware-agnostic, collaborating with partners such as IBM to ensure seamless integration without re-platforming. This approach will enable organizations to unlock operational efficiency and drive better business results at enterprise scale.

I couldn鈥檛 be more excited about what鈥檚 next for our customers鈥� future as we bring 麻豆原创鈥檚 AI-native architecture to life.

Philipp Herzig is CTO of 麻豆原创.

We鈥檙e entering a new era, according to 麻豆原创 Executive Board Member Muhammad Alam, in charge of 麻豆原创 Product & Engineering: 鈥渢he era of agentic AI, where AI moves from being just a tool to becoming your trusted teammate.”

Joined on stage by 麻豆原创 CTO Philipp Herzig and Michael Ameling, president of 麻豆原创 Business Technology Platform, Alam set the stage during the kick-off keynote, saying: 鈥淎s developers, you are not on the sidelines of this AI revolution. You are the revolution. And we are here to supercharge you for what鈥檚 next.鈥�

Supercharging developers

Together they dismissed suggestions that AI will replace developers. 鈥淭he truth is that developers aren’t going away,鈥� Alam said. 鈥淭hey are getting supercharged. They’re becoming the architects of smart connected businesses. So, the real question isn’t if we need developers; it’s how fast can we empower them to thrive and lead in this AI-native era?鈥�

Ameling, Alam, and Herzig outlined 麻豆原创’s vision and highlighted the integration of AI, data, and intelligent agents to transform business processes and drive innovation. They also emphasized the importance of a unified data fabric and the deployment of advanced AI models and agentic technologies within the 麻豆原创 ecosystem.

In this new business environment, they noted that every enterprise is becoming a data company and every user experience鈥攆rom the front line to the boardroom鈥攊s becoming AI-driven.

鈥淎s developers, you don鈥檛 just code anymore,鈥� Alam said. 鈥淵ou also design intelligent workflows and supervise AI agents to shape real business outcomes.鈥� To help developers do this, 麻豆原创鈥檚 strategy centers on empowering them with applications, connecting them with data, and supercharging them with AI.

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麻豆原创 BTP is the foundation for AI agents

All this runs on 麻豆原创 Business Technology Platform (麻豆原创 BTP), which serves as the foundation for building and managing AI agents鈥攂oth 麻豆原创 built and custom developed. While 麻豆原创 BTP is the engine, the Business Transformation Management portfolio is the navigator, ensuring technology translates into real business impact. It aligns strategy, process, and people, turning AI-driven potential into sustainable transformation at scale.

Alam identified three broad themes during the keynote:

First, he said 麻豆原创 is continuing to make 麻豆原创 more open. As part of that, he announced 麻豆原创 Snowflake, which brings the full data and AI capabilities of Snowflake as a solution extension to 麻豆原创 Business Data Cloud (麻豆原创 BDC). This partnership is exactly what joint customers have been asking for, Alam shared.

Second, he said 麻豆原创 will provide developers with the most context-rich agentic platform, including the most deeply grounded set of ready-to-use agents that developers can customize to their needs. 鈥淭oday, you鈥檒l hear about creating custom Joule Agents using low-code and pro-code tools with agent builder in Joule Studio as part of 麻豆原创 Build鈥� Alam said.

鈥淲e鈥檙e also standardizing AI agent interoperability with the agent-to-agent protocol, allowing your agents to collaborate securely across ecosystems,鈥� he added.

Third, he announced 麻豆原创鈥檚 first foundation model built specifically for structured business data: 麻豆原创 RPT-1, pronounced 鈥溌槎乖� Rapid One.鈥� 鈥淥ur relational pretrained transformer delivers enterprise-grade accuracy and scale, outperforming both LLMs and AutoML for tabular AI, which is critical for building reliable high-value agents,鈥� Alam said.

鈥淚n short, we鈥檙e embracing an open ecosystem, supercharging agents with deep process and data context, and giving you the tools to amplify AI and agents,鈥� he said. As the keynote continued, Ameling and Herzig detailed these and other innovations, explaining how they will help developers work smarter and achieve more.

麻豆原创 BDC and Snowflake

Ameling expanded on the new partnership with Snowflake, which will bring Snowflake鈥檚 fully managed data and AI capabilities to 麻豆原创 customers. Together with the introduction of 麻豆原创 BDC Connect for Snowflake, he said this will result in cost savings and simplified data landscapes. 鈥淭his enables you to integrate 麻豆原创 and non-麻豆原创 data products seamlessly between 麻豆原创 BDC and Snowflake, so that you can deploy intelligent applications faster and share across your preferred data marketplace.鈥�

Ameling also positioned 麻豆原创 HANA Cloud as 鈥渢he database AI was looking for.鈥� With 麻豆原创 HANA Cloud and 麻豆原创 BDC, 麻豆原创 provides the best business data fabric to help address these challenges, he said. 鈥淲ithout 麻豆原创 HANA Cloud, you would have one database for each and every data representation, which leads to disaggregated data siloes that limit your AI potential. With 麻豆原创 HANA Cloud, we have all these powerful engines in one integrated, multi-model database.鈥�

Building on this, Herzig emphasized that every business requires a strong data foundation because 鈥淎I is nothing without well-organized data…On top of the data foundation sits our AI Foundation that allows you to not only use the latest frontier AI technologies out there in the market, but also to extend 麻豆原创鈥檚 out-of-the-box AI capabilities and build your own experiences deeply contextualized in your business processes and data.鈥�

麻豆原创 pioneers a tabular foundation model

Herzig then explained that 麻豆原创 RPT-1 was designed to address a crucial problem for developers and enable them to deliver much better predictive capabilities, enterprise-grade accuracy, and scale to business customers.

Until now, Herzig said, 鈥淲e still had to go back to good old machine learning 鈥o train what we call 鈥榥arrow鈥� AI models that are specifically made for each [business] task. Therefore, you really had to train a hell of a lot of models.鈥� For example, to solve 10 predictive tasks across 10 different entities like company codes or plants would require training 100 different models.

鈥淲hat we really want to do is get rid of all these models and just introduce one giant model that only requires a small amount of data to learn from,鈥� he said. That鈥檚 what 麻豆原创 RPT-1 is. 鈥淲e believe 麻豆原创 RPT-1 is the most capable predictive foundation model that鈥檚 out there today,鈥� he said, delivering much higher prediction quality while being very fast and super-efficient in terms of resource requirements.

Joule, Joule Agents, and AI assistants

The 麻豆原创 CTO also emphasized that the company is committed to providing developers with the most context-rich agentic platform. He noted that 麻豆原创 has already shipped 20 Joule Agents across lines of business and will have approximately 40 by the end of the year, and that these agents can leverage more than 2,100 pre-delivered Joule skills. In addition, more than 300 embedded AI scenarios across product lines are available for customers to date, including Joule Agents, growing to 400 use cases in total by the end of the year.

Ameling added: “Our promise is simple: build with intent. You describe the outcome and 麻豆原创 Build uses AI agents to generate code, logic, and UIs for you, all with seamless access to your applications and data while you stay in the flow… [麻豆原创] Joule for Developers enables vibe coding experiences to make intent-based development simple and intuitive.”

麻豆原创 is taking it one step further by providing extensions to work with VS code, Windsurf, Cursor, OpenAI Codex, Claude Code, Cline, and more directly in 麻豆原创 Build. “You choose a tool, and we meet you where you are,” Ameling said. He also announced that fine-tuned ABAP LLMs with ABAP 1 on AI Foundation will be published in Q4 this year.

麻豆原创 is redefining how developers interact with AI through innovations in Joule and agentic AI, but also in terms of physical AI. Herzig welcomed Torsten G. Mueller, Group CIO and COO BPS at Sartorius, to discuss how the partnership between Sartorius, NEURA Robotics, and 麻豆原创 is bringing to life robots that understand the what, when, and how based on live business context. 鈥淭his is how we鈥檙e really imagining the future, right? Humans and robots working in harmony through Joule, through AI,鈥� Herzig said.

Quantum computing

Looking to the future, Herzig ended the keynote by talking about another 鈥渃ompute paradigm that is still hard to seize鈥�: quantum computing. While he made it clear that 麻豆原创 is not building a quantum computer, 麻豆原创 is teaming up with quantum hardware leaders, like IBM鈥攚hose Director of Research and IBM Fellow Jay Gambetta joined via video鈥攖o help evaluate quantum computing for business processes and applications.

鈥淲e believe quantum will join classical and AI compute in your stack, and we鈥檙e embedding it into the processes and apps you鈥檙e already using, so it just shows up in the workflows of your enterprise,鈥� Herzig said. 鈥淎nd of course, with the cloud, we scale it all. Now, 麻豆原创 has got you covered, and you鈥檝e got your business covered.鈥�

At 麻豆原创, we believe in creating an ecosystem that simplifies your data landscape and preserves the mission-critical business context of all of your data. This is made possible with a business data fabric.

This architectural approach marks the culmination of decades of progress 鈥� from cubes to warehouses to lakehouses 鈥� now converging toward a business data fabric architecture that brings the true meaning of data together for AI projects to succeed at scale.

Simplify your data landscape with a business data fabric

Earlier this year, we announced 麻豆原创 Business Data Cloud (麻豆原创 BDC), making end-to-end business data fabric capabilities available for everyone that relies on mission-critical 麻豆原创 data, including fully managed 麻豆原创 Databricks.

This week at 麻豆原创 TechEd Berlin, we announced the 麻豆原创 Snowflake solution extension for 麻豆原创 BDC that brings Snowflake鈥檚 data and AI capabilities directly to 麻豆原创 customers.

Together with 麻豆原创 BDC, this provides organizations with the flexibility to choose the right compute and storage for every data and AI workload 鈥� extending their business data fabric while maintaining governance, interoperability, and semantics. As a solution extension, 麻豆原创 Snowflake will be available directly through 麻豆原创, providing a simplified operational experience for customers.

For many customers, integrating data across multi-cloud and hybrid environments adds complexity, especially when bringing transactional and analytical workloads together. Too often, that process comes with a hidden data tax: it strips away the business context and semantics that give data its meaning.

We recently announced 麻豆原创 BDC Connect, a capability that gives customers bi-directional, zero copy data and metadata sharing in 麻豆原创 Business Data Cloud with their existing Databricks and Google Cloud environments. Today, we are excited to announce 麻豆原创 BDC Connect for Snowflake, making it dramatically easier for customers to harmonize and govern mission-critical data wherever it resides.

Connect all your data

As organizations simplify their data landscapes, building a trusted data foundation rooted in business context has become a top priority. A found that nearly half are heavily investing more in harmonizing business data, underscoring the growing importance of using data built on industry standards.

To help accelerate this progress, 麻豆原创 delivers fully managed data products as a core component of 麻豆原创 Business Data Cloud, now with new innovations that expand coverage and connectivity:

• Data product studio: A new capability in 麻豆原创 BDC allows users to create, model, and manage reusable data products using both visual tools and SQL-based transformations from a single workspace. Users can define schema, lineage, and logic to blend 麻豆原创 and non-麻豆原创 data into governed assets with full version control and lifecycle management. It is a simpler way to cross-pollinate data products across lines of business and ensure a consistent definition of data across your business data fabric.
• Additional 麻豆原创 data products: are now available through 麻豆原创 BDC, spanning 麻豆原创 Cloud ERP, 麻豆原创 SuccessFactors, sustainability, and customer experience solutions and more 鈥� bringing even broader coverage across business domains.
• Bi-directional data sharing: We announced data sharing between 麻豆原创 BDC and 麻豆原创 HANA Cloud, unlocking the value of data across both transactional and analytical workloads. Customers can reuse existing objects, such as 麻豆原创 HANA calculation views, directly in 麻豆原创 BDC 鈥� preserving business logic, KPIs, and governance as they extend models across their business data fabric.

Amplify your agents and applications with an AI database

We鈥檙e expanding 麻豆原创 HANA Cloud with new capabilities that make it the AI database for building agents and intelligent applications, helping developers connect and understand all types of data: structured, spatial, graph, vector embeddings, and more, all within a single in-memory engine.

Today, we鈥檙e expanding these multi-model capabilities with three major innovations that make it easier to build agentic AI experiences.

• Expanded knowledge graph capabilities to enable accurate agents: 麻豆原创 HANA Cloud knowledge graph engine will now enable customers to automatically generate knowledge graphs from 麻豆原创 HANA Cloud metadata. The automated graph will include tables and columns and can demonstrate data relationships. These knowledge graphs are customizable and composable, so developers can review data mapping, modify the graph structure, execute a semantic search, and use it to ground agents with the business context it needs to reason accurately.
• Model Context Protocol (MCP) support for 麻豆原创 HANA Cloud: We鈥檙e expanding 麻豆原创 HANA Cloud with Model Context Protocol (MCP) support, giving Joule Agents access to rich multi-model engines in 麻豆原创 HANA Cloud. While SQL remains the default database standard, MCP allows Joule Agents to go beyond rows and columns to interface with unstructured data 鈥� understanding relationships, locations, and meaning across all data types. In practice, that means Joule Agents can navigate relationships between customers and suppliers, analyze geographic dependencies through spatial data, and perform semantic searches through vector embeddings.
• Tabular AI capabilities: This integration with 麻豆原创 AI Core allows users to run AI workloads such as forecasting, anomaly detection, and predictive modeling directly on structured business data from 麻豆原创 HANA Cloud. Along with ready-to-use tabular AI models, customers also gain access to the 麻豆原创-RPT-1 AI model, a new transformer-based foundation model. Embedded natively in 麻豆原创 HANA Cloud, this delivers predictions without task-specific pre-training, enabling developers to use simple SQL procedures to bring AI closer to their 麻豆原创 data and generate semantically rich outputs.

Get started today

A business data fabric provides a deeply integrated ecosystem for all your data. And with 麻豆原创 Business Data Cloud and 麻豆原创 HANA Cloud, you have a fully managed solution for every data and AI workload that ensures business context remains intact across your data landscape.

Irfan Khan is president and chief product officer of 麻豆原创 Data and Analytics.

Build custom agents on the most context-rich agentic platform

I鈥檓 excited to share the ability to build custom agents in will be generally available in December. New capabilities include AI-assisted agent design, system-triggered agents, extensibility of 麻豆原创-delivered Joule Agents, centralized enterprise-grade agent monitoring, support for Agent-to-Agent (A2A) protocol, and support for Model Context Protocol (MCP). Read our in-depth and to learn more.

鈥淛oule Studio鈥檚 agent builder connects 麻豆原创 analytics with merchandising systems, powering Accenture鈥檚 Optisell agent to surface at鈥憆isk inventory, recommend pricing actions, and simplify merchandise alert configuration — all without heavy custom development.鈥�

Catherine Nguyen, Global Lead for 麻豆原创 Business Group AI Strategy and Adoption, Accenture

For developers building pro-code agents, (麻豆原创 BTP) offers comprehensive support for popular open-source frameworks, like Crew.AI and LangGraph, and provides end-to-end identity, authorization, governance, and integration capabilities.

MCP support for is now available, providing with direct access to rich multi-model engines. This allows agents to be grounded in full data context: navigating relationships across customers and suppliers, understanding geographic dependencies through spatial data, and performing semantic searches through vector embeddings 鈥� all within a single in-memory engine. 

Additionally, 麻豆原创 HANA Cloud knowledge graph engine can now automatically generate knowledge graphs from 麻豆原创 HANA Cloud metadata. What used to take weeks of manual modeling can now happen automatically in minutes.

We鈥檙e also enabling agentic memory in 麻豆原创 HANA Cloud. With long-term memory, AI agents can persist context across long-running sessions and memorize past input and decisions, just like humans do, to become continuously smarter.

