麻豆原创 Business Data Cloud (麻豆原创 BDC) is the data foundation of that platform, the business data fabric that anchors universal business context, serving as the trusted knowledge core聽for every enterprise application and agent.聽

The future of agentic organizations will be driven by AI with the deepest organizational knowledge. That future doesn’t start with AI models; it starts with whether your data foundation can give agents the business context they need to act autonomously. 

Today, we are introducing innovations that move organizations closer to becoming an autonomous enterprise.

Turn all your data into business outcomes 

A business data fabric architecture ensures every agent, application, and decision draws from the same trusted business context. And today, we are introducing new business data fabric capabilities that bring multi-model, unified master data, and embedded governance to your agentic foundation. 

• 麻豆原创 HANA Cloud natively available in 麻豆原创 Business Data Cloud:聽麻豆原创 HANA Cloud聽is聽now a聽core聽component of 麻豆原创 Business Data Cloud.聽As the AI database聽for 麻豆原创 BDC,聽麻豆原创聽HANA Cloud provides a聽unified聽in-memory engine聽for agents to reason across transactional, analytical, and multi-model workloads聽such as spatial, graph, and vector.聽In practice, this means agents can navigate relationships across customers and suppliers, analyze geographic dependencies, or perform semantic search in real time.聽And because every workload runs on a single in-memory engine with native workload management, inference time drops dramatically, lowering TCO and improving the predictability of AI聽costs.聽With 麻豆原创 HANA Cloud, 麻豆原创 Databricks, and 麻豆原创 Snowflake, 麻豆原创 Business Data Cloud delivers聽intelligent compute for聽every data and AI workload.
• Reltio in 麻豆原创 Business Data Cloud: With the completed acquisition of Reltio, 麻豆原创 is bringing multi-domain master data management capabilities directly into 麻豆原创 Business Data Cloud, helping customers unify, cleanse, and harmonize data across 麻豆原创 and third-party聽sources. Reltio鈥檚 AI-based entity resolution identifies and merges related records聽into a single, consistent view of business entities.聽Low-latency delivery and Model Context Protocol support enable real-time, multi-agent workflows across聽your data landscape: a procurement agent, for example, can assess supplier risk and trigger action almost instantly using trusted, real-time data. Together, this becomes a golden record system of context that Joule Agents use to deliver faster time-to-value for business AI.
• 麻豆原创 Master Data Governance natively available聽in聽麻豆原创 Business Data Cloud:聽Unified master data is only as valuable as the governance applied to it. To ensure data is AI-ready, governance must聽shift聽from regulator to value accelerator. 麻豆原创 Master Data Governance is now a core component of 麻豆原创 Business Data Cloud, governing master data and policies across聽your聽business data fabric.聽This results in聽embedded聽AI governance that accelerates agent deployment, ensuring every agent operates on data聽products聽that聽are聽verified聽and aligned to your business policies.聽
• 麻豆原创 AI Core integration with 麻豆原创 Business Data Cloud: 麻豆原创 is introducing deeper integration between 麻豆原创 Business Data Cloud and 麻豆原创 AI Core, enabling AI models to be grounded directly in trusted business data, semantics, and governance. Batch inference can now be embedded into business-ready data products, continuously enriching the data that powers Joule with predictions, classification, and聽AI聽outputs.聽聽

“This is where 麻豆原创 Business Data Cloud fits into the vision: not as a centralized system, but as an enabler of cultural change through its unique capabilities. These capabilities allow teams to preserve mission-critical business context across financial and non-financial data.”

Jannie Affeld, VP Finance Systems and ERP, Google 

Transform outcomes with Joule Agents 

麻豆原创 is bringing agentic AI directly into the business data fabric through Joule Agents, introducing new capabilities that streamline data management, analytics, and planning through a conversational experience: 

• Data product search and creation: Joule Agents simplify how users discover and create data products. With natural language prompts, users can identify relevant 麻豆原创 and third-party data sources, perform joins and transformations automatically, and apply business context and governance policies.  
• Automated planning and analytical modeling: Joule Agents enable data modelers and planning teams to generate analytical and planning models using AI. By defining dimensions, granularity, and data sources, users can automatically create models aligned with best practices. Teams can also initiate planning cycles, manage versions, and apply calculations without deep technical expertise. 
• Easily聽surface business聽insights:聽Business users聽can聽ask complex analytical questions in natural language and receive context-aware insights across lines of business. Powered by governed data products聽in 麻豆原创 Business Data Cloud and 麻豆原创 Knowledge Graph,聽Joule聽understands relationships, processes, and business logic聽to deliver聽more accurate and complete answers without requiring manual exploration.
• 麻豆原创 Analytics Cloud story generation: Joule accelerates 麻豆原创 Analytics Cloud story creation by transforming data models, queries, and business context into dashboards and visualizations automatically. Users can continue the conversation, drilling into KPIs, identifying drivers, and exploring trends in a single workflow. 

Extend context across your open data ecosystem

Last year, we introduced 麻豆原创 BDC Connect, a capability to share data and metadata with zero copies, preserving meaning across every cloud and platform. We are excited to announce 麻豆原创 BDC Connect for Amazon Athena, continuing our promise of openness and choice.

This enables 麻豆原创 data products to be discovered and consumed directly within AWS without replication or loss of context. As a result, teams can build analytics, applications, and AI agents faster while ensuring they operate on trusted, governed business data.

Together with existing partners across Snowflake, Databricks, Google BigQuery, and Microsoft Fabric, 麻豆原创 Business Data Cloud delivers a connected, open data ecosystem so organizations can extend business context across their entire landscape with zero copies. 

General availability is planned for H2 2026.

“Compute can happen anywhere, data can stay at the source when needed, but business context is managed once, centrally, in 麻豆原创 Business Data Cloud.”

Malin Persson, CIO at Ericsson

Get started today 

Build your trusted foundation for agentic AI with 麻豆原创 Business Data Cloud.  

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

Building on their long-standing partnership, AWS and 麻豆原创 are making it easier for customers to access mission-critical 麻豆原创 data products across AWS services, including Amazon Bedrock, Amazon Quick, and Amazon SageMaker. This will allow teams to deliver self-service analytics and build AI agents across all lines of business鈥攚ithout waiting for IT teams to replicate, prepare, and provision 麻豆原创 data. 

