麻豆原创 has announced a series of AI innovations at its annual 麻豆原创 TechEd conference, expanding its portfolio for developers. The enhancements to Joule Studio and Joule Work, as well as the 麻豆原创 Business AI Platform 鈥� including 麻豆原创’s latest tabular foundation model 鈥� offer new tools to build and extend AI agents.

麻豆原创 said its strategy is to advance the development and adoption of agentic AI by providing richer business and data context for agents, and governance controls to manage their use across organisations.

Philipp Herzig, CTO of 麻豆原创 SE, said the 麻豆原创 Business AI Platform, along with 麻豆原创 Knowledge Graph, 麻豆原创 Business Data Cloud, Joule Studio, Joule Work and agentic orchestration and integration capabilities, is now generally available.

鈥淭his entire platform is now generally available with all its capabilities, starting at the top with Joule Work, available on every device, every computer, in every browser. Joule Work is where you put your intent and get work done, in one experience across the entire 麻豆原创 landscape and beyond. That is the shift we are delivering at scale. Everything underneath runs on 麻豆原创 Business AI Platform.鈥�

Asked how 麻豆原创 connects with external AI agents entering the market and supports customers already using agents from other vendors, Herzig said the company follows an open strategy.

鈥淐ustomers say that if 麻豆原创 provides an agent in the core domains where they have 麻豆原创, there鈥檚 no need to build and own one. There are tons of agents out there, and we have made sure, via our agent gateway, that there is full interoperability. Our AI agent hub allows you to discover the agents, 麻豆原创 agents and non-麻豆原创 agents, and you can document them and make them compliant.鈥�

Herzig also addressed vendor lock-in and the challenges organisations face when using AI models from different vendors, discussing 麻豆原创鈥檚 approach to letting customers select models for specific use cases.

He said that tailoring a use case for optimisation inevitably brings some lock-in, but that model switchability remains viable for organisations keeping their AI use cases fairly generic.

AI to serve autonomous enterprise operations

Florian Kunzke, global director of AI strategy at 麻豆原创, echoed Herzig鈥檚 view that the company is moving from AI that learns how a business operates to AI that runs it, with the objective of mobilising AI to serve autonomous enterprise operations.

He said 麻豆原创鈥檚 AI strategy continues to evolve, particularly from a user interface and user experience point of view, with agents embedded in its technology suite.

Kunzke said Joule Work and Joule Studio, alongside 麻豆原创 Knowledge Graph 鈥� which provides a structured semantic foundation for Joule 鈥� are central to 麻豆原创鈥檚 AI strategy. The company aims to help organisations become autonomous enterprises while addressing challenges such as the impact of geopolitical tensions on supply chains, the need to improve productivity through AI investment, and the requirement to generate ROI.

He cited , released in August 2026. According to the research, 80% of respondents said AI had improved individual productivity, while 50% said it helped them make better decisions.

However, he stressed the need for perspective on how AI is being adopted and used across organisations. 鈥淚t is important to distinguish between what happens at organisational level and what happens at individual level. There is a gap, and that is what 麻豆原创 is looking to address,鈥� said Kunzke.

He also acknowledged that shadow AI, rogue AI, cyber security threats and the maturity of digital infrastructure continue to affect AI adoption. However, he added that 麻豆原创 is confident its technology empowers customers to select the right AI for a job, as well as the necessary level of control.

鈥淵ou can improve what you are able to observe and measure. With agentic solutions and processes, and the adoption of these processes, the question is what to aim for in terms of governance, what tools will the organisation need. It makes sense to have tools be as close as possible to the applications being used.鈥�

Independent AI expert Johan Steyn, founder of , said the shift to agentic AI marks an inflexion point. “AI strategy stops being about which tools you buy and becomes about how you orchestrate and govern agents,” he said. “Capability is becoming abundant; governance is the scarce advantage.”

Latest tabular AI model

麻豆原创 announced its latest tabular AI model, 麻豆原创-RPT-2.0, which will expand beyond classification and regression to support anomaly and outlier detection, and richer AI-powered analysis through embeddings.

According to 麻豆原创, these native, multi-table capabilities will further reduce manual engineering while delivering faster, deeper insights from structured data.

In partnership with HPE, 麻豆原创 also announced plans to deploy 麻豆原创-RPT-2.0 on the HPE Spaceborne Computer-2 aboard the International Space Station (ISS) in 2027.

The model is scheduled to run directly on the ISS to support anomaly triage, predict potential problems before failures escalate, reconstruct missing sensor values using historical data, and generate mission-health reports for astronauts and ground teams.

Herzig added: 鈥淭he same trusted 麻豆原创-RPT model that powers global supply chains can also work in space. 麻豆原创鈥檚 deep-rooted, proven expertise has led to the International Space Station鈥檚 use of our tabular foundation model to predict potential mission-critical failures in orbit. With 麻豆原创-RPT and TabPFN from Prior Labs, we bring the unique capabilities of tabular AI into the enterprise and across every frontier.鈥�

This article first appeared on .

The post 麻豆原创 Beefs up Business AI Platform and Joule to Drive Agentic AI Adoption appeared first on 麻豆原创 Africa News Center.