I鈥檓 excited to share several innovations, including our first enterprise relational foundation model (RPT), 麻豆原创-RPT-1, accompanied by a no-code testing playground environment and prompt optimizer service. New capabilities are continuously added to our , empowering developers to experiment with leading models and orchestration tools and scale AI development and productization across 麻豆原创 and non-麻豆原创 landscapes. .

Vibe on 麻豆原创 Build using the tools of your choice

New local give developers the ability to use agentic tools for development and preferred code assistants, such as Cursor, Windsurf, Claude Code, Cline, and OpenAI Codex — all while maintaining enterprise-grade governance and clean-core alignment.

An 麻豆原创 Build extension pack for Visual Studio (VS) Code is now available to simplify development of CAP, Fiori, UI5, and mobile applications. This makes it easier for VS Code developers to build faster and deploy apps on 麻豆原创 BTP. Looking ahead, we will publish our extensions on the Open VSX Registry to simplify the onboarding of these tools and provide similar native development experiences on other integrated developer environments (IDEs).

Increase velocity with 麻豆原创 Joule for Developers

, the best code assistant for 麻豆原创 development, empowers developers of all skill levels to build more efficiently by leveraging comprehensive, AI-infused developer tools to deliver precise, contextualized outcomes powered by purpose-built, 麻豆原创-centric AI models. This frees-up time to be more productive, creative, and proficient in accelerating ABAP, Java, JavaScript, and visual tool-based application development and automation of 麻豆原创 processes.

New enhancements to 麻豆原创 Joule for Developers, such as within and capabilities, help developers modernize legacy systems and meet enterprise-grade governance and security requirements. These improvements also boost productivity, enhance code quality, and support cloud transformation goals.

Developers working in can now use AI-assisted content creation to quickly generate comments, create workspace content, and summarize documents. AI responses can also draw directly from user-specific folders and workspace content, providing users with trusted insights tailored to their roles, while maintaining compliance and secure role-based document grounding. 

Looking ahead, new ABAP large language models (LLMs) trained on ABAP code and specialized for ABAP development will be released next year.

Connect everything to boost productivity

Developers build the bridges that keep businesses running. We鈥檙e making that work easier and faster with . The following innovations make API and agent-driven automation easier, ensure reliable end-to-end security with real-time monitoring, and boost developer productivity.

We are continuing to embed AI capabilities directly into 麻豆原创 Integration Suite. will now automatically provide targeted recommendations and intelligent healing to resolve common API anomalies such as error spikes, latency surges, or abnormal traffic patterns. Developers can also ask Joule to about the most used APIs to gain deep API insights and understand usage patterns.

MCP Gateway support will enable customers to expose custom APIs and integration flows that can be consumed by AI agents. This feature introduces the ability for customers to enrich custom agents built in Joule Studio or extend Joule Agents by integrating data from third-party and legacy 麻豆原创 systems, composed as MCP tools for smooth agentic consumption. This approach standardizes access, centralizes governance and security, and simplifies discoverability in the .

To jumpstart integration projects, you can access hundreds of out-of-the-box integration adapters as well as pre-built API, event, and integration content on .

Gain security and operations built in, not bolted on

麻豆原创 BTP provides developers with a unified environment to manage applications, secure data, and scale solutions seamlessly across 麻豆原创 and third-party systems. With core centralized application lifecycle, interoperability, security, and administration capabilities, developers can easily and quickly resolve errors and boost team productivity. Read the full list of enhancements in the .

Explore at your own pace

If you missed attending 麻豆原创 TechEd in person or virtually, please be sure to read the full list of announcements in the  and watch .

Wherever you鈥檙e at in your journey, there are easy ways to get started:

• Visit to start a
• Explore and new 
• Register for our upcoming on December 9
• Read more in “Introducing 麻豆原创 Snowflake, New Data Fabric Innovations for 麻豆原创 Business Data Cloud and 麻豆原创 HANA Cloud“

Michael Ameling is general manager and chief product officer of Business Technology Platform and a member of the Extended Board of 麻豆原创 SE.

BERLIN 鈥� At 麻豆原创 TechEd in 2025, (NYSE: 麻豆原创) brings AI deep into the development process to level up how developers build.

New AI-driven capabilities in the 麻豆原创 Build solution, an expanding data ecosystem and powerful Joule Agents empower developers to move from idea to impact with unprecedented speed and confidence. As AI transforms the nature of professional work, 麻豆原创 also pledges to equip 12 million people worldwide with AI-ready skills by 2030.

鈥溌槎乖粹�檚 announcements today give developers the tools they need to deliver at the speed of AI,鈥� said Muhammad Alam, member of the Executive Board of 麻豆原创 SE. 鈥淚nnovations across 麻豆原创鈥檚 unique flywheel of applications, data and AI put developers in the driver’s seat — where they belong.鈥�

Opening the Developer Ecosystem

麻豆原创 Build, the company鈥檚 flagship solution for enterprise application development and automation, now gives developers more freedom to build, extend and automate using the tools they love most.

For instance, developers who prefer agentic development solutions like Cursor, Claude Code, Cline and Windsurf can now use 麻豆原创 development frameworks with new 麻豆原创 Build local Model Context Protocol Servers. Visual Studio Code users will be able to access 麻豆原创 Build capabilities directly in their development environment with a new 麻豆原创 Build extension. This extension will also be made available later on Open VSX Registry for other development environments. 麻豆原创 and n8n also announced plans for an integration so Joule Studio agents and n8n agents can work together.

And with new agent building capabilities in Joule Studio, developers have the tools they need to extend 麻豆原创鈥檚 ready-to-use agents and build new agents grounded in 麻豆原创 business data and context that can act autonomously based on changing business conditions.

Putting Data to Work

Every intelligent application starts with trusted data. 麻豆原创 is giving developers more ways to put that data to work through 麻豆原创 Business Data Cloud.

The solution now connects with more of the data and AI platforms developers use every day. A new 麻豆原创 Snowflake solution extension for 麻豆原创 Business Data Cloud brings Snowflake鈥檚 fully managed data and AI capabilities directly to 麻豆原创 customers, giving them the flexibility to choose the right compute and storage for each data and AI workload, while maintaining governance, interoperability and business context. 麻豆原创 also announced a new 麻豆原创 Business Data Cloud Connect partnership with Snowflake. This complements existing integrations with Databricks and Google Cloud, giving developers more freedom to choose how they work with 麻豆原创 data.

With a new data product studio capability in 麻豆原创 Business Data Cloud, developers can turn raw data into ready-to-use assets known as data products that support analytics, AI and application development.

An expanded capability in the 麻豆原创 HANA Cloud knowledge graph engine can automatically generate knowledge graphs. This capability maps relationships across 麻豆原创 database tables, columns and data models, revealing how data fits together and why it matters. Developers will be able to see how their data connects across systems and uncover underlying business insights.

Bringing AI Autonomy to Life

麻豆原创 is evolving its AI portfolio to give developers the intelligence and orchestration power they need to take AI from insight to action.

麻豆原创 introduced its first enterprise relational foundation model, a new class of AI that predicts business outcomes rather than the next word in a sentence. 麻豆原创-RPT-1, or the first-generation Relational Pre-trained Transformer, can make fast and accurate predictions for common business scenarios like delivery delays, payment risk or sales order completion. 麻豆原创 launched a free playground environment for developers today.

New AI assistants in Joule coordinate multiple agents across workflows, departments and applications, bringing automation and autonomy to life. These assistants plan, initiate and complete complex tasks spanning finance, supply chain, HR and beyond. Today, 麻豆原创 introduces new agents built for technical users. For example, an agent for business process analysis will help teams understand how processes run, identify inefficiencies and uncover opportunities to optimize workflows and drive measurable improvements.

Lastly, as AI changes the nature of work for everyone, 麻豆原创 is pledging to equip 12 million people worldwide with AI-ready skills by 2030. 麻豆原创 will expand hands-on training and certification programs that integrate practical AI-ready tools, including through its partnership with online learning platform Coursera.

Visit the . Get 麻豆原创 news via  and .

About 麻豆原创

As a global leader in enterprise applications and business AI, 麻豆原创 (NYSE:麻豆原创) stands at the nexus of business and technology. For over 50 years, organizations have trusted 麻豆原创 to bring out their best by uniting business-critical operations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit鈥�.

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This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ. Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of 麻豆原创鈥檚 2024 Annual Report on Form 20-F.
漏 2025 麻豆原创 SE. All rights reserved.
麻豆原创 and other 麻豆原创 products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of 麻豆原创 SE in Germany and other countries. Please see  for additional trademark information and notices.
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Enabled by 麻豆原创 Business AI and built on 麻豆原创 Business Technology Platform, the assistant is already delivering faster response times, enhanced supplier experiences and smooth multilingual automation.

With 38 shows across global cities and a workforce of almost 4,000 artists and staff from 80 countries, Cirque du Soleil鈥檚 operations are as dynamic as its performances. Managing more than 70,000 supplier invoices annually鈥攅specially from tour-supporting vendors at residency shows鈥攈as placed increasing pressure on the accounts payable team. Nearly 40 percent of inquiries are from vendors seeking invoice status updates, and these inquiries were often delayed due to limited visibility and manual processing.

To address this, Cirque du Soleil turned to 麻豆原创 Business AI. The company鈥檚 new AI-enabled invoice assistant automates the triage-and-response process for invoice-related emails. It analyzes incoming messages in all languages, identifies the request type, extracts invoice details, determines the status of each invoice and even captures the sentiment of the email, prioritizing those that need attention more urgently. The assistant then generates a proposed response in English and French, significantly reducing the average handling time from 30 minutes to just two minutes per inquiry.

鈥淭he time-consuming research required to identify the payment status of an invoice and its reason was overwhelming,鈥� said Philippe Lalumi猫re, vice president of information technology, Cirque du Soleil Entertainment Group. 鈥淲e were looking for a more efficient way to handle this, and 麻豆原创 Business AI provided us with a simply stunning answer.鈥�

The assistant leverages 麻豆原创 HANA Cloud to store and process structured data derived from incoming emails, along with analysis results and generated responses. 麻豆原创 AI Core foundation supports intelligent automation, enabling the assistant to detect urgency, sentiment and even root causes of payment delays. This has drastically reduced manual workload and improved supplier satisfaction.

“As we partner with Cirque du Soleil on this transformative journey, it鈥檚 inspiring to see how technology is streamlining operations and focusing organizations even more on what they do best鈥攄elivering unforgettable experiences,鈥� said Dr. Philipp Herzig, chief technology officer and chief AI officer at 麻豆原创 SE. 鈥淭his is a perfect example of how data and AI can unlock both creativity and efficiency.鈥�

Key benefits include:

• Efficiency: Automation frees up employee time and accelerates response rates.
• Accuracy: AI minimizes human error and helps ensure timely, contract-compliant payments.
• Multilingual support: Bilingual capabilities enable inclusivity across Cirque鈥檚 global supplier base.
• Scalability: The assistant handles high volumes without additional resources.
• Enhanced experience: Standardized, timely responses foster stronger supplier relationships.

With this innovation, Cirque du Soleil continues to lead not only in the world of live performance but also in operational excellence. 麻豆原创 remains a trusted partner in this journey, helping the company scale its global footprint while staying agile and responsive.

Visit the . Get 麻豆原创 news via  and .

Media Contact:
Lesa Plingen, +49 622 776 9000, lesa.plingen@sap.com, CET
麻豆原创 麻豆原创 Room; press@sap.com

Top image courtesy of Cirque du Soleil

This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ. Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of 麻豆原创鈥檚 2024 Annual Report on Form 20-F.
漏 2025 麻豆原创 SE. All rights reserved.
麻豆原创 and other 麻豆原创 products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of 麻豆原创 SE in Germany and other countries. Please see for additional trademark information and notices.

It鈥檚 time to rethink what a modern AI-ready database should look like.

麻豆原创 HANA Cloud solves this exact challenge with its single, multi-model platform that brings together vector, graph, text, spatial, and relational data natively. It enables developers and data teams to build smarter, more context-aware AI solutions 鈥� directly on operational data.

One database, every model: native support for complex AI workloads

麻豆原创 HANA Cloud uniquely supports:

• Vector data for semantic and similarity search
• Graph data for explicit relationship modeling and knowledge graphs
• Text and spatial data for real-world context
• Relational data for structured operations and analytics

Rather than sending data across disparate services, you can store and process all of it in one place, accelerating time-to-value while reducing the risk of misalignment.

This is multi-model done right, and it is the foundation for powerful AI workloads that scale.

Semantics + similarity: combining vector search with knowledge graphs

Traditional semantic search engines can tell you what documents are similar, but they cannot tell you why. On the other hand, knowledge graphs can express rich, explicit relationships, but often lack the ease of retrieval.

With 麻豆原创 HANA Cloud, you don鈥檛 have to choose; you get both. Bringing together 麻豆原创 HANA Cloud vector engine and 麻豆原创 HANA Cloud knowledge graph engine empowers developers to build context-aware, intelligent queries that go far beyond keyword matching.

Imagine asking: 鈥淔ind the nearest warehouse in Germany (~ 50 km radius of Frankfurt) for suppliers that are ISO 9001 certified, have low carbon tax rates, and are not flagged for customs delays.鈥�

We can conduct a multi-model query to find the warehouses that fit the above criteria.

Here, we are using a SPARQL table within 麻豆原创 HANA knowledge graph engine to filter the suppliers that comply to the following conditions: ISO 9001 certified, low carbon tax rates, not flagged for customs delays.

We can further combine the SPARQL_EXECUTE function in 麻豆原创 HANA knowledge graph engine with vector-based semantic filtering and spatial constraints to identify suppliers that are located within “~ 50 km of Frankfurt” and whose past custom report narratives align with 鈥渘o custom delays.鈥� This hybrid query leverages 麻豆原创 HANA Cloud vector engine, 麻豆原创 HANA Cloud knowledge graph engine, and spatial engine to rank nearby suppliers not only by distance, but also by their trustworthiness and performance signals.

After running these queries, we have the following supplier warehouses as our best match:

This is the power of semantics plus structure, and it is built into the core of 麻豆原创 HANA Cloud.

Unified queries: SQL, SPARQL, and vector search side by side

Developers must often stitch together multiple tools and languages: SQL for relational data, SPARQL for RDF, and separate APIs for vector stores.

麻豆原创 HANA Cloud removes that complexity. You can write a single SQL query that brings together relational data, semantic reasoning via SPARQL (embedded in SQL), and vector similarity search, using native SQL functions 鈥� all in one go: no ETL, no separate infrastructure, just one unified, in-memory engine.

This approach not only speeds up development, but enables new types of AI applications that were not previously practical in siloed environments.

Built for generative AI and RAG: GraphRAG, VectorRAG, HybridRAG

Large language models (LLMs) are only as good as the data they can reason over. That is why retrieval-augmented generation (RAG) has emerged as a critical pattern for enterprise generative AI.

We have brought in new capabilities into 麻豆原创 HANA Cloud, whether you are grounding an LLM in unstructured text (VectorRAG), structured knowledge graphs (GraphRAG), or both simultaneously (combination of VectorRAG and GraphRAG).

麻豆原创 HANA Cloud ensures transparency, traceability, and performance throughout the generative AI pipeline with all the database management qualities. You get explainable answers and full control over how you retrieve, rank, and assemble information, which is vital for regulated industries.

Real-world impact across industries

Enterprises across industries are already leveraging the multi-model capabilities of 麻豆原创 HANA Cloud for transformative outcomes:

• Supplier matching and environmental, social, and governance (ESG) scoring: Blend structured supplier data with document similarity and relationship insights to identify ideal partners
• Compliance monitoring: Connect and query policies, regulations, and audit trails with natural, semantic inputs
• Fraud detection: Analyze transactional data, behavioral signals, and known fraud patterns 鈥� all in real time
• Life sciences research: Integrate clinical trials, publications, and patient outcomes using hybrid semantic and structured queries

These are use cases where meaning is distributed across formats, systems, and relationships.