鈥淭he next era of business will be defined by how well organizations turn intelligence into action at scale,鈥� said Muhammad Alam, member of the Executive Board of 麻豆原创 SE, 麻豆原创 Product & Engineering. 鈥淏y bringing together 麻豆原创 Business Data Cloud and widely adopted AWS AI and analytics capabilities, customers can unlock the true potential of data and AI.鈥� 

Enabled by 麻豆原创 BDC Connect, the integration delivers near real-time, zero-copy access to semantically rich 麻豆原创 data products directly through Amazon Athena, keeping data in place, preserving its original business context, and eliminating replication delays. Customers can query and analyze this data immediately, or choose to store and transform it for use across the broader AWS environment. This gives teams a governed, secure environment within AWS to easily build reports, dashboards, and AI agents.

“麻豆原创 and AWS share a commitment to helping customers put their most valuable data to work,” said Ruba Borno, vice president of Global Specialists and Partners at AWS. “By combining 麻豆原创 Business Data Cloud with the AWSsecure, global infrastructure and advanced AI services, organizations can unlock mission-critical 麻豆原创 data and act on it at the speed and scale their business demands.” 

With 麻豆原创 BDC Connect for Amazon Athena customers can: 

• Create a single, trusted foundation for all their business data, 麻豆原创 and beyond 
• Get AI up and running faster with business data that is ready to use 
• Build intelligent applications and agents powered by the business data that matters most 
• Fast-track insights and innovation with self-service analytics that reduce time-to-insight from weeks to hours 

General availability

麻豆原创 Business Data Cloud is already available on AWS in the U.S. East (N. Virginia), Europe (Frankfurt), Asia Pacific (Tokyo), Canada (Central), Asia Pacific (Sydney), South America (S茫o Paulo), Asia Pacific (Seoul), Asia Pacific (Singapore) Regions, and the AWS European Sovereign Cloud. 

The new capability simplifies access to semantically rich 麻豆原创 data products through bi-directional, zero-copy sharing with Microsoft Fabric, enabling enterprises to gain instant access to trusted, business-ready insights for advanced analytics and AI.

鈥淲e are excited about continuing to strengthen our partnership with Microsoft to create more value for our customers,鈥� said Muhammad Alam, member of the Executive Board of 麻豆原创 SE, 麻豆原创 Product & Engineering. 鈥淏y bringing 麻豆原创 Business Data Cloud and Microsoft Fabric closer together, our customers can seamlessly leverage the power of data to generate real business value through AI and analytics.鈥�

鈥淥rganizations across every industry are accelerating their AI transformation by bringing together data from operations, analytics, and applications,鈥� said Scott Guthrie, executive vice president, Microsoft Cloud and AI. 鈥淲ith 麻豆原创 Business Data Cloud and Microsoft Fabric, we鈥檙e delivering a trusted foundation for analytics and AI, and helping our customers move faster, make smarter decisions, and turn insight into real business outcomes.鈥�

Unlocking the true potential of your enterprise data

麻豆原创 BDC Connect for Microsoft Fabric empowers organizations to fully harness their data and applications by delivering secure, rapid access to 麻豆原创 data products at scale鈥攚ithout the delays of data replication.

Through bi-directional, zero-copy sharing between 麻豆原创 Business Data Cloud and Microsoft Fabric, customers can realize use cases that previously required moving and managing copies of data.聽麻豆原创 data products will be seamlessly integrated into Microsoft OneLake, Microsoft Fabric鈥檚 AI ready data lake, and data sets shared from Microsoft OneLake will also be available in 麻豆原创 BDC to supplement intelligent applications.

By utilizing Fabric鈥檚 data engineering, data warehousing, and Power BI capabilities, organizations can effectively integrate 麻豆原创 data with their broader ecosystem, establishing a unified foundation for their enterprise data. OneLake integration into Microsoft AI Foundry can also help customers leverage their 麻豆原创 data in building AI applications, and as OneLake is built into Microsoft 365, hundreds of millions of users can get secure access to their 麻豆原创 data through the products they use every day such as Excel and Teams.

Accelerating business insights and AI with 麻豆原创 and Microsoft Fabric

麻豆原创 BDC Connect for Microsoft Fabric enables a unified data foundation that helps organizations get insights faster and accelerate their AI strategy. Through this bi-directional integration, customers can:

• Build a semantically rich data foundation on harmonized 麻豆原创 and non-麻豆原创 data
• Perform advanced analytics and interact with enterprise data in natural language with Copilot in Microsoft Power BI.
• Develop intelligent AI applications and agents grounded in mission-critical business data using Fabric data agents, Copilot studio, and AI Foundry
• Enable multi-agent collaboration between M365 Copilot and Joule, leveraging a unified enterprise data and productivity platform to provide a seamless experience for business users

Availability

麻豆原创 Business Data Cloud Connect for Microsoft Fabric is planned to be generally available in Q3 2026.

Irfan Khan is president and chief product officer for 麻豆原创 Data and Analytics.
Arun Ulag is president of Azure Data at Microsoft.

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.

New intelligent applications and open ecosystem
partnerships turn insights into action across the enterprise

As enterprises move toward an AI-driven future, the role of data has never been more critical. Yet much of that data remains locked in silos 鈥� spread across teams, clouds, and legacy systems.

This fragmentation creates a 鈥渃ontext gap,鈥� where information is technically available but disconnected from the business meaning that makes it actionable. For example, sales and marketing teams may share a common view of pipeline, but without linking it to product feedback or process bottlenecks, AI models trained on that data miss the full business context. The result is inconsistent insights, slower decision-making, and a stalled cycle of AI, data, and applications. 

closes this gap. By harmonizing enterprise data wherever it resides and preserving its business context, it provides the foundation for intelligent applications and reliable AI.

At 麻豆原创 Connect, 麻豆原创 is bringing this vision to life with the next wave of innovations: 麻豆原创 Business Data Cloud Intelligent Applications 

Four new intelligent applications in preview

Building on the momentum for intelligent applications established at 麻豆原创 Sapphire, 麻豆原创 is now opening a restricted public preview of four intelligent applications designed to transform decision-making across finance, procurement, supply chain, and revenue operations.

Finance Intelligence gives CFOs and finance teams real-time AI-powered analysis of liquidity by harmonizing 麻豆原创 and third-party data and suggesting key actions to implement. Leaders can forecast cash flow instantly as well as detect liquidity risks using AI trained on live receivables and payables with external credit data such as 惭辞辞诲测鈥檚 for richer customer risk assessment. With Joule and generative AI agents automating routine finance tasks, finance teams can shift their focus from reporting on the past to actively steering the future. 