Developer experience: simplicity without compromise

麻豆原创 HANA Cloud offers developers:

• One platform for all data models: Combined structured, unstructured, and semantic data without stitching together multiple systems
• Built-in support for modern AI workloads: Enable use cases like RAG without external vector stores or pipelines
• Tight integration with 麻豆原创 and open ecosystems: Leverage 麻豆原创 Business Technology Platform and popular open-source tools with minimal setup
• Focus on innovation, not infrastructure: Eliminate the need to manage and maintain separate triplestores, search engines, or vector databases

The result is faster prototyping, cleaner architecture, and lower operational complexity.

Conclusion: It鈥檚 time to rethink your database

In the AI-first enterprise, data is not just a backend concern; it鈥檚 the front line of innovation. And innovation requires infrastructure that is flexible, intelligent, and unified.

麻豆原创 HANA Cloud provides building blocks to create the infrastructure for AI apps in a way that is easy to consume. It doesn鈥檛 just support AI workloads; it accelerates them, with a single platform that brings together semantics, similarity, and structure in real time.

AI needs more than just access to data and 麻豆原创 HANA Cloud delivers that, natively.

Key takeaways

• Unified multi-model: Vector, graph, spatial, text, and relational data all in one platform
• Smart queries: Compose intelligent queries using SQL, SPARQL, and vector search 鈥� side by side
• Generative AI-ready: Built for GraphRAG, VectorRAG, and HybridRAG with full explainability
• Reduced complexity: No need for separate vector stores or knowledge graph engines

Philipp Herzig is CTO, chief AI officer, and a member of the Extended Board of 麻豆原创 SE.
Stefan Baeuerle is senior vice president and head of 麻豆原创 BTP/麻豆原创 HANA & Persistency at 麻豆原创.

As the world鈥檚 No.1 fireworks provider, French pyrotechnics company Etienne Lacroix ships fireworks globally and has supported events such as the Burj Khalifa Grand Opening Fireworks Show in Dubai and Bastille Day, France鈥檚 national holiday that is celebrated on July 14 each year.

Logistics play a major role for the global player in the pyrotechnics sector, as shipping hazardous materials such as fireworks requires special precautions, especially when crossing international borders. Labels typically include warning pictograms and complex regulatory information in various formats. Recipients such as customs officers must be able to tell at a glance what sort of goods are inside, what the required shipping conditions are, and who is authorized to open the freight.

鈥淥n top of that, customers have their own specific requirements,鈥� , director of Information Systems at Etienne Lacroix explains. 鈥淎lso, there are different color codes in place for hazmat, depending on the country of destination. Red may mean danger in European countries, but in China, for example, it stands for celebration. Green has a different meaning in the Middle East that it does in the U.S., and so on.鈥�

With so many different regulations in place around the globe, labeling the shipments at the end of the production line is not only time-consuming, but also leaves a lot of potential for human error. Now, with support from 麻豆原创 partner STMS and 麻豆原创, the prototype for a generative AI solution was introduced that has the potential to reduce human involvement to a minimum.

Business AI Co-Innovation Project with 麻豆原创 partner STMS

In early 2024, , general manager at STMS SOLUTIONS, a longtime partner of both 麻豆原创 and Etienne Lacroix, participated in a event where 麻豆原创 partners leveraged 麻豆原创 technology to address pain points of their customers. The idea for a generative AI use case came up, and STMS approached its customer Etienne Lacroix.

At that time, IT and business experts at Etienne Lacroix were very interested in how generative AI could assist them in making their processes easier. 

鈥淏ut I have to admit, I was also a little skeptical,鈥� Marini says. 鈥淓verybody is currently talking about AI, about how to introduce it to the industry and the huge benefits we will reap from leveraging it. But suggestions are scarce when it comes to implementing it in a way that guarantees the company will benefit from it.鈥�

鈥淭ogether, we looked at the pain points of the company and discussed possible use cases with 麻豆原创 Co-Innovation Lab,鈥� Faure says. 鈥淲e received the requirement from the business that AI should help avoid human tasks that are error-prone and don鈥檛 actually add value.鈥�

Supply Chain Use Case with Generative AI

The team quickly identified that the administrative process of creating labels for shipping was a task currently performed by human employees that required a huge amount of time and focus. The huge potential for the usage of generative AI was evident. 

鈥淲ith guidance from experts from the 麻豆原创 partner organization, we were able to build a specific 麻豆原创 app on and 麻豆原创 S/4HANA to organize and use AI,鈥� Faure says. 鈥淲e then collected feedback from the business experts at Etienne Lacroix and, in the next step, brought in the generative aspect.鈥�

To meet the regulations from the customer, the developers from STMS aggregated all the necessary data and created a model on 麻豆原创 HANA Cloud vector engine.

Thanks to 麻豆原创 HANA Cloud vector engine, which was newly introduced in 2024, 麻豆原创 Business AI can allow customers and partners to leverage large language models (LLMs) in a much more accurate way on multi-model database 麻豆原创 HANA Cloud. In case of the generative AI use case for Etienne Lacroix, the LLM was ChatGPT 3.5 Turbo.

鈥淭echnically, this prototype leverages everything 麻豆原创 has to offer in terms of AI right now,鈥� Faure says. 鈥淭he app uses 麻豆原创鈥檚 generative AI hub and 麻豆原创 HANA Cloud vector engine to draw on all the necessary information and generate the label.鈥�

The remaining human task is to validate whether everything on the label is correct. 鈥淭hat was the most important requirement,鈥� Marini says. 鈥淗uman intervention must be guaranteed, as with all AI use cases.鈥�

鈥淚t鈥檚 the generative aspect that makes all the difference,鈥� Miliau Pape from 麻豆原创 Co-Innovation Lab says. The LLM suggests what should go on the specific label鈥攕uch as warning pictograms鈥攂ased on legal regulations, historical customer requirements, cultural standards, and so on. The Retrieval-Augmented Generation (RAG) provides the LLM with context and makes the outcome relevant and reliable. 鈥淪imply put, when the AI is trying to be as creative as possible, the RAG provides guardrails, so it doesn鈥檛 potentially go wild and come up with nonsense,鈥� Pape says.

For each shipment, a prompt draws on destination, shipping route, specific customer data, such as the storage and language this customer required the last time, or the colors or signs used to indicate that the shipment contains hazardous materials and can only be opened by experts with a certain certification.

鈥淢y first thought when I saw this, was鈥攕imply put鈥攚ow,鈥� Marini says. 鈥淲ow, they actually did it. Wow, this will make our lives easier. This generative AI use case, at this point, may still be only a prototype, but it鈥檚 an applicable idea, an actual use case for an actual pain point in our company.鈥�

鈥淭o show the world of possible, push the boundaries of the technology鈥攖hat is the purpose of the exercise,鈥� Pape says.

Etienne Lacroix Group is in the process of migrating to . With the components of the app ready on 麻豆原创 Business Technology Platform, go-live is planned for 2025.

鈥淥ur ERP was aging and no longer very popular with business users,鈥� Marini says. 鈥淢igration to 麻豆原创 S/4HANA gives us access to the newest technologies such as generative AI. This motivates users to take ownership of their IT solutions again and brings our business and IT together. All in all, it allows our company to fully exploit the potential of our 麻豆原创 system.鈥�

He adds: 鈥淭he generative AI solution for labeling shipments is a tangible proof of the power of AI, a real use case, and we have it in our company. It is a very decisive first step in our AI journey.鈥�

Hamburg has more bridges than any other city in Europe. For Germany鈥檚 second largest city it鈥檚 a complex task to maintain its 2,500 bridges and other structures like pedestrian tunnels, locks, flood barriers, and embankments.

The State Agency for Roads, Bridges and Waterways (LSBG) operates a large portion of the traffic infrastructure in Hamburg and is responsible for the entire lifespan of these public works.

鈥淲e鈥檙e an important player in flood protection and the prevention of water pollution as well as the maintenance of most roads and bridges in Hamburg,” Erdinc Karabugday, head of Planning and Controlling at LSBG, shares. “Together with our network, we build and protect everything that keeps Hamburg together.鈥�

麻豆原创 technology is one building block to perform this duty safely and efficiently.

Free Flow of Traffic as Top Priority  

Mobility plays a key role in the lives of people in Hamburg and other major cities. Bridges bear a particularly heavy load, because they are critical junctions in the city鈥檚 transportation network. Tracking the condition of bridges and planning for their maintenance needs and upgrades is vitally important to keep people moving in urban areas.

Karabugday describes the problem in a nutshell: 鈥淥ur objectives are long term, so basing operational decisions solely on the current situation isn鈥檛 enough. We need comprehensive data for the strategic context 鈥� not only economic aspects, but social and ecological impacts as well. Our 麻豆原创 solution supports us with this.鈥�

The manual entry of damage to structures like bridges used to be very expensive and time-consuming, a complex process made even more difficult by the fact that data entry and analysis are performed by both the agency鈥檚 own staff and external companies.

Digital Representation of Infrastructure

To reduce Hamburg鈥檚 renovation backlog and create a sustainable long-term solution, LSBG teamed with 麻豆原创 to develop a standardized data platform. One central aspect involves merging data from a variety of sources on , making it possible to blend data such as the location and condition of each structure. The results feed into a digital model of streets and bridges and can be used to guide decisions and generate precise forecasts for maintenance and budget planning.聽

Ulrike Brecht, architect advisor in Customer Advisory Public Sector at 麻豆原创 Germany, explains: 鈥淭he project was initially intended to handle bridge maintenance. Employees conduct the necessary maintenance work and inspections on site. They also document the condition of a structure, ensuring that necessary maintenance measures are carried out at the right time.鈥�

All available data on the structures, including road and bridge data as well as geographic and monitoring data, is merged in 麻豆原创 HANA Cloud. When combined with aging models for the structures, this information can be used for forecasting when specific road segments will require resurfacing, for instance.

These data-driven forecasts put infrastructure budget planning on a new, firmer foundation and make it possible to define the priorities for object renovation to minimize the impact on traffic flows and the lives of urban residents.

Future Urban Platforms

Cities around the world face enormous challenges in the coming years when it comes to protecting and maintaining their residents鈥� quality of life. Dr. Philipp Schulz was a research assistant at the University of Heidelberg and wrote his doctoral thesis on digital urban development. Today, he advises cities and communities on topics like revitalizing inner cities, redesigning public spaces, and civic participation.

One trend Schulz has observed in the cities and towns he works with is the development of urban dashboards that show all the data collected in a city as important parameters such as air quality, weather forecasts, and movements of people.

For Schulz, developing a long-term digital strategy is one of the pillars of modern urban planning.

鈥淔rom my perspective the term 鈥榮mart city鈥� is outdated,鈥� he says. 鈥淭oday I call it 鈥榩latform urbanism,鈥� an approach in which different players and their information are brought together on one platform.鈥� Platform urbanism describes how apps and websites are changing the way people in cities live, work, and interact with one another. It involves the digitalization of individual areas, which are then brought together incrementally.

The city of Hamburg is on the right track. 鈥淗amburg鈥檚 goal is to handle the full maintenance management of its infrastructure through a standardized data platform,鈥� says Brecht.

The city is in the process of expanding the accomplishments of this project to other areas, such as the maintenance of public parks and municipal buildings.

麻豆原创 HANA Cloud is a market-leading database-as-a-service enabling intelligent data applications and is one of the most adopted services within 麻豆原创 Business Technology Platform (麻豆原创 BTP) internally at 麻豆原创. As of today, more than 180 different applications and services use 麻豆原创 HANA Cloud with its multi-model capabilities.

Now, 麻豆原创 HANA Cloud is also a leader in the generative AI age.

At 麻豆原创, we work with various LLMs such as GPT-4, Llama2, Falcon-40b, and Claude2. While these models offer amazing opportunities, they also have limitations. For example, LLMs may rely on outdated training data and lack company-specific data and business process context.

As an example, imagine having an LLM as a colleague. This colleague would be very intelligent, able to program, pass exams, or have arguments 鈥� but this colleague would not know anything about what happened in the world in the past year, nor have any idea about internal processes of your company or any of your systems. Even worse, after every conversation you have, this colleague would forget what you just talked about. Working with such a lack of memory would be of limited value. This shortcoming is why an LLM cannot answer easy questions like 鈥淲hat do you think about the offer from our most important supplier last week?鈥� An LLM can only work with the initial training data 鈥� all other data must be provided as context.

Supplementing this lack of information is where 麻豆原创 HANA Cloud vector engine can assist. The engine can provide LLMs with all the relevant data of an organization through a process called “retrieval-augmented generation.”

A Game-Changing Feature

So how does the vector engine work? It is a new addition to 麻豆原创 HANA Cloud’s multi-model engines, enabling customers to utilize the similarity between two or more vectors to solve business problems. With the integration of AI-focused technology, 麻豆原创 HANA Cloud can now empower businesses to combine intuition along with data-driven insights to solve even the most complex of problems.

Some key benefits and features of the vector engine include:

• Multi-model: Users can unify all types of data into a single database to build innovative applications using an efficient data architecture and in-memory performance. By adding vector storage and processing to the same database already storing relational, graph, spatial, and even JSON data, application developers can create next-generation solutions that interact more naturally with the user.
• Enhanced search and analysis: Businesses can now apply semantic and similarity search to business processes using documents like contracts, design specifications, and even service call notes.
• Personalized recommendations: Users can benefit from an improved overall experience with more accurate and personalized suggestions.
• Optimized large language models: The output of LLMs is augmented with more effective and contextual data.

The Database Foundation of 麻豆原创鈥檚 Generative AI Strategy

The addition of the vector engine establishes 麻豆原创 HANA Cloud as the default database in 麻豆原创’s generative AI solution strategy. Customers can create the next level of user experiences along with other services within 麻豆原创 BTP. As an example, 麻豆原创 BTP can provide centralized access to SaaS-based LLMs from multiple vendors as well as host LLMs from open-source models or third parties. The generative AI hub in 麻豆原创 AI Core, a capability that facilitates the use of generative AI capabilities, will soon rely on 麻豆原创 HANA Cloud as the primary vector storage. One function of the generative AI hub feature is to help provide a process for creating embeddings and storing the resulting vectors in 麻豆原创 HANA Cloud. Customers building intelligent data applications can use both services together to augment LLM queries with relevant context for meaningful answers.

麻豆原创 is working on foundation models that are specific for 麻豆原创-related industry and process knowledge.

The Database for Innovation

麻豆原创 HANA Cloud continues to lead the market by storing and processing different types of relevant business data 鈥� all within the same database. The new vector engine, combined with other multi-model capabilities, opens a world of possibilities for applications to help enhance the execution of business processes. Whether improving search capabilities, gaining deeper insights for informed decisions, or optimizing LLMs, 麻豆原创 HANA Cloud enables the type of applications that can elevate the expertise and effectiveness of every user.

To learn more, sign up for . Do you already have a use case for 麻豆原创 HANA Cloud vector engine in mind? If so, consider registering for the .

Juergen Mueller is CTO and member of the Executive Board of 麻豆原创 SE, Technology & Innovation.
Stefan Baeuerle is head of Database, 麻豆原创 HANA Database, & Analytics for Technology & Innovation at 麻豆原创.

Recognizing this potential, the City of Antibes and have joined forces to redefine digital contract management with a focus on public procurement processes. Patrick Duverger, chief technology officer of the City of Antibes, describes its previous procurement operations as follows: 鈥淎lthough we achieved a high level of operational proficiency, our business processes lacked full traceability. This resulted in process opacity when it comes to recurring delays, delivery errors, or administrative sanctions. By gaining a deeper understanding of our processes, we can optimize them, reduce costs, and minimize business risks.鈥� 

Transparent and Traceable Collaboration 

The lack of visibility and traceability in these processes hindered automation, cross-organizational data and process mining, and intelligence. This directly affected how disputes were resolved and impacted organizational budgets.聽

To address this challenge, 麻豆原创 Innovation Center Network developed a prototype based on the service, combined with a blockchain-based shared ledger on 麻豆原创 HANA Cloud. 鈥淭his prototype aims to replace manual practices with automated, cross-company orchestrations. By using an 麻豆原创 HANA Cloud shared ledger, organizations like the City of Antibes can benefit from a permissioned, publicly verifiable, and immutable audit trail of cross-organizational interactions,鈥� says Benjamin Stoeckhert, innovation product manager at 麻豆原创 Innovation Center Network, illustrating the potential of this innovation.聽

鈥淟everaging the full potential of an 麻豆原创 HANA Cloud shared ledger allows us to connect digital platforms that unite businesses and government to track the compliance of services and product deliveries according to contractual terms and conditions,鈥� explains Duverger. 鈥淲e can leverage data from different parties, such as logistics companies and quality certification bodies, and move beyond the era of cumbersome paperwork and manual processes. For example, this pattern is applicable to procurement processes where multiple parties verify the compliance of suppliers and their deliveries.鈥�

Complete Control of Unencrypted Data 

However, opening up collaborative processes directly conflicts with customer privacy concerns. This dilemma poses a significant challenge for next-generation contract management. How can businesses ensure transparency without compromising the privacy of private business information and processes? Duverger emphasizes the importance of protecting sensitive public procurement secrets: 鈥淐onfidentiality, including negotiated prices and deal sizes, is paramount for us and our suppliers.鈥� 

In response to this pressing need, the 麻豆原创 Security Research team, in collaboration with the 麻豆原创 Innovation Center Network blockchain team, has extended 麻豆原创 Cross-Company Workflow Collaboration with a hardware-based privacy-enhancing technology (PET) innovation. Dr. Laurent Gomez, who led this innovation with Antibes, explains: 鈥淏efore committing a transaction to the shared ledger, organizations encrypt it along with its associated sensitive information, using their own managed cryptographic material. Encrypted data and processes are only processed within secure and trusted hardware modules, with the explicit consent of each stakeholder.鈥澛�

This innovation can unlock significant business value by helping to automate cross-company operations and protect the privacy of customer data while still allowing for analysis. The key contribution of this approach is that it gives customers complete control and ownership of their encrypted material. 鈥溌槎乖� can never access unencrypted data; the only data that leaves our information system is encrypted by us,鈥� says Duverger. 鈥溌槎乖� Business Technology Platform (麻豆原创 BTP) allows us to hold our own encryption keys, which is different from competing solutions.鈥� 聽

5% Less Late Payment Penalty Costs 

The co-innovation has revealed the bottlenecks that slow down the procurement process at the City of Antibes and lead to late payment penalties for suppliers and delivery delays. 鈥淏y adopting this secure distributed ledger approach, we have improved these key performance indicators without changing the process itself. We can now reliably manage all our procurement transactions,” says Duverger. “A key achievement was that we reduced our delinquency rate by 5%, which significantly minimized the impact of late payment penalty costs on our global spend budget.鈥澛�

The project was recently recognized at the highest national level with the Territoria Gold Award by the French Ministries of the Interior, Ecological Transition, and Territorial Cohesion.

To find out more about 麻豆原创 Cross-Company Workflow, get in touch with us at icn@sap.com.

Corinna Schmidt is part of NVT Communication at 麻豆原创.

WALLDORF 鈥� (NYSE: 麻豆原创) and Amazon Web Services Inc. (AWS), an Amazon.com Inc. company (NASDAQ: AMZN), today announced that 麻豆原创 HANA Cloud now supports AWS Graviton processors.

麻豆原创 is extending its cloud-native, in-memory database to AWS Graviton-powered Amazon Elastic Compute Cloud (Amazon EC2) instances to take advantage of AWS鈥檚 price, Performance and energy efficiency benefits.

Thousands of joint customers depend on solutions from AWS and 麻豆原创 to run their mission-critical business processes. As customers build data-driven, intelligent applications that enable users to make more precise and faster decisions, their compute and memory demands grow. These customers require solutions that lower costs without compromising performance and energy efficiency. By choosing to run 麻豆原创 HANA Cloud on AWS Graviton, 麻豆原创 can optimize its compute costs and allow its customers to benefit from these efficiencies.

鈥淎WS and 麻豆原创 have a long history of delivering value in a way that is environmentally responsible,鈥� said Juergen Mueller, Chief Technology Officer and member of the Executive Board of 麻豆原创 SE. 鈥淭his collaboration with AWS on the use of Graviton demonstrates our commitment to reduce the impact of our technologies on the environment while continuing to provide value in the solutions we bring to market.鈥�

鈥淥ne of the most visible ways we are innovating is improving the power efficiency of AWS chips,鈥� said David Brown, vice president of Amazon EC2 at AWS. 鈥淥ur Arm-based AWS Graviton3 processors deliver the best performance per watt of energy use in Amazon EC2, bringing a powerful combination of energy efficiency and price performance to 麻豆原创.鈥�

Arm-based AWS Graviton processors leverage AWS鈥檚 extensive expertise in systems design and cloud infrastructure to deliver the best price performance over comparable x86-based instances for a variety of workloads running in Amazon EC2. By migrating 麻豆原创 HANA Cloud to AWS Graviton-based Amazon EC2 instances, 麻豆原创 has seen up to 30% better compute performance for analytical workloads and lowered its compute costs by 15%. And with Graviton3-based instances using up to 60% less energy for the same performance than comparable EC2 instances, 麻豆原创 can reduce the compute carbon footprint of the workloads of 麻豆原创 HANA Cloud by an estimated 45%. AWS Graviton3 also supports the latest DDR5 memory, which provides 50% higher memory bandwidth compared to DDR4, to improve the performance of memory-intensive applications.

As a signatory of Amazon鈥檚 The Climate Pledge, 麻豆原创 is actively working alongside 427 organizations in 38 countries to help reduce carbon emissions and ultimately improve the environment. By choosing to run 麻豆原创 HANA Cloud on AWS Graviton, 麻豆原创 can further its efforts to reduce its carbon footprint and support efforts to address the climate crisis. 麻豆原创 and AWS have a longstanding relationship spanning back to 2008, when 麻豆原创 developed and tested the 麻豆原创 NetWeaver technology platform 鈥� the underpinning of 麻豆原创 S/4HANA and many other cloud solutions from 麻豆原创 on AWS. Today, 麻豆原创 customers continue to use AWS across 麻豆原创鈥檚 cloud enterprise portfolio through the RISE with 麻豆原创 solution and 麻豆原创 Business Technology Platform (麻豆原创 BTP). In addition, the 麻豆原创 NS2 Secure Data Cloud service, which is designed for public sector and defense customers with uniquely stringent security and compliance requirements, uses AWS to deliver trusted and secure solutions. Amazon companies, including Twitch, Zappos.com and Zoox Inc., also rely on 麻豆原创 software on AWS to support their national and global operations.

麻豆原创 plans to expand its use of AWS Graviton in the future to take advantage of the performance gains, cost savings and energy efficiencies.

To learn more about 麻豆原创 HANA Cloud, visit . To learn more about AWS Graviton processors, visit .

Visit the . Follow 麻豆原创 at .

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Top image: AWS Graviton3 processor. Courtesy of AWS.

This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ. Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of 麻豆原创鈥檚 2022 Annual Report on Form 20-F.
漏 2023 麻豆原创 SE. All rights reserved.
麻豆原创 and other 麻豆原创 products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of 麻豆原创 SE in Germany and other countries. Please see for additional trademark information and notices.

In an interview, Mueller shares 麻豆原创鈥檚 amazing generative AI journey with partners and customers that鈥檚 supercharging generative AI development and how companies operate.

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Q: What are the top three things that developers, IT professionals, and business leaders need to know about the at 麻豆原创 TechEd 2023?

A: First, we want every 麻豆原创 ecosystem developer to become an AI developer and we are rolling out new tools, leveraging generative AI, to help them build and deploy intelligent data applications at scale.

Second, we are simplifying interactions between large language models (LLMs), enabling developers to implement intelligent data for generative AI applications. By expanding 麻豆原创 HANA Cloud database capabilities with a vector engine, developers can combine the generic LLMs and gain the context they need with company-specific real-time data.聽

Third, is the choice for infusing 麻豆原创 and partner applications with AI. By embedding generative AI into our solutions and giving developers, partners, and customers access to all our technology and learnings through 麻豆原创 BTP, 麻豆原创 is the go-to partner for business AI and generative AI-powered enterprise applications. We already have 22,000 live 麻豆原创 BTP customers in the cloud.

Lastly, our ecosystem is critical for all our efforts to provide our customers with beneficial innovations for their digital transformation. We have 2,100 partners on 麻豆原创 BTP, and there are 2,000 innovative partner solutions on the today. More than 360 of these solutions offer AI capabilities that drive business value.

Can you give us a snapshot of the major announcements this year?

Each of these advancements reflects 麻豆原创鈥檚 commitment to become the No. 1 generative AI enterprise application ecosystem together with our partners and supported by our platform, 麻豆原创 BTP.

• 麻豆原创 Build Code offers AI-powered productivity tools for developers. It鈥檚 an exciting evolution of the 麻豆原创 BTP low-code solution that we launched last year. Our unified lobby of tools enables enhanced collaboration between citizen developers, professional developers, and IT departments. Developers will be able to create new applications or extensions for 麻豆原创 solutions using our generative AI assistant Joule to generate code, create data models, and test data for applications.
• New vector capabilities for 麻豆原创 HANA Cloud allow developers to enrich business data with unstructured data including text, images, and audio. This is a unique offering from 麻豆原创, as customers will be able to combine the intelligence of LLMs with their business-specific data to provide accurate, relevant, and insightful responses. is the database management foundation of 麻豆原创 BTP.
• AI Foundation on 麻豆原创 BTP is our one-stop-shop for developers to build business-ready AI applications and extensions on 麻豆原创 BTP. From ready-to-use AI services to AI runtimes and lifecycle management, we鈥檙e providing the tools developers need to manage enterprise-grade generative AI with security, governance, and trust. As part of AI Foundation we will also include a generative AI hub in 麻豆原创 AI Core to provide developers with instant access to a broad range of LLMs from different providers.
• Learning is foundational to 麻豆原创鈥檚 ambitious goal to upskill 2 million professionals by 2025. Our newly announced role-based certification for ABAP Cloud back-end developers will drive expert skillset growth for agile cloud business transformation. Moreover, we鈥檝e supplemented the with a new , which explains how to build and implement business applications on 麻豆原创 BTP.

How do 麻豆原创 solutions help developers, data scientists, business users, and other professionals power their personal success and organization鈥檚 growth?

麻豆原创 is already at the forefront of generative AI advancements. Over 24,000 cloud customers are actively using more than 130 AI scenarios built on 麻豆原创 BTP. We have the business data, processes, and customer relationships, and we believe that most business AI capabilities will be consumed in an embedded way.

麻豆原创鈥檚 unique access to business data and our industry depth — together with our foundation in ethics, data privacy, compliance, and security — mean that we鈥檙e able to deliver unparalleled automation and seamless human-machine collaboration capabilities to our customers.

Most important, 麻豆原创 Business AI is relevant, reliable, and responsible. In our trusted environment, people are creating relevant AI use cases in the context of their organization鈥檚 real-world business processes and embedded into their daily 麻豆原创 systems. These use cases are reliable because they鈥檙e based on an understanding of both the business data and what it means within the business process.

Finally, our AI is responsible as it is built on leading ethics and data privacy standards.

How are customers and partners generating business results from 麻豆原创 BTP generative AI capabilities?

Many of our partners are pioneering multiple generative AI use cases with our support.

麻豆原创 partner and customer HCLTech is using AI technology to simplify daily tasks like recruiting in 麻豆原创 SuccessFactors software for speed and efficiency in finding the best job candidates. They鈥檙e developing a catalog of generative AI-infused processes across industries and line-of-business use cases. India鈥檚 Mahindra & Mahindra, which has automated more than 250 business processes in just three months using 麻豆原创 Build Process Automation, has piloted two generative AI use cases.

In Brazil, social enterprise startup SDW brings clean water to over 20,000 people. The company used 麻豆原创 Build Apps to develop an app that speeds up field worker collaboration and analyzes accurate data to help measure the impact of its services against KPIs, proving ROI that boosts investments for growth. Henkel is co-innovating with 麻豆原创 on its first large-scale generative AI use case, combining natural language processing, simulation, and planning to make decisions faster.

Can you preview what developers should expect from 麻豆原创鈥檚 generative AI vision as we head into 2024?

We are building AI capabilities, including our new generative AI copilot Joule, into our cloud-based enterprise applications. This includes 麻豆原创鈥檚 just ask feature in , available in Q1 2024. We鈥檒l also continue expanding access to LLMs in the generative AI hub. Watch for more generative AI use cases that will be released in the first half of 2024.

麻豆原创 Unveils Innovations in Generative AI Application Development and Vector Database Capabilities as Well as New Learning Opportunities for Developers in the Era of AI

鈥淭oday鈥檚 dynamic technology and business landscape means every developer needs to be an AI developer,鈥� said Juergen Mueller, Chief Technology Officer and member of the Executive Board of 麻豆原创 SE. 鈥淭he innovations we鈥檙e launching at 麻豆原创 TechEd, from AI-infused pro-code tools to a one-stop shop to create generative AI extensions and applications on 麻豆原创 Business Technology Platform, support the developers at the heart of the AI revolution and provide them with resources they need to transform the way businesses run.鈥�

As organizations aim to derive business value from generative AI, effective collaboration between professional and citizen developers is essential. 麻豆原创 is launching the 麻豆原创 Build Code solutions, which streamline cooperation with business experts who use the low-code 麻豆原创 Build solutions launched at 麻豆原创 TechEd in 2022. Uniquely built for 麻豆原创 applications and the 麻豆原创 ecosystem, 麻豆原创 Build Code solutions offer AI-powered productivity tools for developers and are optimized for Java and JavaScript development. 麻豆原创 Build Code also draws on the power of 麻豆原创鈥檚 new generative AI copilot Joule 鈥� the copilot that truly understands business 鈥� to further boost productivity, embedding code generation capabilities for data model, application logic and test script creation.

Good data is the foundation of good AI, and 麻豆原创 HANA Cloud continues to pioneer innovation in the data space by adding new vector database features to its multimodel offerings at no additional cost. Vector data stores manage unstructured data 鈥� such as text, images or audio 鈥� to provide long-term memory and better context to AI models. This makes it easy to find and retrieve similar objects quickly. For example, users can search for suppliers based on the language in their contracts to examine payment history and trace individual orders. These powerful new vector database features enhance interactions between large language models and an organization鈥檚 mission-critical data. The innovation helps put 麻豆原创 developers at the forefront of delivering radically new levels of data insight within a secure, private framework that uses industry-specific customer data to reduce hallucinations.

AI Foundation on 麻豆原创 BTP, a new one-stop shop for developers to create AI- and generative AI-powered extensions and applications on 麻豆原创 BTP, will further help increase developers鈥� impact and efficiency. AI Foundation includes everything developers need to start creating business-ready AI tools on 麻豆原创 BTP 鈥� from ready-to-use AI services and access to the top large language models to vector database capabilities and AI runtime and lifecycle management.