Spend Intelligence provides organizations with a single, comprehensive view of enriched and classified spend data. Built-in AI and advanced analytics uncover patterns, anomalies, and opportunities for cost savings, while collaborative features connect finance, procurement, HR, and supply chain teams for better alignment. Through native integration with 麻豆原创 source-to-pay solutions, spend data continuously informs operational workflows, improving decision-making, enhancing control, and strengthening enterprise resilience. 

Supply Chain Intelligence equips operations leaders with the context to make faster, more impactful decisions. By combining 麻豆原创 data with external signals such as weather, regulatory updates, and market shifts 鈥� along with insights from millions of partners in 麻豆原创 Business Network 鈥� businesses can leverage the power of AI to understand and take action on key supply chain issues and drive optimization. This comprehensive intelligence helps anticipate disruptions, evaluate supplier risks, and orchestrate decisions seamlessly from prediction to execution, ensuring more resilient and agile operations. 

Revenue Intelligence transforms fragmented customer touchpoints into unified, actionable insights. By linking individual customer behaviors with enterprise-wide operations, it helps revenue leaders see which accounts to prioritize, when to intervene, and how to optimize customer investments. Unlike CRM-only tools, Revenue Intelligence connects front-office engagement to back-office execution, empowering organizations to maximize growth opportunities and strengthen customer relationships with a complete view of the business context.

麻豆原创 Business Data Cloud Connect

Beyond intelligent applications, 麻豆原创 is strengthening its open data ecosystem with 麻豆原创 Business Data Cloud Connect, giving customers unprecedented flexibility to work with trusted data wherever it resides. With secure, zero-copy sharing, customers can bring 麻豆原创 data products directly into their existing data platforms, eliminating duplication, reducing transformation efforts, and extending the reach of 麻豆原创鈥檚 business data fabric.

The first partners adopting this capability include Databricks (generally available) and Google (now in public preview), enabling real-time, bi-directional access to semantically rich 麻豆原创 data products in environments customers already use.

With 麻豆原创 Business Data Cloud Connect for Databricks now generally available, organizations can accelerate analytics and AI initiatives with greater speed, less friction, and full confidence in the integrity of their data.

麻豆原创 is committed to rapidly expanding this partner ecosystem so that, no matter where enterprise data resides, customers can connect it with trust, governance, and business context. 

Why it matters

Together, these announcements reflect 麻豆原创鈥檚 vision for the intelligent enterprise 鈥� where applications don鈥檛 just analyze, but act. By combining trusted data, open connectivity, and embedded AI, enterprises can shorten decision cycles, reduce integration complexity, and align intelligence directly with business outcomes.

For organizations operating across hybrid environments and complex data landscapes, these innovations make it easier than ever to turn insights into action and deliver measurable impact.

This week at , customers can experience this vision firsthand through live demos, real-world case studies, and discussions with 麻豆原创 leaders, partners, and peers. It鈥檚 an opportunity to see how 麻豆原创 Business Data Cloud is redefining decision-making today and shaping the future of the intelligent enterprise.

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

By connecting Google BigQuery, the autonomous data to AI platform with agentic capabilities, and 麻豆原创 and Google aim to help enterprises of all sizes gain more immediate access to trusted, business-ready data for enterprise analytics and AI across their platforms.

For decades, enterprise data and analytics have existed in separate worlds. Mission-critical business data, rich with semantic context, has been locked within transactional systems. Traditional extract, transform, load (ETL) processes create data replicas that are difficult to govern, quickly become stale, and prevent businesses from acting on real-time insights, ultimately hindering digital transformation.

Our 麻豆原创 and Google partnership ends this compromise. By eliminating data replication and unifying the data landscape, 麻豆原创 and Google Cloud are empowering businesses to build intelligent agents, automated workflows, and predictive insights that are directly grounded in live, trusted business information.

As the first hyperscaler to adopt 麻豆原创 BDC Connect, 麻豆原创 BDC Connect for Google BigQuery enables organizations to unlock the true potential of their data and applications with secure and rapid access to 麻豆原创鈥檚 semantically rich and governed data products at scale, without the delays and complexities of data replication and need for ETL pipelines. Customers can flexibly combine 麻豆原创 data with their other enterprise data in BigQuery and vice-versa to innovate with leading analytics and agentic AI capabilities.

鈥溌槎乖� and Google Cloud have a long history of empowering global enterprises to harness the power of data and AI,鈥� said Christian Klein, CEO of 麻豆原创 SE. 鈥淏ringing together Google BigQuery and 麻豆原创 Business Data Cloud gives our customers choice without compromise, enabling them to fast-track their analytics and AI initiatives.鈥�

鈥淏usinesses are combining intelligence and automation into every aspect of their operations,” said Thomas Kurian, CEO of Google Cloud. 鈥淏y uniting 麻豆原创 Business Data Cloud with BigQuery and Gemini models, we鈥檙e making it easy for enterprises to build a unified data foundation that breaks down silos and unlocks a new class of AI agents and applications.鈥�

Innovation with 麻豆原创 data products and Google BigQuery

The centerpiece of this partnership is the new 麻豆原创 Business Data Cloud Connect for Google BigQuery. This is a zero-copy data fabric that enables seamless access to 麻豆原创 BDC鈥檚 semantically rich business data with Google鈥檚 powerful data and AI ecosystem, including Gemini models and the Vertex AI platform. The result is a modern platform for data, analytics, and AI that enables automated, cross-functional business processes.

This bi-directional integration helps to deliver an enterprise-grade offering for building and scaling AI. With 麻豆原创 Business Data Cloud Connect for Google BigQuery, customers can:

• Build grounded, trustworthy AI: Ensure the Google BigQuery AI models and agents operate on the most current and complete view of the business by accessing trusted semantically rich 麻豆原创 data in real-time without copies.
• Deploy autonomous agents: Build and deploy intelligent agents using Google Cloud鈥檚 Vertex AI and Gemini that can automate complex cross-functional processes鈥攆rom supply chain optimization to financial forecasting.
• Unleash deeper insights: Fuse 麻豆原创 data through 麻豆原创 BDC with unique, world-scale datasets only available on Google Cloud, like Google Maps geospatial data, Google Trends, and public datasets, to create unparalleled business context.
• Reinvent analytics: Move beyond dashboards and reports. Enable anyone in the organization to ask complex questions on Google Cloud of their business data in natural language and get immediate, intelligent answers.