The rapid pace of technological innovation has driven up global demand for skilled developers 鈥� and 麻豆原创 is increasing its learning opportunities in tandem. As part of a commitment to upskill two million professionals by 2025 and complement free AI learning content already available, 麻豆原创 today launched and free learning resources for back-end developers using the ABAP Cloud development model. The two new learning resources covering ABAP development tools on 麻豆原创 BTP and 麻豆原创 S/4HANA are available on the . They are designed for agile and cloud-compliant business transformation, providing developers with skills to build cloud-ready extensions that are aligned with 麻豆原创鈥檚 clean core strategy. 麻豆原创 has also joined the Stanford HAI (Institute for Human-Centered AI) . Researchers and engineers at 麻豆原创 will work with the Stanford academic community, including research faculty and students, on the intersection of generative AI and business.

For details on all the announcements made at 麻豆原创 TechEd in 2023, please .

Visit the 麻豆原创 News Center. Follow 麻豆原创 at .

About 麻豆原创

麻豆原创鈥檚 strategy is to help every business run as an intelligent, sustainable enterprise. As a market leader in enterprise application software, we help companies of all sizes and in all industries run at their best: 麻豆原创 customers generate 87% of total global commerce. Our machine learning, Internet of Things (IoT), and advanced analytics technologies help turn customers鈥� businesses into intelligent enterprises. 麻豆原创 helps give people and organizations deep business insight and fosters collaboration that helps them stay ahead of their competition. We simplify technology for companies so they can consume our software the way they want 鈥� without disruption. Our end-to-end suite of applications and services enables business and public customers across 26 industries globally to operate profitably, adapt continuously, and make a difference. With a global network of customers, partners, employees, and thought leaders, 麻豆原创 helps the world run better and improve people鈥檚 lives. For more information, visit .

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This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ. Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of 麻豆原创鈥檚 2022 Annual Report on Form 20-F.
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As the NHL continues to grow, the League continues to prioritize technology adoption to help advance the game and provide more engagement opportunities for fans.

Chris Foster, NHL vice president of Digital Business Development, explains: 鈥淎s our relationship with 麻豆原创 grows and technology advances, we pivot quickly to meet new demands and address our challenges with intuitive technology through 麻豆原创 Preferred Success services.鈥�

Unlocking the Power of Data with Partnership

The NHL is a rich tapestry of unforgettable moments, legendary players, and enduring passion that has captured the hearts of fans worldwide. To inspire and keep generations of new fans entertained and engaged, the League understands the importance of continuously innovating the experience in the arena and through its national broadcast partners.

鈥淥ur digital transformation efforts are not only boosting fan engagement across NHL platforms, but also increasing parity among our 32 clubs,鈥� Foster says. 鈥淲e are looking at data differently, ensuring it reaches the right people 鈥� our fans, players, coaches, and clubs.鈥�

This mindset on finding opportunity in data launched a series of innovations focused on enhancing the game and improving venue sustainability. With 麻豆原创 Preferred Success, to implement a platform that jump-started its ability to build and expand use cases over time to help meet changing business dynamics and objectives.

鈥溌槎乖� Preferred Success is instrumental in making all this work,鈥� Foster underscores. 鈥淎ccess to personalized, prescriptive recommendations from subject-matter experts and quality reviews enables us to create a customized and personalized solution.鈥�

Connecting Fans with Their Favorite Clubs

The first project the NHL delivered in collaboration with 麻豆原创 was transforming 鈥� creating a definitive destination for hockey analytics. Last season alone, more than 100 million data-hungry NHL fans engaged with the site’s intuitive dashboards and filters to analyze the performance of their favorite clubs and players and compare them to past NHL legends.

鈥淲e saw the potential to create a one-stop shop that uses stats to better connect our audiences with their favorite players and teams, understand the strategy of the game, and see trends more broadly across the League,鈥� Foster shares.

Working with 麻豆原创 Preferred Success, the NHL tapped into a database that has evolved into to help store and manage data points like never before. The effort digitalized more than 100 years of historical hockey data and introduced new and enhanced statistics in a way that enthusiasts can find visually appealing.

Foster adds: 鈥淭here are also unlimited storytelling opportunities as we provide our fans with a personalized and interactive experience.鈥�

Elevating Plays with Data Intelligence

Following the digitalization of its stats, the NHL co-developed one of the most significant technologies resulting from its partnership with 麻豆原创 Preferred Success 鈥� the , which runs on the League鈥檚 iPads. 麻豆原创 HANA Cloud again serves an integral role as the processing power that helps translate all in-game hockey data from the arena and the NHL’s system to the mobile app.

鈥淎s the fastest game on ice, there are millions of data points to be collected and analyzed every second across our 32 clubs,鈥� Foster says. 鈥淲e knew we needed to deliver a tool that could serve every club with very different expectations, different coaching staff structures, and different responsibilities.鈥�

Equipped with the advisory checks introducing development and administration readiness, capability advisory, and design discovery that 麻豆原创 Preferred Success offers, the NHL increased developer productivity for the mobile app development. Making real-time, customizable player statistics and data visualizations accessible during the game allows coaching staffs to adjust in-game tactics and achieve new levels of individual player and club performance.

For example, the data tiering functionality of the 麻豆原创-NHL Coaching Insights mobile app on the League鈥檚 iPads differentiates between in-game and past seasons’ NHL EDGE Puck and Player Tracking data. In-game data is analyzed in real time with the quick in-memory processing of 麻豆原创 HANA Cloud, processing puck and player position coordinates every 30 milliseconds. Meanwhile, gigabytes of NHL EDGE Puck and Player Tracking data are archived instantly, stored cost-effectively and securely, and reactivated readily and swiftly for further analysis.

Throughout this use case, 麻豆原创 Preferred Success helped the NHL better understand the stability of the system to reduce data duplication and storage while still providing a powerful processing engine that brings accurate data to the user rapidly. The services also helped deliver security and connectivity reviews and performance optimizations to help ensure the NHL coaching staffs have the best possible experience. In fact, with visualizations made possible by the solution, the League can review each clubs鈥� app usage to improve the app further and tailor it to their evolving needs.

Going Green with NHL Venue Metrics

In addition to elevating the fan experience and enhancing the game on the ice, the NHL is also working to reduce its ecological impact while preserving the sport’s roots for future generations. The League developed to collect, process, and report energy and water consumption, waste generation, and recycling frequency across NHL clubs and arenas 鈥� which plays a key position in its NHL Green platform.

The end-to-end, cloud-based application is the NHL’s latest and extended use of 麻豆原创 Business Technology Platform (麻豆原创 BTP), delivered through the prescriptive guidance of 麻豆原创 Preferred Success. Data is processed through 麻豆原创 HANA Cloud and visualized with 麻豆原创 Analytics Cloud, helping give venues the insights to embed sustainability best practices into their business operations wherever possible.

鈥淭he development of NHL Venue Metrics enables us to define new sustainability goals and standards as a League,鈥� Foster remarks.

Building a Future of Game-Changing Outcomes

A critical lesson the NHL learned throughout its experience with 麻豆原创 Preferred Success is the value of expert guidance and support 鈥� fast-paced innovation enabled through skillful teamwork. Each step in the League’s innovation journey progresses with best practices, targeted learning, in-depth release guidance, and prioritized incident handling 鈥� all aimed at evolving and improving the overall growth of the game.

鈥淲e certainly have clear goals and specific objectives for the future of the NHL. But it’s equally important to have in-depth expertise to ensure business solutions are doing all they can to help us reach our vision. It takes experience in seeing what others have done, what’s worked well, and what you should avoid,鈥� Foster reflects.

By working with 麻豆原创 Preferred Success, the NHL gained a trusted partner that helps it map out and provide prescriptive advice on configuration steps, modeling, performance testing, and more. All this work culminates in a smooth rollout and adoption experience across NHL club coaching staffs.

Foster concludes: 鈥淥ur collaboration has allowed us to continue to evolve and deliver additional stable and reliable applications that increase productivity, improve efficiency, and reduce costs.鈥�

To learn more about the value of 麻豆原创 Preferred Success and how the NHL is innovating, look at the following resources:

Amit Lodhe is global solution owner of 麻豆原创 Preferred Success for 麻豆原创 BTP at 麻豆原创.

Top image courtesy of the NHL

It’s a special thrill for Team Liquid fans, as both teams 鈥� the Dota 2 and the League of Legends squad 鈥� have qualified for the championships and will compete for the title. We tapped into our connection with Team Liquid and had the exclusive opportunity to talk to two team members, Haitham 鈥淗aitham鈥� Algbory, head analyst of the League of Legends team, and Mathis 鈥淛abbz鈥� Friesel, assistant coach and analyst of the Dota team, about how they prepare the teams for the world championships and what role 麻豆原创 technology plays for the teams to perform at their top level.

A big part of what 麻豆原创 brings to Team Liquid is , which helps make data analysis for both League of Legends and Dota a lot easier. The database allows the analysts to focus less on gathering data and more on analyzing it. Both Jabbz and Haitham have been working in this field for a long time, and there are things that they can do now that they never could before, thanks to a tool specifically made for esports data analysis.

鈥淚 support both the general manager and the coaching staff with scouting new talent,鈥� Haitham said. 鈥淭he way I do that is by providing periodic solo queue and scrim reports and end-of-season scouting reports. When it comes to the Academy teams of the East Regions, at the same time, we just track the players that are in the scene in general and we see their improvement based off the metrics that we have set in our tools.鈥�

On the League of Legends side, 麻豆原创 HANA Cloud is Haitham鈥檚 primary tool for scouting. But that鈥檚 not what Jabbz uses the data for. For Team Liquid Dota, the data is more match-focused.

鈥淔or us, 麻豆原创 HANA Cloud has more of a different function,鈥� Jabbz said. 鈥淲e use it mostly for performance-related things. I think the big advantage we have with the database is that we can actually import any public game that we want. Let鈥檚 say things have changed in a recent patch; we can make sure that we鈥檙e always up-to-date with how the meta is evolving. We also get to have a replay of every tournament game, so we can pick up all the information we need from any game, especially during live events. This is incredibly helpful. By having this tool available, you can quickly see how teams are adapting, how teams are thinking. I save a lot of time getting that information, whereas before I would have to open up the replays in the game and manually scroll through everything.鈥�

According to Haitham, being able to use real gameplay clips to corroborate the data 鈥� and vice versa 鈥� often helps build a stronger case for whatever argument he鈥檚 trying to make. Players are more inclined to believe the data once they have a reference point, which then allows them to gain a deeper understanding of the game.

鈥淲ith 麻豆原创, we have a lot of good [visualization] tools,鈥� Haitham said. 鈥淲e have an entire map tool that will just visualize where the wards are and what the movement is looking like. In addition, we have 麻豆原创 Analytics Cloud that gives us an opportunity to build charts and graphs for the players. I would use videos or clips that are important to show the opponent鈥檚 style, and then I support that with the maps or graphs from the 麻豆原创 tools.鈥�

For some, all these details might sound small, even insignificant. However, any coach or analyst will tell you that at the highest level of esports, the difference lies in the details. When pretty much every player is equal in skill, it鈥檚 those minor advantages that matter 鈥� which makes data analysis an important factor for success. After all, a close win is still a win. Both Haitham and Jabbz point to 鈥渢he small margins鈥� as the reasons why they love their roles as analysts.

鈥淧ersonally, I work on my own goal to help others achieve theirs at the same time,鈥� Haitham said. 鈥淪eeing how players are able to use science while playing video games, to beat opponents that they may not be able to without that kind of information鈥t just makes everything worthwhile.鈥�

鈥淚 agree. I think it鈥檚 always very satisfying to give information to the guys that they wouldn鈥檛 pick up on,鈥� Jabbz added. 鈥淚 guess we鈥檙e very similar in that regard. I also enjoy helping the guys and that鈥檚 what gives me the joy in this job. I don鈥檛 necessarily have to see myself in the limelight or at the front of the stage, but I really just like seeing my friends succeed.”

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Isabelle Schuhmacher is director of Global Sponsorships at 麻豆原创.
Christian Kreidt is storytelling lead for Global Sponsorships at 麻豆原创.

Photos courtesy of Team Liquid.

麻豆原创 data and analytics solutions were recognized with the following 2023 Best Of awards:

• in the Cloud Data Warehouse market category
• in the Predictive Analytics, Business Intelligence, and Corporate Performance Management market categories
• in the Embedded Database, Database-as-a-Service (DBaaS), Data Virtualization, In-Memory Databases, and Relational Databases market categories

Unleash the Power of Business Data with 麻豆原创 Datasphere

is a comprehensive data solution that can enable every data professional to deliver seamless and scalable access to mission-critical business data. It can provide a unified experience for data integration, data cataloging, semantic modeling, data warehousing, data federation, and data virtualization.

In a recent review, a TrustRadius customer described 麻豆原创 Datasphere as 鈥渆legant and robust.鈥� They went on to say that 麻豆原创 is 鈥渆xcellent at ensuring data integrity by eliminating duplications鈥� and that 麻豆原创 Datasphere can 鈥渉andle large volumes of data at ease [and] the efficiency of data virtualization makes modeling easy.鈥� Read more of the review .

Build Intelligent Data Applications with 麻豆原创 HANA Cloud

is a modern database as a service powering the next generation of intelligent data applications 鈥� self-learning and self-adapting applications that leverage built-in analytical and operational database capabilities to provide new experiences. 麻豆原创 HANA Cloud can empower users to build intelligent data solutions with cloud-native scalability, speed, and performance.

Megan Headley, vice president of Research at TrustRadius, noted: 鈥淩eviewers on TrustRadius appreciate 麻豆原创 HANA Cloud鈥檚 low administrative overhead, speedy data processing, and ease of use for new users.鈥�

Bring Together Analytics and Planning with 麻豆原创 Analytics Cloud

supports trusted insights and integrated planning processes enterprise-wide to help you make decisions without doubt. It can automate data-driven insights with the power of machine learning, helping you utilize the full context of 麻豆原创 data so that you can bring analytics closer to the point of decision.

麻豆原创 Analytics Cloud is the 鈥渂est financial planning and analytics innovative cloud solution,鈥� noted one TrustRadius reviewer. 鈥溌槎乖� Analytics Cloud is an innovative and solid product to improve FP&A, analytics, and consolidation [for] cloud-based business transformation processes.鈥� Learn more in the .

Give Data Purpose with 麻豆原创 Data and Analytics Solutions

Data and analytics empower business users to make informed decisions with 麻豆原创 solutions. 麻豆原创 Datasphere, 麻豆原创 Analytics Cloud, and 麻豆原创 HANA Cloud can work together seamlessly to help provide trusted insights while easily integrating into your business processes.

We鈥檙e honored that our customers have made their voices heard and we are proud that TrustRadius has recognized our products as top rated. Thank you to our passionate data and analytics customers for your continued support.

Learn more about .

Daniel Yu is senior vice president of Solution Management and Product Marketing for 麻豆原创 Data and Analytics at 麻豆原创.

As a manufacturer supporting hundreds of leading brands in just about every industry, Jabil is adept at helping companies bring products to market with speed and agility, including smart home appliances and electronics, industrial machinery, cloud computing solutions, energy storage systems, and telecommunications infrastructure.

Customers depend on Jabil for everything from product design and engineering through volume manufacturing, assembly, quality testing, procurement, and logistics, which is why the company has undergone a massive digital transformation moving to .

鈥淲e鈥檝e seen marked improvements in speed because we鈥檙e on an database,鈥� said Cynthia Kendall, IT director at Jabil. 鈥淚n addition, bringing our ERP applications into the cloud has given us significant improvements in scalability from business transparency. For example, we now have visibility into all open sales orders by facility in just seconds, versus what historically took over an hour.鈥�

Jabil is a longtime 麻豆原创 customer, and the two companies share numerous business objectives, notably a commitment to innovation and sustainability. At this year鈥檚 , Kendall showcased how the company working with 麻豆原创 was inherent to its cloud-first strategy.