Availability

Google Cloud will offer customer and partner incentives that fast-track the adoption of these joint solutions, enabling an accelerated journey to AI-infused data transformations.

麻豆原创 Business Data Cloud is available today in Google Cloud regions across Asia Pacific, Europe, and the U.S., with more regions planned. 麻豆原创 Business Data Cloud Connect for Google BigQuery is planned to be generally available in H1 2026.

In addition, 麻豆原创 BW, private cloud edition, which is offered through 麻豆原创 BDC, is supported in more than 40 Google Cloud regions, helping our customers meet critical data residency and compliance requirements.

We’re witnessing the rise of a new wave of intelligent applications reshaping how organizations operate, embedding real-time data and critical operational context with AI models to enable swift and thoughtful decisions. Unlike traditional software that is governed by rigid business rules, these modern applications can learn and adapt to rapidly evolving customer and market demands 鈥� detecting changes to optimize processes, anticipate needs, and collaborate with both human and artificial “thinkers” to create competitive advantage for an organization. 

Yet, we stand at the cusp of a bolder wave of innovation, one that unfortunately only the discerning few organizations may fully harness. Despite the vast potential of AI and cloud technologies, their true impact hinges on using these innovations with the secure and semantically rich data that is vastly available within an organization. 

Transform outcomes with intelligent applications

This year at 麻豆原创 Sapphire, we unveiled a significant expansion of 麻豆原创 Business Data Cloud to deliver on the promise of intelligent applications: prebuilt, composable applications that seamlessly integrate trusted data products, AI capabilities, and business simulations to serve the needs of every business leader.

These intelligent applications are not just analytics tools; they transcend traditional analytics by automating and orchestrating work across both analytical and transactional workflows, enabling customers to make decisions and execute actions within 麻豆原创 Business Data Cloud.

Today, we are introducing new intelligent application capabilities in 麻豆原创 Business Data Cloud, starting with People Intelligence, an offering grounded in workforce composition, skills, and compensation data products. Built on data from 麻豆原创 SuccessFactors software, People Intelligence provides HR and business leaders with AI-driven recommendations to optimize talent decisions, drive engagement, and ensure compliance. It features capabilities such as workforce composition insights, compensation insights, and skill insights, all available in the second half of 2025.

Additional intelligent application capabilities in 麻豆原创 Business Data Cloud that are entering technology preview include: 

• Cloud ERP Intelligence: Empowers leaders with transformative insights, business simulations, and AI capabilities to manage uncertainty, drive profitability, and meet sustainability goals. These capabilities include new data products from key business processes such as manufacturing (production execution, resource optimization, etc.), supply chain (inventory, deliveries. etc.), and contract accounting (payments, billing, etc.). 
• Customer Intelligence: Guide sales, service, marketing, and commerce teams with a 360-degree customer view to anticipate needs, improve targeting, and build a comprehensive customer profile.  
• Finance Intelligence: Provides CFOs and finance teams with real-time forecasting and planning, connected data across systems, and AI-powered anomaly detection. 
• Spend Intelligence: Delivers procurement and operations leaders real-time spend visibility to minimize supplier risk, flag spend outliers, and reduce costs.

Each intelligent application in 麻豆原创 Business Data Cloud is underpinned by curated, governed data products, sets of structured business data and metadata designed to accelerate use cases and reduce data integration overhead. And with 麻豆原创 Databricks natively available in 麻豆原创 Business Data Cloud, users can leverage 麻豆原创 data products with existing lakehouses with a zero-copy approach.

As part of these technology previews, we are also announcing the delivery of hundreds of new data products throughout 2025 across all 麻豆原创 Business Suite domains 鈥� from inventory optimization and delivery analysis to sustainability and compliance data products. The first wave includes new environmental, health, and safety (EHS) and product compliance datasets, with sustainability footprint data to follow later in the year. 

Amplify the value of AI with your most powerful data

In addition, 麻豆原创 Business Data Cloud is expanding its knowledge graph capabilities. Originally launched within 麻豆原创 Datasphere, the knowledge graph can now ingest and map metadata across 麻豆原创 and external sources, and seamlessly consume models published in 麻豆原创 Knowledge Graph on 麻豆原创 BTP. This creates a living model of how business data is structured and connected, providing a semantic backbone for AI to operate with higher precision.

Paired with Joule in 麻豆原创 Business Data Cloud, now generally available, users can engage with complex business data as naturally as they think, without the constraints of traditional technology. Joule unlocks the full richness of enterprise information, empowering people across the organization to navigate, reason, and act with intelligence grounded in real business context.

Open data ecosystem: Expanding intelligence beyond 麻豆原创

We are also making 麻豆原创 Business Data Cloud more accessible to power the next generation of intelligent, multi-cloud applications.

Starting in the second quarter, 麻豆原创 Business Data Cloud is available on AWS, with Google Cloud and Microsoft Azure expected to follow in the second half of 2025. This makes 麻豆原创鈥檚 data foundation more accessible and deployable within multi-cloud strategies, giving customers the flexibility to run intelligent workloads wherever they operate. 

At the same time, 麻豆原创 is actively collaborating with leading partners to build the next wave of intelligent applications.

• Accenture will release six intelligent applications addressing key challenges in supply chain, talent, finance, and procurement (GA timeline pending). 
• Adobe and 麻豆原创 are co-developing an application that fuses Adobe鈥檚 marketing data with 麻豆原创鈥檚 financial and supply chain data, enabling real-time alignment between demand signals and operational planning, expected in late 2025. 
• Palantir and 麻豆原创 are partnering to facilitate joint customers鈥� cloud migration journey and modernization programs. Seamless connectivity between Palantir and 麻豆原创 Business Data Cloud will enable customers to build a harmonized data foundation across their enterprise landscape. 麻豆原创 Business Data Cloud and Palantir Foundry and AIP will transform data silos into a trusted data foundation that enables human + AI teaming in the real world. Together the companies will responsibly deliver essential outcomes and support customers, including the U.S. government, to quickly adapt to changes and disruptions.
• Thomson Reuters will develop an intelligent application to help customers navigate the fast-moving challenges in the current global trade and tariffs environment, planned for end of 2025.
• Joint Collibra and 麻豆原创 Business Data Cloud customers can now run up to 10x more active data quality jobs in Collibra Data Quality & Observability when run on 麻豆原创 BDC data, at no additional cost. This limited time offer helps accelerate decision-making, strengthen compliance, and improve AI readiness, and is available until May 30, 2026.

The scope of partner collaboration also extends to data enrichment use cases. A new partnership with 惭辞辞诲测鈥檚 will let our joint customers blend 麻豆原创鈥檚 accounts receivable data with 惭辞辞诲测鈥檚 risk datasets to enhance cash flow forecasting, prioritize collections, and reduce exposure to bad debt. This solution is scheduled for general availability in the fourth quarter of 2025. 

We鈥檙e excited to partner with our customers and ecosystem to unlock a new generation of intelligent applications in 麻豆原创 Business Data Cloud, where trusted data, AI, and business context come together to drive meaningful change. The future of modern business will belong to those who turn intelligence into action.

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• featuring the latest on data products and intelligent applications in 麻豆原创 Business Data Cloud

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

In 2023, Google Cloud and 麻豆原创 established a strategic partnership, which continues to deliver significant value for enterprises seeking to maximize insights from their data. Building upon that foundation, the partnership is now evolving to focus on 麻豆原创 Business Data Cloud, a fully managed SaaS solution that unifies and governs all 麻豆原创 data and seamlessly connects with third-party data.

By connecting BigQuery, Google鈥檚 autonomous data to AI platform with agentic capabilities powered by Gemini, and , Google Cloud and 麻豆原创 aim to help enterprises of all sizes gain insights across their enterprise data landscape and unlock new generative AI capabilities.   

Strong analytics partnership foundation

麻豆原创 and Google Cloud have enabled integration between 麻豆原创 Datasphere and BigQuery, which remains a cornerstone of the evolution of the partnership with 麻豆原创 Business Data Cloud. The collaboration aims to help customers access BigQuery data in 麻豆原创 Business Data Cloud and vice versa. Expanding the two-way data federation capabilities first pioneered with 麻豆原创 Datasphere will enable customers to join diverse datasets and obtain deep comprehensive insights without building and managing complex ETL pipelines.

Our objective is to enable all enterprises to streamline data integration and data science, enhance their analytical workflows, and accelerate their transformation into an AI-driven enterprise. By using the combined strengths of Google Cloud and 麻豆原创, customers can gain faster, more accurate, and actionable insights, augmented by intelligent automation and novel content generation. 

Innovating with data unified across 麻豆原创 Business Data Cloud and BigQuery

A cornerstone of this collaboration is seamless connectivity between 麻豆原创 data solutions and Google Cloud鈥檚 powerful data platform. With the existing integration of 麻豆原创 Business Data Cloud and BigQuery, customers can facilitate business analysis across their entire data estates, providing enterprises the ability to unify 麻豆原创 and non-麻豆原创 data to create powerful insights and innovate faster with generative AI.

Key features include:

• Seamless data federation: Directly integrate enterprise data warehouse data in BigQuery with 麻豆原创 data in 麻豆原创 Datasphere. Federation from 麻豆原创 Datasphere to BigQuery is in preview, enabling similar integration into broader data strategies. 
• Efficient bi-directional replication: Smoothly replicate data between 麻豆原创 systems and BigQuery using replication flows from 麻豆原创, enhancing performance and mitigating query bottlenecks. 

麻豆原创 Business Data Cloud is planned to be available in three Google Cloud regions in Q2 2025, including India, Frankfurt, and Iowa, with more to follow over the coming year

Success stories: Realizing value today  

Joint Google Cloud and 麻豆原创 customers are already benefiting from the seamless integration between 麻豆原创 Datasphere and BigQuery.

Power International, a major consumer electronics company, leveraged the integrated solutions to help modernize its sales reporting process. Using 麻豆原创 Datasphere, BigQuery, and Dataform for sales pipeline automation, the company built a real-time sales reporting and analytical solution, which replaced static PDF reports. Power International now enjoys deeper, dynamic, and more actionable business insights, available on demand, which in turn drive improvements in sales performance. 

Driving future integration and innovation 

Building on the existing partnership between 麻豆原创 and Google Cloud and extending our collaboration in the context of 麻豆原创 Business Data Cloud will allow us to enrich analytics and AI capabilities for our joint customers. This approach will allow customers to tap into the comprehensive suite of 麻豆原创 data solutions and integrate with the extensive data sets in BigQuery whether they are private, shared, or public. 

Customers can also complement the AI capabilities available in 麻豆原创 Business Data Cloud with AI applications built on Google Cloud, powered by Google鈥檚 industry-leading Gemini model and third-party AI models available in Vertex AI. This initiative aims to provide pre-packaged, intelligent data products that accelerate time to value for common business scenarios, leveraging the strengths of both platforms. 

To learn more about the 麻豆原创 and Google Cloud partnership, visit booth 301 at 麻豆原创 Sapphire Orlando, taking place May 19-21, 2025.

Irfan Khan is president and chief product officer of Data and Analytics at 麻豆原创.
Andi Gutmans is vice president and general manager of Data Cloud at Google Cloud.

With even more investments being made in AI, it鈥檚 more important than ever for customers to have a solid data foundation.

That鈥檚 why in February of this year, 麻豆原创 introduced 麻豆原创 Business Data Cloud. This fully managed SaaS solution unifies and governs 麻豆原创 and third-party data, enhancing decision-making and AI value. Databricks is natively available in 麻豆原创 Business Data Cloud, which provides data and AI professionals access to industry-leading data engineering, AI, and machine learning capabilities within a single solution.

麻豆原创 Business Data Cloud momentum

Since the initial launch, we鈥檝e made progress to support customers and advance their business data fabric journey.

Several have already adopted 麻豆原创 Business Data Cloud and expect significant benefits. For example, Swedish steel distributor Tibnor is the first live 麻豆原创 Business Data Cloud customer and plans to integrate 麻豆原创 data with non-麻豆原创 sources so it can respond more quickly to changing market conditions.

Dag 脜selius, senior IT advisor and longtime former CIO at Tibnor, said: 鈥淲e鈥檝e always tried to stay ahead of the curve in our industry. 麻豆原创 Business Data Cloud opens new opportunities for integrating external data quickly — something we couldn鈥檛 even imagine just a few years ago.鈥�

This customer momentum builds on a successful pre-launch beta program. 麻豆原创 received positive feedback from those customers that saw benefits across the board, including a 20 to 50 percent improvement in data models. Moreover, the beta community agreed that 麻豆原创 Business Data Cloud will allow them to get greater value out of existing investments in 麻豆原创 Datasphere and Databricks.