Connected Data Speeds Up Operations

It鈥檚 no understatement to say that Jabil is complex. The multi-billion dollar, Florida-based company employs over 250,000 employees who serve customers from more than 100 sites, totaling over 500 million square feet of manufacturing space 鈥� the equivalent of 868 football fields. Digitalization that connects accurate data across these vast operations has boosted accurate planning and forecasting. As a result, Jabil can react faster to customer demands.

鈥淲e鈥檝e increased efficiencies with inventory management, capturing real-time data on materials in stock as products are finished,鈥� said Kendall. 鈥淲e have exact numbers on the components and materials available for each product as they鈥檙e produced. This data speeds up our ability to build, ship, and invoice products.鈥�

Cloud-First Business Results

Staying on top of fast-moving innovations that continuously redefine customer markets is core to Jabil鈥檚 growth strategy. Kendall said that the company鈥檚 move to 麻豆原创 S/4HANA has provided the entire organization with critical flexibility.

鈥淪ince moving to the cloud, we鈥檝e resized our app servers; what once took days is now completed in hours,鈥� she said. 鈥淲e鈥檝e collapsed a number of servers into a larger one, requiring less time to manage. This has allowed our business to explore how to transform and innovate in this new 麻豆原创 S/4HANA landscape in ways that we could never do before.鈥�

Future-Proof Strength Amidst a Sea of Change

Jabil鈥檚 customers are selling products worldwide, facing increasingly stringent and rapidly changing global regulations. This reality was behind one of the company鈥檚 decisions to migrate to the cloud with 麻豆原创.

鈥淚t didn鈥檛 make sense to keep customizing our legacy 麻豆原创 solutions,鈥� said Kendall. 鈥溌槎乖� S/4HANA provides the platform we need to build advanced capabilities aligned to the evolving compliance mandates and market demands facing our customers.鈥�

Supply Chain Resiliency Despite Disruptions

Having gone live with 麻豆原创 S/4HANA during the pandemic, Jabil鈥檚 innovation is well underway with pilots designed to help achieve business goals in a dramatically different environment of supply chain and other disruptions.

鈥淲e鈥檙e showing the business many opportunities that weren鈥檛 available before,鈥� said Kendall. 鈥淓specially in production planning, we are able to make faster, better-informed decisions. Even in the face of supply chain shortages, this will help us make educated and nimble decisions moving forward with what we can actually manufacture and when we can manufacture it.鈥�

Start Now to Forge a Path to Innovation

More than anything, Jabil鈥檚 journey with 麻豆原创 is a tremendous opportunity for the company to transform and innovate. Kendall鈥檚 advice to other organizations was clear.

鈥淓mbrace the fact that you鈥檒l need to migrate to 麻豆原创 S/4HANA, and start planning now,鈥� she said. 鈥淓ven if your project isn鈥檛 kicking off for another six months or later, there are things you can do today to prepare for the journey so you鈥檒l be future-ready for tomorrow.鈥�

This pragmatic advice and expert insight into 麻豆原创 S/4HANA migration planning is at the heart of , the company鈥檚 new 麻豆原创 S4-as-a-Service offering developed by practitioners for practitioners to help streamline and simplify 麻豆原创 S/4HANA Cloud migrations.

To hear more from customers on their digital transformation journey with 麻豆原创, .

Susan Galer is communications director at 麻豆原创. Follow me @smgaler.

• New Offering Will Unite 麻豆原创 with Google Cloud鈥檚 Data and Analytics Technology, Making Enterprise Data More Open and Valuable and Advancing Enterprise AI Development

The offering enables customers to build an end-to-end data cloud that brings data from across the enterprise landscape using the solution together with Google鈥檚 data cloud, so businesses can view their entire data estates in real time and maximize value from their Google Cloud and 麻豆原创 software investments.

Data is the cornerstone of digital transformation and AI development. Organizations spend significant resources building complex data integrations, custom analytics engines, and and natural language processing (NLP) models before they start to realize value from their data investments. Data originating from 麻豆原创 systems, in particular, is among organizations鈥� most valuable assets and can contain critical information on supply chains, financial forecasting, human resources records, omnichannel retail and more. 麻豆原创 Datasphere combines this mission-critical data with data from across the enterprise landscape, regardless of its origin. Being able to combine 麻豆原创 software data and non-麻豆原创 data on Google Cloud from virtually any other data source, means organizations can dramatically accelerate their digital transformation with a fully defined data foundation that retains complete business context.

鈥淏ringing together 麻豆原创 systems and data with Google鈥檚 data cloud introduces entirely new opportunities for enterprises to derive more value from their full data footprints,鈥� said Christian Klein, CEO and member of the Executive Board of 麻豆原创 SE. 鈥溌槎乖� and Google Cloud share a commitment to open data and our extended partnership will help break down barriers between data stored in disparate systems, databases and environments. Our customers not only benefit from the business AI already built into our systems, but also from a unified data foundation.鈥�

鈥溌槎乖� and Google Cloud now offer an incredibly comprehensive and open data cloud, providing a foundation for the future of enterprise AI,鈥� said Thomas Kurian, CEO, Google Cloud. 鈥淔ew resources are as important to digital transformation as data. By deeply integrating 麻豆原创 software data and systems with our data cloud, customers will be able to utilize our analytics capabilities as well as advanced AI tools and large language models to find new insights from their data.鈥�

麻豆原创 and Google Cloud鈥檚 new open data offering complements the RISE with 麻豆原创 solution and will enable customers to:

• Access business-critical data in real time: The integration between 麻豆原创 Datasphere and Google Cloud BigQuery allows customers to access their most critical data in real time without data duplication. This joint offering can unify data from 麻豆原创 software systems, such as 麻豆原创 S/4HANA and 麻豆原创 HANA Cloud, providing organizations with a comprehensive view of their most important data on Google data cloud.
• Simplify data landscapes: 麻豆原创 and Google Cloud co-engineered powerful data replication and federation technologies, which allow businesses to integrate 麻豆原创 software data with BigQuery environments and leverage 麻豆原创 and Google Cloud鈥檚 leading data analytics capabilities. Now, customers can federate queries across 麻豆原创 Datasphere and BigQuery to blend data from 麻豆原创 and non-麻豆原创 software. This eliminates common data silos from sources that span marketing, sales, finance, supply chain and more. For example, customers with wholesale business distribution models can now have full visibility into their products as they go through the sales pipeline and reach customers.
• Create trusted insights with Google Cloud鈥檚 advanced AI and machine learning (ML) models: Businesses will be able to use Google鈥檚 AI and ML services to train models on data from 麻豆原创 and non-麻豆原创 systems.
• Perform advanced analysis: Organizations can utilize the analytics capabilities of the 麻豆原创 Analytics Cloud solution in Google Cloud to analyze financial and business outcomes while improving the accuracy of models. With a simple integration to data in BigQuery with 麻豆原创 Datasphere, customers can plan with a single, comprehensive view of their businesses.
• Utilize joint solutions for sustainability: 麻豆原创 and Google Cloud are exploring ways to combine 麻豆原创 Datasphere with broader ESG data sets and insights powered by Google Cloud to accelerate sustainability journeys with actionable insights.
• Use (麻豆原创 BTP) on Google Cloud globally: 麻豆原创 will advance its multi-cloud offerings by expanding regional support of 麻豆原创 BTP and on Google Cloud, which includes support for 麻豆原创 Analytics Cloud and 麻豆原创 Datasphere. 麻豆原创 and Google Cloud intend to launch 麻豆原创 BTP in five new regions this year, building to a total of eight regions supported by 2025.

The companies also plan to partner on joint go-to-market initiatives for enterprises鈥� largest data projects, enabling customers to adopt data products from both 麻豆原创 and Google Cloud. Visitors to the 麻豆原创 Sapphire conference can see demos of joint AI and data solutions at Google Cloud鈥檚 booth. These include how enterprises can apply generative AI to common workflows and applications, such as using a chatbot to search, create and edit purchase requests. The 麻豆原创 Sapphire conference takes place May 16鈥�17 in Orlando, Florida.

Visit the 麻豆原创 News Center. Follow 麻豆原创 on Twitter at .

About Google Cloud

Google Cloud accelerates every organization鈥檚 ability to digitally transform its business. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology 鈥� all on the cleanest cloud in the industry. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

About 麻豆原创

麻豆原创鈥檚 strategy is to help every business run as an intelligent, sustainable enterprise. As a market leader in enterprise application software, we help companies of all sizes and in all industries run at their best: 麻豆原创 customers generate 87% of total global commerce. Our machine learning, Internet of Things (IoT), and advanced analytics technologies help turn customers鈥� businesses into intelligent enterprises. 麻豆原创 helps give people and organizations deep business insight and fosters collaboration that helps them stay ahead of their competition. We simplify technology for companies so they can consume our software the way they want 鈥� without disruption. Our end-to-end suite of applications and services enables business and public customers across 25 industries globally to operate profitably, adapt continuously, and make a difference. With a global network of customers, partners, employees, and thought leaders, 麻豆原创 helps the world run better and improve people鈥檚 lives. For more information, visit .

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Innovative brands have realized this.

Zwift 鈥� a massive multiplayer online cycling and running program that enables users to train, interact, and compete in a virtual world 鈥� recently embraced inclusion by adding a hand-cycling that allows physically challenged athletes to race in the metaverse alongside able-bodied athletes. And it鈥檚 not alone. Earlier last year, Degree Deodorant hosted the world’s first on the Decentraland metaverse with a 26.2-mile picturesque course along the platform鈥檚 Vegas City Sports Quarter district, which reflected a more inclusive landscape with structures such as ramps for wheelchair users.

But How Does This Help Businesses?

Research shows that inclusion strengthens social networks, reduces barriers, and increases trust to generate economic benefits. Businesses that incorporate inclusivity are more likely to make bolder and better decisions. Meanwhile, sports possess the ability to transcend linguistic, cultural, social, and, now, physical barriers. With the metaverse looming large over the foreseeable horizon, a convergence of sports and inclusivity could serve as a lighthouse for business and society 鈥� a truly mouthwatering prospect of things to come. But is there an addressable market for this to make business sense?

There are 5.07 billion active Internet users in the world today 鈥� 50,000 already Web 3.0 virtual worlds and 12% of U.S. Internet users are interested in using the metaverse. Digital avatars contribute immensely to the virtual experience and are increasing becoming ubiquitous.

Per the U.S. Census Bureau, 12.8% of the U.S. population in 2019 registered as people with disabilities. The European equivalent that year was 39 million 鈥� Great Britain alone accounted for 11 million 鈥� while Asia had an estimated 135 million people with disabilities. The global fitness platform market for the disabled alone is expected to hit US$1.41 billion this year, a CAGR of 23.9%.

So, there is clearly an audience for this type of inclusivity. But why bother the metaverse with it?

Answering the Community鈥檚 Call

Digital avatars contribute immensely to the virtual experience and are increasing becoming abundant. In fact, online communities are demanding greater inclusivity. A revealed a general underrepresentation of people with disabilities and women, alongside an inaccurate representation of online identities. With 57% of Gen Z metaverse-gamers their penchant for in-game self-expression as higher than in real life, developers are taking note. Last June, Meta the launch of wheelchairs, over-the-ear hearing aids, and cochlear implants for its avatars. As the metaverse takes shape, inclusivity features prominently on the social media giant鈥檚 development agenda.

And it is just not Meta. Companies developing gaming consoles are building for inclusivity as well. From Xbox Adaptive Controllers to community-built modified controllers, features to assist those with mobility, hearing, and impaired vision are gaining prominence. Gaming companies are also modifying popular games for impaired gamers. For instance, The Last of Us II 鈥� the game from the company Naughty Dog 鈥� now has play modes for deaf, blind, and mobility-impaired gamers. Likewise, colorblind players can now enjoy the hugely popular Call of Duty: Black Ops thanks to a new mode that customizes the game鈥檚 display to create a spectrum of options to suit a player鈥檚 specific need.

Clearly, the metaverse can be a great enabler of inclusivity and open new doors.

A New Vista of Inclusion Opportunities Powered by the Metaverse

Imagine a metaverse loaded with features that welcome all to coexist in the surrounds of a safe virtual haven. Events like the marathon and my annual cycling event can become regular features in the metaverse, much like those in the real world today.

Add cutting-edge sports performance analytics from to this and challenged participants can receive a significant boost for their efforts of being recognized as competitive athletes. In fact, in the highly competitive world of Paralympics where every inch matters, teams that can get their hands on 麻豆原创 Sports One can integrate data from various sources and study consolidated insights from all the athletes on their team with real-time analytics. At the highest levels, where the gold medal is decided by seconds, even challenged athletes deserve the very best and can benefit from what cutting-edge performance analytics can offer. In the esports world today, organizations like readily use 麻豆原创 data and analytics solutions such as and to help make split second decisions and heighten their performances on the professional circuit.

With such precedents in place, the metaverse becomes a prime greenfield of opportunities and facilitates the development of an environment where inclusivity can genuinely thrive. This, coupled with gamification and play-to-earn models, can lead to the creation of an ecosystem in the metaverse that nurtures a virtual economy with limitless horizons. Brands and technology companies that are building an inclusive metaverse will enjoy numerous revenue-generating avenues and enhanced social agendas.

We are at the dawn of exciting times for sure.

To learn how software helps clubs and organizations digitalize sports performance management, visit .

Richard Whittington is senior vice president of Sports, Media, & Entertainment at 麻豆原创.

TrustRadius shares unbiased reviews from authenticated users across a variety of industries and identifies the top-performing products. The Winter 2023 Best Of awards highlight solutions that have earned outstanding customer feedback regarding their features, price, and support.

麻豆原创 data and analytics solutions maximize the value within all data for the most impactful decisions. We view this recognition from TrustRadius as a testament of our mission to give data purpose, connect business processes, and accelerate innovation.

We鈥檙e honored that our data and analytics solutions have been recognized with the following awards:

• : Best Feature Set, Best Value for Price, and Best Relationship in the Relational Databases category
• : Best Feature Set, Best Value for Price, and Best Relationship in the Cloud Data Warehouse category
• : Best Feature Set, Best Value for Price, and Best Relationship in the Master Data Management category
• : Best Feature Set, Best Value for Price, and Best Relationship in the Data Fabric category

Modernize the Data Foundation with 麻豆原创 HANA Cloud

is a modern database as a service powering the next generation of intelligent data applications and analytics across all enterprise data. It empowers users to build data solutions with cloud-native scalability, speed, and performance.

Megan Headley, vice president of Research at TrustRadius, noted, 鈥淩eviewers on TrustRadius appreciate 麻豆原创 HANA Cloud鈥檚 low administrative overhead, speedy data processing, and ease of use for new users.鈥�

One TrustRadius reviewer noted, 鈥淚t鈥檚 great to run mission-critical operations in real time from anywhere, introduce new business models within the industry, and expand globally with a trusted partner.鈥� They also mentioned that it 鈥渞educes the complexity of multi-cloud or hybrid system landscapes鈥� and that the support is 鈥渁lways great.鈥� Read the for more.

Make Data Meaningful with 麻豆原创 Data Warehouse Cloud

goes beyond traditional data warehousing to provide a multi-cloud, multisource business semantic service for enterprise analytics and planning. This software as a service helps users to better understand business data and make decisions based on real-time information.

鈥淏uyers have a wide range of cloud data warehouse products to choose from,鈥� said Headley. 鈥淥n TrustRadius, reviewers highlight 麻豆原创 Data Warehouse Cloud鈥檚 no-code data modeling tools and no-ETL connections to data sources.鈥�

In a recent evaluation, one TrustRadius reviewer called it 鈥渢he future of cloud data warehousing.鈥� They went on to say that 鈥渆nd users have way more flexibility in making changes to the models without interference from IT鈥� and that 麻豆原创 Data Warehouse Cloud 鈥渋s the first tool [they鈥檝e] seen that can easily facilitate self-service data warehousing from a business user point of view.鈥� Find out more in the .