麻豆原创 Business Data Cloud and Databricks momentum

麻豆原创 is bringing the power of Databricks into 麻豆原创 Business Data Cloud with 麻豆原创 Databricks, now generally available on Amazon Web Services. The allows us to serve the needs of a broader community of data and AI professionals and provides customers benefits:

• Simpler access to all data: Easily connect to contextual 麻豆原创 data using zero-copy Delta Sharing and blend with third-party data
• End-to-end AI and machine learning: Develop AI and machine learning models with end-to-end lifecycle management from data prep and experimentation to deployment
• Pro-code environment: Write Spark scripts, run SQL analysis, or create machine learning models in any notebook
• Trusted data foundation: Build intelligent insights on a unified and trusted data foundation that governs and protects data and AI assets

Together, 麻豆原创 Business AI and 麻豆原创 Databricks offer powerful, complementary AI and machine learning capabilities.

For example, 麻豆原创 Business AI allows customers to embed AI directly within their business processes. It also helps customers develop and expand AI models trained on their 麻豆原创 data and deploy them directly into business processes for closed-loop decision-making.

Additionally, 麻豆原创 Databricks provides a comprehensive workbench for data preparation and machine learning experimentation, as well as predictive, AI, and machine learning modeling. Customers can use 麻豆原创 Databricks to develop customized AI and machine learning models on harmonized 麻豆原创 and non-麻豆原创 data, tailored to their unique requirements.

Get started with 麻豆原创 Business Data Cloud

Today, 麻豆原创 is introducing a promotional offer to help customers get started. We will offer 麻豆原创 Databricks services at a discounted consumption rate for a limited time through April 30, 2026. This will accelerate 麻豆原创 Databricks workloads by allowing customers to consume more capacity at no additional cost.

Don鈥檛 miss 麻豆原创 Sapphire, to be held May 19-21, 2025, in Orlando, Florida. Register for .

For more about the latest 麻豆原创 Databricks news, .

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

Today, 麻豆原创 announced 麻豆原创 Business Data Cloud, a fully managed software-as-a-service (SaaS) solution that unifies and governs all 麻豆原创 data and seamlessly connects with third-party data. As an evolution of our industry-leading data, planning, and analytics solutions, 麻豆原创 Business Data Cloud brings together 麻豆原创 Datasphere, 麻豆原创 Analytics Cloud, and 麻豆原创 Business Warehouse with a unified experience that delivers transformational insights across all lines of business.  

麻豆原创 also announced a landmark partnership with Databricks that brings the power of Databricks directly into 麻豆原创 Business Data Cloud. This marks a new era in enterprise data management, with two leaders in their domains coming together to redefine how applications and data platforms work together.

Unleash transformative insights

Many organizations still grapple with data they cannot trust. This persistent gap in trust remains a barrier to true innovation in data and AI.

A found that 55 percent cite poor data quality as their biggest challenge. And nearly half of these leaders pointed to the difficulty of harmonizing data across ecosystems as a key reason that innovation stalls.

麻豆原创 Business Data Cloud bridges this gap with a trusted and harmonized data foundation, empowering IT and business leaders with full business context to drive more impactful decisions. 

麻豆原创 Business Data Cloud delivers fully managed 麻豆原创 data products across all business processes. These curated data products align to a highly optimized and unified 鈥渙ne domain model,鈥� maintaining their original business context and semantics, which means you get immediate access to high-quality data you can trust.

Since these data products are fully managed by 麻豆原创, you no longer bear the hidden costs of rebuilding and maintaining data extracts. The SaaS experience simplifies life cycle management, ensures data consistency, and enables zero-copy sharing across your data and analytics ecosystem. 

With these data products, 麻豆原创 Business Data Cloud delivers a suite of pre-built analytical applications that help you uncover hidden insights and fast-track decision-making. These “insight apps” are fully managed and incorporate pre-defined metrics, AI models, and planning capabilities, simplifying how you connect and integrate every part of your business.

This accelerates use cases aligned with your most important business functions, including ERP, spend, supply chain, HR, customer experience, and finance.

Every organization needs a pulse on its most important resources. With insight apps, you can use preconfigured packages already connected to your business data, such as working capital, to gain a 360-degree view of your organization鈥檚 financial health with real-time visibility into cash flow and profitability.

Connect all your data 

麻豆原创 Business Data Cloud connects all your data by leveraging business data fabric principles, making it easier to discover, share, govern, and model your data. It includes 麻豆原创 Databricks as a first-party data service, bringing the power of Databricks directly in 麻豆原创 Business Data Cloud.

• Business semantics: Use 麻豆原创 Datasphere to discover, share, and model the same trusted data across existing platforms without costly data extraction. Build a powerful knowledge graph of all your data, preserving its business metadata and semantics, so your data is easily searchable and actionable. For existing 麻豆原创 Datasphere customers, your investments remain fully supported鈥攚ith no disruptions鈥攁nd all 麻豆原创 Datasphere capabilities will natively be available in 麻豆原创 Business Data Cloud. 
• Data engineering and machine learning/AI: 麻豆原创 Databricks empowers every data professional to accelerate AI models and generative AI apps on their business data. Native capabilities like Delta Sharing harmonize 麻豆原创 data products with existing lakehouses bi-directionally. By integrating all your data with a zero-copy approach, you can apply advanced AI and machine learning models to finance use cases, like predicting the payment date on open receivables.
• 麻豆原创 Business Warehouse modernization: 麻豆原创 Business Data Cloud gives on-premise 麻豆原创 Business Warehouse customers a flexible path to the cloud. With native integration to 麻豆原创 Business Warehouse, easily access your data as a data product with the object store via Delta Share鈥攕implifying your modernization journey and maximizing your 麻豆原创 Business Warehouse investment.
• Analytics and planning: 麻豆原创 Business Data Cloud brings analytics and planning together in one solution, enabling you to go from insights to actions instantly. Automate reporting, simulate possible business outcomes with AI, and unify your financial, supply chain, and operational planning鈥攁ll in a connected view.

鈥溌槎乖� Business Data Cloud will help us unlock the value of our data and drive innovation across our business. Its semantically rich data products and deep Databricks integration will connect and enhance our existing data products, ensuring long-term adaptability. Trusted, business-ready data will empower users to model scenarios and leverage AI insights, building a sustainable and flexible future for our data ecosystems.鈥� 

Markus Hartmann, Corporate Vice President, Head of Business Technology, Henkel

Foster reliable AI 

The rapid growth of agentic AI requires organizations to first have the right data foundation. 麻豆原创 Business Data Cloud brings together all your data to ensure agentic AI is built on accurate, trusted data with business context.