Manage Data Centrally with 麻豆原创 Master Data Governance

A unified, trusted view of a business allows for working more efficiently and making better decisions. The application helps pull together master data and manage it centrally using a master data management layer based on (麻豆原创 BTP).

鈥淩eviewers of 麻豆原创 Master Data Governance on TrustRadius appreciate the product鈥檚 impact on their data integrity and robust auditing capabilities,鈥� said Headley.

A TrustRadius reviewer mentioned, saying 鈥渢his program is just intuitive鈥� and it 鈥渟hortened the time to bring a solution to the client.鈥� The customer is 鈥渁ble to maintain [their] master data without the worry of having a duplicate moving in from another system or being created downstream.鈥� For more information, read the .

Integrate Data Across the IT Landscape with 麻豆原创 Data Intelligence Cloud

is a comprehensive data management solution supporting data fabric implementations. As the data orchestration layer of 麻豆原创 BTP, it transforms distributed data sprawls into vital data insights, supporting innovation and business growth.

Headley stated that 鈥渞eviewers on TrustRadius highlight 麻豆原创 Data Intelligence鈥檚 self-service data catalog, data lineage tools, and data integration capabilities.”

鈥溌槎乖� Data Intelligence suits all business scenarios that encompasses data,鈥� noted one TrustRadius reviewer. 鈥淚t simplifies exploration, enticement, modeling and visualization of data.鈥� The reviewer also mentioned that it helps them 鈥渋ntegrate data from flat files and external applications, process, and manage it in one spot.鈥� Learn more in the .

Give Data Purpose with 麻豆原创 Data and Analytics Solutions

Data and analytics are at the core of enterprise decision-making. 麻豆原创 data and analytics solutions bring together data warehousing, management, and integration to deliver trusted insights on a modern, open cloud architecture. These solutions empower users to retain the full perspective of their 麻豆原创 data and facilitate seamless integration with their business processes.

To us, this recognition from TrustRadius represents the voice of our customers. We鈥檙e proud that our products have inspired such gracious feedback in the user community, and we thank our passionate data and analytics customers for their support.

To learn more, visit the .

Daniel Yu is senior vice president of Solution Management and Product Marketing for 麻豆原创 Data and Analytics at 麻豆原创.

The Magic Quadrant provides an overview of the major technology players in the CDBMS market and positions them according to their completeness of vision and ability to execute. The CDBMS market includes vendors that supply fully provider-managed public or private cloud software systems that manage data in cloud storage. Gartner recognizes technology providers that perform highly in both the completeness of their vision and their ability to execute as a Leader.

We believe that the Gartner acknowledgement reflects our ability to perform well today while remaining in a position of strength for tomorrow.

Data is the heart of the intelligent enterprise, and data volumes are increasing exponentially. At 麻豆原创, we are committed to simplifying our customers鈥� digital transformation journeys with a business-centric cloud data and analytics portfolio that leverages existing investments, delivers live insights, and provides the ability to create action plans for improved business performance.

We view this recognition from Gartner as a testament to our mission to help organizations transform their data strategy and give data purpose.

The Data-First Approach

Our data and analytics solutions, which include 麻豆原创 HANA Cloud and 麻豆原创 Data Warehouse Cloud, maximize the value of 麻豆原创 data by using its complete business context and meaning for the most impactful decisions.

麻豆原创 HANA Cloud is our cloud-native database as a service that is uniquely suited for modern applications and analytics. It powers mission-critical applications at a petabyte scale and manages data more efficiently with multi-tiered storage. With its built-in design and runtime capabilities for smart multi-model processing and embedded machine learning, 麻豆原创 HANA Cloud is our powerful database foundation for intelligent data applications.

Developed using 麻豆原创 HANA Cloud, 麻豆原创 Data Warehouse Cloud is our central hub for advanced analytics and data unification. It is a multi-cloud, multi-source business semantic layer for enterprise analytics and planning. 麻豆原创 Data Warehouse Cloud enables organizations to centrally define business semantics and federate data access across systems.

We were recognized as a Leader with our 麻豆原创 HANA Cloud and 麻豆原创 Data Warehouse Cloud solutions being evaluated. Both include a wide range of modern features, multicloud, intercloud, and hybrid compatibility, and a comprehensive integration into the wider 麻豆原创 and non-麻豆原创 application ecosystems.

Next Steps

If you鈥檙e ready to unlock the full potential of your data with a unified cloud data and analytics solution, take the next step with the following resources:

• Read the full complimentary
• Explore
• Try and for free

JG Chirapurath is chief marketing and solutions officer for 麻豆原创 Business Technology Platform.

Gartner, Magic Quadrant for Cloud Database Management Systems, Henry Cook, Merv Adrian, Rick Greenwald, Xingyu Gu, December 13, 2022.
Gartner research publications consist of the opinions of Gartner鈥檚 research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and/or its affiliates and are used herein with permission. All rights reserved.
This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document.

To better understand customer needs around translytical platforms, Forrester Research has studied many real-time offerings and evaluated them for suitability across multiple dimensions such as architecture, translytical functions, data handling, streaming, and security.

An intelligent enterprise consistently applies advanced technologies and best practices within agile, integrated business processes and can wisely plan yet act in the moment. But to respond accurately in real time, organizations must analyze transactions as they are generated and correlate diverse signals from ever-growing data sources. Moving and aggregating data can undermine agility and increase vulnerabilities; thus the need for translytical data platforms with all workloads running simultaneously on the same database.

Translytical data platforms are a crucial technology to combat data sprawl and reduce the number of data copies by allowing users to run real-time analysis on the transactional systems themselves.

The translytical capabilities of 麻豆原创 HANA Cloud turn data into business value by supporting a variety of workloads and use cases, including real-time transaction processing, streaming analytics, machine learning, and rapid operational reporting within a single database. Our various cloud and on-premise deployment options deliver a high level of openness, scalability, and flexibility for customers. 麻豆原创 HANA Cloud has built-in design and runtime capabilities for smart multi-model processing, combined with integrated multi-tier storage, making it uniquely suited to support intelligent data applications.

When it was released over 10 years ago, 麻豆原创 HANA was one of the biggest innovations in enterprise information technology. By combining analytical and transactional processing in a single in-memory database, 麻豆原创 brought a radically different approach to the database market.

The in-memory performance and unique architecture of 麻豆原创 HANA Cloud, however, enabled 麻豆原创 to do just that: dramatically changing the game by enabling customers to attain real-time visibility across their businesses. 麻豆原创 HANA Cloud continues to impact customers — such as , , , and the — in all industries.

Data and analytics solutions from 麻豆原创 maximize the value of 麻豆原创 data by uniquely using the complete business context and meaning for the most impactful decisions. For us, this report鈥檚 conclusion is a testament to our mission to help organizations transform their data strategy and give data purpose.

To learn more, visit the . For a deeper dive into The Forrester Wave™: Translytical Data Platforms 2022, download a .

Daniel Yu is senior vice president of Solution Management and Product Marketing for 麻豆原创 Data and Analytics.

This recognition represents the voice of our customers. Each solution received dozens of reviews from customers in the past year, ranking their overall satisfaction, use cases, return on investment, and likelihood to recommend.

At 麻豆原创, we pride ourselves on providing our customers the technology they need to build intelligent, sustainable enterprises. Our success ultimately comes down to one thing: the success of our customers. Regardless of industry or region, every organization is facing similar challenges 鈥� the need to digitally transform and build more sustainable practices while facing supply chain challenges, a growing skills gap, and macroeconomic headwinds. Our customers鈥� ability to digitally transform in this environment and future-proof their business is what drives us and their ongoing partnership 鈥� the constant feedback and collaboration 鈥� is what enables us to keep transforming and innovating alongside them.

With 麻豆原创 Business Technology Platform (麻豆原创 BTP), our customers can easily integrate and build applications across their systems, streamline their workflows and processes, and unlock insights across all their data. The comprehensive portfolio of solutions spans across application development, automation, integration, data and analytics, and artificial intelligence (AI). 麻豆原创 BTP is the only platform in the world that is purpose-built for the 麻豆原创 ecosystem.

Below are just a few of the reviews from our customers for the five solutions recognized on the Best Software List.

麻豆原创 Analytics Cloud, a solution of 麻豆原创 Business Technology Platform, brings together analytics and planning with unique integration to 麻豆原创 applications and smooth access to heterogeneous data sources.

鈥溌槎乖� Analytics Cloud offers stunning data visualizations and superb dashboard suggestions. It has reduced data processing operational costs by using no code and automation that bridge the gap between processing to analysis. It unifies BI and CPM tools into one single solution. And it’s a quick and effective way to impress every level of management. It helps me to visualize the data more effectively.鈥� 鈥�

麻豆原创 Data Warehouse Cloud, the multisource business semantic service of 麻豆原创 Business Technology Platform, provides data modeling, connectivity, virtualization, and access across the enterprise.

鈥淏ased on my expertise, 麻豆原创 Data Warehouse Cloud is the best data modeling solution that I have ever used. It automates the entire process of visualizing data through machine learning and AI tools.鈥� 鈥�

麻豆原创 HANA Cloud is a single database-as-a-service (DBaaS) foundation for modern applications and analytics across all enterprise data, allowing businesses to gain trusted, actionable information from a single solution while enabling security, privacy, and anonymization with proven enterprise reliability.

鈥淲e use 麻豆原创 HANA to manage and retrieve data. Its user interface allows us to solve any business problem easily and accurately. As a large organization with many clients, we often work with large data sets and 麻豆原创 HANA never lets us down. This helps us with data analysis and can help us with decision-making, especially on live data.鈥� 鈥�

麻豆原创 S/4HANA Cloud is a complete modular cloud enterprise resource planning (ERP) solution designed for every business need, powered by AI and analytics, to help businesses run mission-critical operations in real time from anywhere, introduce new industry business models, and expand globally.

鈥溌槎乖� S/4HANA Cloud is ready for the ERP business transformation in the current changing digital era. I would recommend it for the below digital transformations: organizations that manage huge amounts of data and want to leverage a cloud platform; someone looking for quick response time and fast data processing; to leverage modern analytical capabilities and enhance business planning/decision making. It’s an investment for the future that optimizes process flow, offers innovation (AI/machine learning), simplifies landscape, and increases ROI.鈥� 鈥�

麻豆原创 SuccessFactors is a comprehensive, global suite of HR solutions spanning core HR and payroll, learning and talent management, HR analytics and workforce planning, and employee experience management.

鈥溌槎乖� SuccessFactors has allowed us to change and manage our business while staying relevant in the market. We have re-engineered process and employee experience while maintaining compliance and staying ahead of risk.鈥� 鈥�

to hear about the latest 麻豆原创 technology news and developer innovations.

JG Chirapurath is chief marketing and solutions officer for 麻豆原创 Business Technology Platform at 麻豆原创.

This end-to-end, cloud-based platform developed by 麻豆原创 enables the NHL to measure and analyze the carbon footprint generated by its Clubs and arenas across various areas, including energy, water, waste, and recycling. These insights will allow the NHL to advance and achieve its sustainability objective of reducing its ecological impact where possible while ensuring the sport thrives for future generations.

The NHL determined that its Clubs鈥� venue operations comprise approximately 70% of the League鈥檚 overall carbon footprint. The League tasked 麻豆原创 to help find a technology solution that seeks to reduce its impact and protect the sport’s roots. The result was a data-driven platform that is available to all Clubs and their arena partners to transform and ultimately help to advance the League鈥檚 environmental sustainability objectives.

鈥淔or years the NHL has been on a journey to embed sustainable business practices across the League and its member Clubs,鈥� said Omar Mitchell, NHL Vice President of Sustainable Infrastructure and Growth Initiatives. 鈥淭he NHL Venue Metrics tool is a true game-changing innovation to help us understand our environmental impacts and create viable insights to improve our ecological impact.鈥�

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NHL Venue Metrics consists of three main components:

• Data Collection: An interface platform between the Clubs and their venue partners enables them to share relevant resource consumption and environmental data with the League.
• Data Calculation and Validation: The processing and verification engine allows the League to track data consistency and identify reporting errors and calculation formulas to create the League鈥檚 carbon inventory.
• Data Reporting and Insights: A visualization dashboard showcases relevant environmental, consumption, and financial insights at both the enterprise level and Club level of the various metrics that would inform the known carbon impacts of the NHL.

The technology behind NHL Venue Metrics, powered by 麻豆原创, derives powerful analytics from one of the most advanced databases, marking the League鈥檚 latest and extended use of 麻豆原创 Business Technology Platform (麻豆原创 BTP). Throughout the 麻豆原创/NHL partnership, 麻豆原创 BTP has been at the forefront of the League鈥檚 co-innovation efforts across multiple areas of their business. The operational data collected from Clubs will be processed using 麻豆原创 HANA Cloud and visualized with 麻豆原创 Analytics Cloud. Insights from the platform will support the NHL in identifying environmentally focused trends, sharing critical learnings shaped by those trends, and ultimately implementing best practices across Clubs to reduce the League鈥檚 collective ecological impact.

鈥淎t 麻豆原创, one of our priorities is providing partners with sustainable technology solutions so they can track and incorporate feasible goals for their business,鈥� said Amy Schulz, senior director of Global Sponsorships at 麻豆原创. 鈥淭he NHL is a longstanding co-innovation partner of ours. With its cloud software foundation built on 麻豆原创 BTP, we could not only develop a custom solution to meet its business objectives, but the solution will come at no cost to the Clubs. It鈥檚 a huge step forward as the NHL looks to decrease its carbon footprint and improve sustainable efficiencies.鈥�

In September 2022, the NHL invited all Clubs and arena operators to use the platform and input historical data from 2018 through mid-2022 to analyze and identify an appropriate baseline. With the inputs from Clubs, the implementation of NHL Venue Metrics powered by 麻豆原创 is already underway this current season, helping the League get one step closer to a more sustainable operation.

Given the popularity of esports and the rise of tournament broadcasts, the need for pre- and post-match analytics also applies to how fans view and consume these fast-paced games. 麻豆原创 has been working with esports teams, tournament organizers, and broadcasters over recent years to enable real-time analytics in esports.

麻豆原创 and well-known game developer and digital media company Valve have joined forces to build on the real-time insights to elevate the fan experience.

As the Official Cloud Analytics Partner of The International 11 (TI 11) tournament, 麻豆原创 is collaborating with Valve to automate and enhance the integration of advanced analytics into the broadcast in milliseconds before and after each match.

麻豆原创 Elevates the Fan Experience at The International

鈥淲hen discussing the need and desire to enhance The International鈥檚 broadcast statistics features, there was only one partner we believed could deliver on the objective, and that was 麻豆原创,鈥� said Sarah Kneller, executive producer at Valve. “With more than 2.7 million peak concurrent viewers for The International 10, our partnership with 麻豆原创 will allow us to bring the broadcast for TI 11 to the next level for our fans watching around the world.”

鈥淭hriving for constant innovation is the core of our business at 麻豆原创 and the reason why we are active in esports. The partnership with Valve was a logical next step and we鈥檙e eager to employ 麻豆原创 technologies that will enhance and elevate the fan experience during The International 11,鈥� said Lars Lamad茅, head of Global Sponsorships, 麻豆原创. “With all the knowledge we have gathered in the last years in esports broadcasts, we will add great features to make TI 11 broadcast as innovative, immersive, and compelling as possible.”

Real-Time Data and Analytics for Tournament Broadcast

Examples of the pre- and post-match insights available to the broadcast team include the identification of the most successful hero for a single player within the tournament, capturing and comparing win/loss data for different players, and calculating the averages of various tournament metrics, including average match duration, unique heroes played, etc.