Joule, 麻豆原创鈥檚 generative AI copilot, is deeply integrated with 麻豆原创 Business Data Cloud. The knowledge graph in 麻豆原创 Business Data Cloud connects your data, metadata, and business processes, enabling AI agents, Joule, and large language models (LLMs) to understand your data within the context of its relationships.

This mapping creates clear data links, making insights more reliable for users and applications. Training AI agents and Joule on business knowledge and context drives increased productivity. For instance, users can use AI to complete cross-functional tasks, uncover insights, and summarize critical information across the business鈥攚ithout heavy reliance on IT support. This empowers the usage of AI to automate complex analytics and planning tasks, such as risk assessment, forecasting, and other advanced scenario simulations.

麻豆原创 Business Data Cloud ecosystem 

At the core, 麻豆原创 Business Data Cloud is built to prioritize openness and customer choice. To simplify your data landscape, 麻豆原创 Business Data Cloud supports an open data ecosystem. It integrates natively with leading data and AI partners like Collibra, Confluent, and DataRobot. And it doesn’t stop there; we鈥檒l announce new strategic partnerships in the coming weeks and months to further expand the open data ecosystem. 

Supported by our large partner ecosystem, we鈥檝e made it easier to unleash transformative insights from all your data. We have partners with deep business process and industry domain expertise that are building insight apps on 麻豆原创 Business Data Cloud.
 
From data enrichment to data activation, partner insight apps build on top of the data products and the core services 麻豆原创 Business Data Cloud provides. We鈥檙e thrilled to announce our first partner apps with Accenture, DataRobot, Spendscape by McKinsey, PwC, EY, Deloitte, and Capgemini. 

Get started today鈥� 

Start your journey with 麻豆原创 Business Data Cloud and unleash the power of AI with trusted business data:

• Experience 麻豆原创 Business Data Cloud鈥痺ith the
• : 鈥�30-Minute Primer on 麻豆原创 Business Data Cloud鈥�

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

Read on to learn more about these transformative announcements, which will enable businesses to unlock new potential in the areas of data management, AI-driven planning, and analytics.

Access Insights Wherever Your Data Resides

麻豆原创 Datasphere Knowledge Graph

麻豆原创 Datasphere knowledge graph will enable organizations to better represent their real-world use of data, leading to more effectively leveraging it for generative AI and better reasoning.

As data is onboarded, transformed, and integrated in 麻豆原创 Datasphere, 麻豆原创 Datasphere knowledge graph automatically creates an ontology representing the relationships in the data, including the inherent business context from 麻豆原创 application sources like 麻豆原创 S/4HANA. This is then available to be extended and augmented via an ontology editor to reflect specific attributes within an organization. Finally, the data in 麻豆原创 Datasphere is automatically applied to this ontology to create a knowledge graph that allows the data to be processed as a semantic web of relationships, drawing new insights from connections that are otherwise difficult to follow.

These knowledge graphs are better suited for answering complex, often open-ended questions. For example, a marketing manager might ask a question like: 鈥淲hat type of campaign for mountain bikes works best for my highest performing cities with a population over 1 million?鈥�

Knowledge graphs can provide better context to large language models (LLMs) and prevent AI-generated 鈥渉allucinations.鈥� 麻豆原创 Datasphere knowledge graph will enable organizations to unleash the power of AI for even the most complex queries.

The effort and cost of manually creating knowledge graphs is typically very high. 麻豆原创 Datasphere knowledge graph overcomes this by pre-populating the knowledge graphs using all the valuable content already available in 麻豆原创 Datasphere. The knowledge graph can then be used with Joule, 麻豆原创鈥檚 generative AI co-pilot, allowing business users to ask both open-ended and specific questions and get instant and well-documented answers. Sign up for a preview of 麻豆原创 Datasphere knowledge graph via the link below.

麻豆原创 HANA Cloud Vector Engine

With the next release of 麻豆原创 HANA Cloud, a vector capability will be added to existing multi-model capabilities, allowing customers to gain value from all relevant types of business data using a single database. The inclusion of a vector engine further enables customers to build that combine the natural intuition of human interaction with powerful machine learning and multi-model processing capabilities.

The vector engine in 麻豆原创 HANA Cloud provides the ability to store and compare vectors using SQL. Determining similarity between vectors enables use cases such as retrieval-augmented generation (RAG), recommendations, classifications, clustering, and more. Key benefits of 麻豆原创 HANA Cloud vector engine include:

• Simplify data architecture and security with a single multi-model database with SQL interaction
• Gain new insights by combining spatial, graph, JSON, and relational data with vector queries
• Easily incorporate vector use cases in solutions based on the HANA Cloud ecosystem (clients, Python libraries, CAP, etc.)
• Integrate with open-source community tools such as LangChain via plug-ins

麻豆原创 HANA Cloud vector engine is currently in public preview and is planned for general availability in late Q1 2024.

Simplified Consumption of Data Products in 麻豆原创 Datasphere

Data products facilitate self-service access to data as a product and enable data sharing across application boundaries. Data consumers need an easy way to explore, understand, and activate the data needed to perform their tasks 鈥� and data providers need an easy way to publish their assets and make them available to data consumers.

麻豆原创 is innovating in this space with an improved user experience that drives data sharing at scale. This starts with published data products, whether produced by 麻豆原创 line-of-business applications, industry solutions, or third parties, and follows with simple consumption in 麻豆原创 Datasphere.

In 麻豆原创 Datasphere, customers will find ready access to 麻豆原创 and non-麻豆原创 data products and easily install them into their 麻豆原创 Datasphere instance. The procedure establishes relevant connections and creates the necessary artifacts in 麻豆原创 Datasphere without the user having to enter those details. Key to this is making data provisioning easier via metadata, which are described via the Open Resource Directory (ORD) protocol. The experience will be harmonized within 麻豆原创 Datasphere by bringing catalog and the data product installation closely together. Visit for the latest updates.

麻豆原创 Datasphere Semantic Onboarding Enhancements

Semantic onboarding provides a seamless import of semantically rich objects from 麻豆原创 S/4HANA and 麻豆原创 BW/4HANA into 麻豆原创 Datasphere. Now, we are taking the next step by adding support for 麻豆原创 HANA Cloud and 麻豆原创 data products through the same unified onboarding experience.

Customers will be able to combine their 麻豆原创 HANA Cloud modeling approach with 麻豆原创 Datasphere by importing calculation views into the data layer of 麻豆原创 Datasphere. This preserves the semantic information such as measures, attributes, hierarchies, aggregations, and currencies/units, while keeping 麻豆原创 HANA Cloud and 麻豆原创 Datasphere objects in sync — allowing customers to leverage their prior investments in 麻豆原创 HANA modeling.

Likewise, semantic onboarding of 麻豆原创 data products will enable inheritance of business context from 麻豆原创 line-of-business applications and industry solutions. By providing the semantics of the source systems and transferring that into the business data fabric as a foundation, 麻豆原创 Datasphere drastically improves the analytic workflow and accelerates and simplifies data-driven insights.

Collibra AI Governance Integration with 麻豆原创 Solutions

The 麻豆原创 and Collibra partnership enables end-to-end data governance and delivers trusted data to all users across the business data fabric. As more tasks and decisions are automated by AI within critical business processes, the need to extend governance to AI has also become apparent.

The partnership with Collibra is being expanded to address the data and AI governance needs of joint customers via Collibra AI Governance. We will build tailored integrations between Collibra AI Governance and 麻豆原创 solutions to connect the data used for AI with the models themselves in a single platform, allowing enterprises to track and manage their AI development efforts.

• Customers will better understand data lineage and metadata of 麻豆原创 data that is utilized in AI modeling. With that, users can see what data their AI models were trained on to ensure that the data is accurate and from a trusted source.
• Customers will benefit from a single view to understand what AI models exist in their organization, and what data is being used to power them. AI/machine learning models created with 麻豆原创 technology will be registered with the Collibra AI Governance platform.

This extension of the 麻豆原创 partnership with Collibra will increase transparency and accountability for organizations, and help ensure that regulatory, compliance, and privacy policies are being met. More importantly, it will build user trust by preventing biased decision-making, inaccurate recommendations, and other risks arising from AI.

Together, 麻豆原创 and Collibra will help joint customers address the data and AI governance needs across their organizations. Collibra AI Governance was and is available to interested customers.

麻豆原创 Datasphere Confluent Integration

Core to the 麻豆原创 data strategy is providing customers with the ability to interoperate with the world鈥檚 leading data and AI vendors through an open data ecosystem. To this end, the newly enhanced Confluent integration enables real-time streaming of data to and from 麻豆原创 Datasphere.

First, the outbound capabilities were extended by taking advantage of Confluent鈥檚 proprietary schema registry capabilities. Second, the Confluent schema registry will be used to enable seamless consumption of Confluent data within 麻豆原创 Datasphere.

The integration is specifically tailored to Confluent and provides a superior user experience for joint customers. It allows connections on the application level without additional custom application development. The integration is a pre-established replication flow in 麻豆原创 Datasphere, which already includes delta and real-time processing natively. This makes the process very efficient as it does not force customers to load all the data at every step, but only when data has changed.

The first integration for data ingestion into Kafka and Confluent is generally available. Additional capabilities for Confluent specific outbound and inbound integration will be generally available at the end of Q1 and Q3, respectively.

Transform Planning with a Business Data Fabric

麻豆原创 Analytics Cloud for Planning Deep Integration to 麻豆原创 Datasphere

麻豆原创 Datasphere and 麻豆原创 Analytics Cloud for planning will be more closely integrated to expand the business data fabric to planning use cases. 麻豆原创 Analytics Cloud planning models can be deployed into 麻豆原创 Datasphere, bringing plan and actuals data together for real-time steering.

Through a reduction in both data footprint and modeling efforts, 麻豆原创 Analytics Cloud extends planning functionality via 麻豆原创 Datasphere and its native capabilities for transformation and integration. This reduces the complexity and risk inherent in storing multiple copies of data which is prevalent today.

麻豆原创 Analytics Cloud for planning will have live access to actual and plan data for extended planning and analysis scenarios, including the live usage of master data. With this, 麻豆原创 Datasphere will become the platform on which planning processes and tools can integrate.

麻豆原创 is the only vendor to offer a business data fabric that seamlessly integrates planning and therefore covers the entire technology stack required to transform data into insights and future actions. Visit for the latest updates.

Foster Trusted AI Across Your Business

麻豆原创 Analytics Cloud Generative AI Co-Pilot

麻豆原创 customers will embrace the power of generative AI to create and simulate business plans in 麻豆原创 Analytics Cloud. With the power of Joule, planning and analytics professionals can leverage generative AI capabilities in a wide range of business processes. Activities such as data discovery, dashboard creation, planning model maintenance, and more are benefitting from a boost in core capabilities and an unmatched user experience.

With the power of natural language processing, end users can easily run analytical queries, simulate driver impacts, plan resource allocations, and auto-generate dashboards and calculations. For example, a business user seeking to understand why gross margins declined in the latest version of a plan could query Joule, which could automatically look through previous plan iterations and attached comments, and uncover the fact that planners were estimating higher commodity costs.

麻豆原创鈥檚 investment in AI and its understanding of the context of business data provides truly limitless potential in unleashing the world of planning and analytics.

A preview of Joule co-pilot functionality in 麻豆原创 Analytics Cloud is planned to be available in Q2 2024. Sign up for the preview via the link below.

麻豆原创 Analytics Cloud Compass

In an increasingly volatile business climate, it is essential to create operational and financial plans and provision BI insights with risk mitigation in mind. This requires the ability to simulate uncertainties and the probability of their impact. Knowing how uncertainties in commodity prices, labor costs, or production volumes will hit your operational expenses or revenue means that companies can quickly prepare and plan counter measures for any scenario.

麻豆原创 Analytics Cloud compass provides Monte Carlo simulation capabilities with a business user-friendly interface. This enables non-technical users to perform real-time multi-variate analysis without prior IT setup or advanced statistical skills.

Users can perform business simulations directly in 麻豆原创 Analytics Cloud at a fraction of the time and effort required to perform similar analysis manually. Scenario modeling capabilities will allow comparisons between assumptions, and the reporting of impact variances provides real-time insight, concept validation, and reveals the sensitivity of the drivers chosen. Now customers can identify their major drivers and combinations over time, enabling a better understanding of the dynamics between the data, and how to continuously simulate better and faster. With compass, customers can face the future with confidence.

A preview of 麻豆原创 Analytics Cloud compass is planned to be available at the end of Q3 2024. Sign up for the preview via the link below.

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Irfan Khan is chief product officer and president for 麻豆原创 HANA Database & Analytics.