Capturing and sharing these insights is possible thanks to 麻豆原创 HANA Cloud, which stores game data and provides instant access to historical data of all official matches in which TI players compete. 麻豆原创 Business Technology Platform (麻豆原创 BTP) hosts the data management, analytics, application development, and data integration, processing and analyzing the data for the broadcast in milliseconds. Thanks to the flexible data modeling capabilities of 麻豆原创 HANA Cloud, the requirements of the tournament can be realized quickly.

鈥淰alve is partnering with 麻豆原创 to enhance the fan experience for the Dota 2 Championship, The International 11,鈥� said JG Chirapurath, chief marketing and solutions officer for 麻豆原创 BTP at 麻豆原创. 鈥淪olutions powering 麻豆原创 Business Technology Platform, like 麻豆原创 HANA Cloud and 麻豆原创 Analytics Cloud, enable them to gain valuable insights on matches, teams, and players based on real-time data and analytics. Those insights bring the game to life and deliver a compelling experience to the fans watching across the globe.”

Setting the Stage

Starting with the release of Dota 2 in 2013, Valve created and organized an annual tournament known as The International. Now in its 11th edition, The International 11 has brought the world鈥檚 best Dota 2 players together in Singapore throughout October for one of the most prestigious esports events of the year. This is also reflected in the price pool, reaching $40 million in the last year.

The popularity of The International cannot be understated — the finals at last year鈥檚 event reached at more than 2.7 million viewers, setting a new tournament viewership record.

Who will win The International 11? Tune in to the tournament鈥檚
broadcast and see for yourself:

As a leading independent research and review platform, TrustRadius recognizes top software solutions based on user feedback. Decision makers across industries turn to TrustRadius鈥� 415,000 reviews to find unbiased perspectives from real customers when searching for the right software for their needs.

鈥淚n the age of the self-serve buyer, software buyers rely heavily on third-party sources,鈥� said TrustRadius CEO Vinay Bhagat. 鈥淭hat鈥檚 why third-party reviews and awards from a trusted source like TrustRadius are so important.鈥�

Our data and analytics solutions maximize the value of 麻豆原创 data by uniquely utilizing its complete business context and meaning for the most impactful decisions. We view these awards as a testament to our mission to help organizations transform their data strategy and give data purpose. We’re honored to be recognized by TrustRadius, and by our customers.

麻豆原创 data and analytics solutions include 麻豆原创 HANA Cloud, a single database foundation for modern applications and analytics, 麻豆原创 Data Warehouse Cloud, a semantic service for unifying all data, and 麻豆原创 Analytics Cloud, which brings planning and analytics together to make decisions without doubt.

Top Rated Award Wins

Within the TrustRadius platform, reviewers rate products based on usability, support, return on investment, and likelihood of recommendation. The Top Rated Awards recognize solutions with the highest customer satisfaction scores. TrustRadius evaluates candidates for these awards based on recency, ratings, and relevancy. To win, products must have earned recent reviews, a high percentage of positive ratings, and considerable site traffic.

We鈥檙e thrilled to have earned multiple 2022 Top Rated Awards:

• won in the following categories: Business Intelligence, Corporate Performance Management, and Predictive Analytics
• won in the following categories: Data Catalog, Data Fabric, and Data Integration
• won in the category Cloud Data Warehouse
• won in the following categories: Database-as-a-Service, Data Virtualization, Embedded Database, In-Memory Databases, and Relational Databases
• won in the following categories: Data Governance and Master Data Management

Best of Award Wins

The TrustRadius Best of Awards recognize software with the Best Feature Set, Best Relationship, and Best Value, according to reviewer insights. These awards highlight the features that buyers care about most and the products that excel in these areas. In order to win, products must have at least 10 recent ratings and be ranked in the top three positions of their category in terms of the percentage of positive reviews.

鈥淏2B relationships built on trust lead to better outcomes for both tech buyers and vendors,鈥� said Megan Headley, vice president of Research at TrustRadius. 鈥淪o we鈥檙e highlighting software vendors who do the best job of delivering on promises and expectations set during the sales cycle. The Best of Awards help buyers identify products with stand-out features, transparent pricing, and the best implementation and support experience.鈥�

麻豆原创 data and analytics solutions were recognized with multiple 2022 Summer Best of Awards:

• won Best Value in the Corporate Performance Management category
• won Best Feature Set, Best Relationship, and Best Value in the Cloud Data Warehouse category
• won Best Feature Set, Best Relationship, and Best Value in the Relational Databases category

For more information about recent reviews, product details, and comparisons, visit the TrustRadius product pages for , , , and .

Transform Your Data Strategy with 麻豆原创 Data and Analytics Solutions

麻豆原创 data and analytics solutions retain the full perspective of 麻豆原创 data, up-to-date and authoritative while bringing other data into the context-rich environment of your existing business systems. Using 麻豆原创鈥檚 modern data stack, you can create intelligent data apps and collaborative plans seamlessly integrated with 麻豆原创 business processes.

At 麻豆原创, we鈥檙e proud and humbled that our solutions have inspired such positive reviews in the user community. Thank you for supporting our work, and for sharing your feedback on the TrustRadius platform.

To learn more information and experience the software,
visit the page on sap.com.

Daniel Yu is senior vice president of Solution Management and Product Marketing for 麻豆原创 Data and Analytics.

Gartner evaluated 20 vendors and named 麻豆原创 a Leader based on 鈥渃ompleteness of vision and ability to execute.鈥�

鈥溌槎乖粹�檚 cloud-first mind-set paves a critical, future-proof path forward for our customers. 麻豆原创 Business Technology Platform serves as the unified, business-centric, and open platform for our customers to become an intelligent enterprise 鈥� helping to integrate and extend applications, streamline workflows and processes, and unlock powerful insights across all data,鈥� said JG Chirapurath, Chief Marketing and Solutions Officer, 麻豆原创 BTP, 麻豆原创. 鈥淲e believe this latest Gartner report demonstrates how we鈥檝e successfully transitioned our leadership in the data management space to the cloud.鈥�

Gartner reviewed several 麻豆原创 products for this Magic Quadrant. The products, which address both operational and analytical DBMS use cases, include the database, the solution, , software and the suite.

麻豆原创 HANA is the database management foundation of 麻豆原创 Business Technology Platform (麻豆原创 BTP) and is trusted by over 58,000 麻豆原创 customers to manage their most business-critical data. With the ability to process transactional and analytical workloads in real time 鈥� no matter where the data resides 鈥� 麻豆原创 HANA is uniquely suited to support our customers鈥� intelligent enterprise journey.

Access a of the 2021 Gartner庐 Magic Quadrant™ for Cloud Database Management Systems report.

For more information, visit the executive .

Visit the . Follow 麻豆原创 on Twitter at .

Media Contact:
Scott Malinowski, +1 (617) 538-6297, scott.malinowski@sap.com, ET
麻豆原创 麻豆原创 Room; press@sap.com

*Gartner, Magic Quadrant for Cloud Database Management Systems, ,听,听,听,听, 14 December 2021.
Gartner and Magic Quadrant are registered trademarks of Gartner, Inc. and/or its affiliates in the United States and internationally and are used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner鈥檚 research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

Any statements contained in this document that are not historical facts are forward-looking statements as defined in the U.S. Private Securities Litigation Reform Act of 1995. Words such as 鈥渁nticipate,鈥� 鈥渂elieve,鈥� 鈥渆stimate,鈥� 鈥渆xpect,鈥� 鈥渇orecast,鈥� 鈥渋ntend,鈥� 鈥渕ay,鈥� 鈥減lan,鈥� 鈥減roject,鈥� 鈥減redict,鈥� 鈥渟hould鈥� and 鈥渨ill鈥� and similar expressions as they relate to 麻豆原创 are intended to identify such forward-looking statements. 麻豆原创 undertakes no obligation to publicly update or revise any forward-looking statements. All forward-looking statements are subject to various risks and uncertainties that could cause actual results to differ materially from expectations. The factors that could affect 麻豆原创’s future financial results are discussed more fully in 麻豆原创’s filings with the U.S. Securities and Exchange Commission (“SEC”), including 麻豆原创’s most recent Annual Report on Form 20-F filed with the SEC. Readers are cautioned not to place undue reliance on these forward-looking statements, which speak only as of their dates.
漏 2021 麻豆原创 SE. All rights reserved.
麻豆原创 and other 麻豆原创 products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of 麻豆原创 SE in Germany and other countries. Please see for additional trademark information and notices.

The pandemic spotlighted talent as a key challenge for organizations around the world. 鈥淭he worldwide shortage of full-time developers will increase from 1.4 million in 2021 to 4.0 million in 2025,鈥� according to IDC.* 麻豆原创鈥檚 announcements tackle the talent gap with new tools, integrations, embedded AI and learning programs to help both employees and applicants build new skills for the cloud-first era. The announcements were made at , 麻豆原创鈥檚 global developer conference, taking place online Nov. 16鈥�18, 2021.

鈥淔or our customers and partners all over the world, the future is in the cloud,鈥� said Juergen Mueller, CTO and Member of the Executive Board at 麻豆原创 SE. 鈥淎ccessing the right talent, skills and capabilities for this journey can be a challenge. 麻豆原创鈥檚 announcements not only empower citizen developers but also support professional developers in their continuous learning efforts so customers can innovate today and continue building the foundation for success tomorrow.鈥�

Everyone Can Be a Developer

麻豆原创 announced a on (麻豆原创 BTP) that lets both professional and citizen developers create new applications, enhance existing ones and automate complex tasks. By adding no-code development and automation with the 麻豆原创 AppGyver development environment, enhancing low-code development with 麻豆原创 Business Application Studio, and offering a , 麻豆原创 provides new ways for customers to do more by drawing on technology talent throughout their organizations, whether in or out of traditional IT departments.

, a global leader in the logistics industry, uses 麻豆原创 AppGyver to digitalize processes and streamline employee operations for fleet management. 鈥淲ith 麻豆原创鈥疉ppGyver,鈥痺e created a mobile app on iOS and Android to better manage鈥痙amage reports for our trailer fleet鈥痑cross Europe,鈥� said Ilari Aarikka, Director, Trailer Pool & Fleet, DHL. 鈥淭he app helped us to increase the鈥痳eliability of reporting while making鈥痠nspections more convenient for鈥痚mployees in the field.鈥�

For professional developers, now includes 麻豆原创 HANA Cloud and 麻豆原创 Integration Suite. 麻豆原创 also offers a for its 麻豆原创 Fiori design system.

Toward Composable Enterprise Solutions

麻豆原创 announced their business with modular, agile solutions that address individual challenges. The to , the integration layer of 麻豆原创 BTP, provides additional prepacked integration content and adapters 鈥攁vailable on 鈥� to integrate 麻豆原创 and non-麻豆原创 applications. By the end of 2021, 麻豆原创 Integration Suite is expected to be available on Google Cloud Platform. 麻豆原创 is expected to release to help customers move workloads to the cloud from their on-premise systems in near-real time. 麻豆原创 also introduces new ways to facilitate migrations solution and .

Embedded AI Offerings Across the Portfolio

麻豆原创 expanded embedded artificial intelligence (AI) capabilities that make it easier for developers and customers to harness AI and boost productivity. service simplify building and monitoring chatbots to automate tasks and workflows. 麻豆原创 is expected to service, a novel neural network-based recommendation engine that delivers highly personalized recommendations across a wide range of business scenarios. And many to, for example, automate intercompany document matching, recommend actions in workflows, extract and process data from business documents, or provide learning recommendations.

Learning From Classroom to Boardroom

麻豆原创 launched an . It addresses at all levels with a simple, intuitive design that makes it easier to upskill or reskill in key innovation areas 鈥� for free. The includes a available in various formats, from expert-led sessions and hands-on training to microlearning videos. 麻豆原创 also introduced an and a program to provide and professors.

48 Hours of Live Content at 麻豆原创 TechEd in 2021

to follow the event with its 100+ skill-building sessions, 25+ workshops, 8 tech tracks and 48 hours of continuous tech talk on Channel 1, accessible with your registration to the 麻豆原创 TechEd conference.

麻豆原创 TechEd News Guide 2021

More details on all news, launches and updates on .

Visit the 麻豆原创 News Center. Follow 麻豆原创 on Twitter at .

About 麻豆原创

麻豆原创鈥檚 strategy is to help every business run as an intelligent enterprise. As a market leader in enterprise application software, we help companies of all sizes and in all industries run at their best: 麻豆原创 customers generate 87% of total global commerce. Our machine learning, Internet of Things (IoT), and advanced analytics technologies help turn customers鈥� businesses into intelligent enterprises. 麻豆原创 helps give people and organizations deep business insight and fosters collaboration that helps them stay ahead of their competition. We simplify technology for companies so they can consume our software the way they want 鈥� without disruption. Our end-to-end suite of applications and services enables business and public customers across 25 industries globally to operate profitably, adapt continuously, and make a difference. With a global network of customers, partners, employees, and thought leaders, 麻豆原创 helps the world run better and improve people鈥檚 lives. For more information, visit .

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*Source: 鈥淨uantifying the Worldwide Shortage of Full-Time Developers,鈥� Doc # US48223621, IDC, September 2021
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These never-before-available insights will enable broadcasters to provide in-depth analysis to enhance the fan experience.

Each live broadcast will provide innovative insights for fans and commentators, allowing them to make sense of the pros鈥� decisions throughout each phase of the match. By comparing structured historical game data stored in against live data using real-time data processing, player actions are put in context for players and fans.

“There is no doubt 麻豆原创 has carried over its vast knowledge and experience in enterprise application software into our world of e-sports,鈥� LEC Senior Manager Zeynep Gencaga said. 鈥溌槎乖�’s engineers have worked tirelessly with our team to help simplify the visualization of statistics to further nourish our LEC storylines, giving an extra edge to every little bit of data for our fans.”

Since 2018, 麻豆原创 has been innovating to bring more industry expertise to the LEC Tournament.

Broadcasters and fans alike will see three analytical visualizations, providing analysis of games as they happen. With the enriched stats, broadcasters get valuable insights for better storytelling and engagement with their audience. Fans can expect to see stats around key game elements such as the use of items, time to complete an objective, and overall player performance records.

Visit the . Follow 麻豆原创 on Twitter at .

Media Contacts:
Reid Strohmeier, +1 (646) 280-9290, reid.strohmeier@sap.com, ET
Lisa Buehn, +49 15167834297, lisa.buehn@sap.com, CET
麻豆原创 麻豆原创 Room; press@sap.com

Any statements contained in this document that are not historical facts are forward-looking statements as defined in the U.S. Private Securities Litigation Reform Act of 1995. Words such as 鈥渁nticipate,鈥� 鈥渂elieve,鈥� 鈥渆stimate,鈥� 鈥渆xpect,鈥� 鈥渇orecast,鈥� 鈥渋ntend,鈥� 鈥渕ay,鈥� 鈥減lan,鈥� 鈥減roject,鈥� 鈥減redict,鈥� 鈥渟hould鈥� and 鈥渨ill鈥� and similar expressions as they relate to 麻豆原创 are intended to identify such forward-looking statements. 麻豆原创 undertakes no obligation to publicly update or revise any forward-looking statements. All forward-looking statements are subject to various risks and uncertainties that could cause actual results to differ materially from expectations. The factors that could affect 麻豆原创’s future financial results are discussed more fully in 麻豆原创’s filings with the U.S. Securities and Exchange Commission (“SEC”), including 麻豆原创’s most recent Annual Report on Form 20-F filed with the SEC. Readers are cautioned not to place undue reliance on these forward-looking statements, which speak only as of their dates.
漏 2021 麻豆原创 SE. All rights reserved.
麻豆原创 and other 麻豆原创 products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of 麻豆原创 SE in Germany and other countries. Please see for additional trademark information and notices.