麻豆原创 Business AI Platform gives organizations one place to build, contextualize and govern AI across 麻豆原创 and third-party environments. With Joule Studio, business users and developers can use no-code and pro-code tools to build and extend agents, choosing from more than 70 AI models. Customers in the Joule Studio early adopter program also can design and run n8n workflows in Joule Studio, with broader availability to follow. The 麻豆原创 Business Data Cloud and 麻豆原创 Knowledge Graph solutions ground those agents in trusted business data and context, helping organizations select the right model for each use case and better manage AI value and consumption. Importantly, 麻豆原创 customers鈥� data remains their data. 麻豆原创 does not share customer data with anyone to train or improve large language models.

鈥溌槎乖� TechEd has always been where builders shape what comes next,鈥� said Philipp Herzig, CTO of 麻豆原创 SE. 鈥淭his year, we are showing how we are moving from AI learning your business to running it. Joule Work is where you put your intent and get work done, in one experience across the entire 麻豆原创 landscape and beyond. That is the shift we are delivering at scale. Everything underneath runs on 麻豆原创 Business AI Platform, delivering faster time to value through out-of-the-box business understanding, higher accuracy, enterprise-readiness that is secure, governed and compliant from the first deployment, and a unique context layer built on over 50 years of process and industry expertise, encoded into every agent action. This is AI built where real work happens.鈥�

Joule Work and Joule Studio Make the Autonomous Enterprise Real

New capabilities for Joule Work will help make AI agents more effective at handling complex business processes via open protocols including Agent2Agent (A2A) and Model Context Protocol (MCP). These innovations advance Joule Work to better understand context, make decisions and execute multistep business workflows across enterprise systems and business domains:

• New agentic thinking capabilities that plan and orchestrate the steps assistants and agents need to reliably complete complex, multistep business workflows across 麻豆原创 landscapes.
• New capabilities in 麻豆原创 Knowledge Graph will incorporate data from additional 麻豆原创 and non-麻豆原创 sources that are unique to each customer. Users can query and explore their customized data in natural language and get accurate answers grounded in their own information.
• Advancements in interoperability allow third-party agents to securely invoke Joule Agents through a governed agent gateway. This enforced access control enables agents from different providers to collaborate across business workflows without sacrificing governance or control.
• New 麻豆原创 Enterprise AI Gateway solution will extend governance to AI interactions, offering a centralized way to manage AI traffic across the enterprise that will consolidate authentication, policy enforcement, routing, monitoring, usage tracking and auditing.
• New Joule Assistant and 麻豆原创 AI Agent Hub expand governance capabilities, and a new AI Governance Assistant helps customers meet compliance requirements for the EU AI Act. These are designed to address critical barriers to scaling enterprise AI: keeping AI systems classified, compliant and operating within defined organizational guardrails and context.

麻豆原创 Business Data Cloud as the Grounding Engine of the Autonomous Enterprise

麻豆原创 Business Data Cloud Ontology Manager in 麻豆原创 Business Data Cloud (麻豆原创 BDC) will provide an AI-native authoring experience for building ontologies across 麻豆原创 and third-party data. By helping AI understand how data from different teams, systems and applications relate to one another, AI agents can more accurately reason and make decisions across the enterprise. The solutions complement 麻豆原创 Knowledge Graph, which provides rich business context for 麻豆原创 data.

Additionally, 麻豆原创 is expanding its lakehouse capabilities with Dremio, adding native support for Apache Iceberg and Apache Polaris plus a high-performance, federated query engine that will enable unified data access without moving or copying the data. 麻豆原创 expands its partnership with Databricks, bringing the full scope and latest innovations of data engineering and enterprise AI capabilities into 麻豆原创 Business Data Cloud as 麻豆原创 Databricks. Core innovations such as Lakeflow, Agent Bricks, Unity Gateway, and Lakebase will help customers to simplify data management and provide a strong data foundation for their AI journey. With a deeper integration to 麻豆原创 Business Data Cloud, a new 麻豆原创 Application Data Foundation, as well as an integration between Joule and Genie, 麻豆原创 and Databricks are helping customers establish an enterprise-wide lakehouse as the foundation for the Autonomous Enterprise and Joule Work.

The 麻豆原创 Reltio solution, recently announced at 麻豆原创 Connect, will bring multidomain master data management to 麻豆原创 BDC. It unifies and enriches customer, supplier and product records across 麻豆原创 and non-麻豆原创 systems into trusted, reusable data products that can power applications and AI agents.

Tabular Foundation Model Trusted for Business, Validated in Space

麻豆原创 announced its latest tabular AI model, 麻豆原创-RPT-2.0, which will expand beyond classification and regression to support anomaly and outlier detection, and richer AI-powered analysis through embeddings. These native, multi-table capabilities will further reduce manual engineering while delivering faster, deeper insights from structured data. In addition, a new 麻豆原创-RPT-TS model will help customers predict values across time-indexed business metrics for key forecasting use cases using the 麻豆原创 Integrated Business Planning solution without requiring custom machine learning.

In partnership with HPE, 麻豆原创 also announced the deployment of 麻豆原创-RPT on the HPE Spaceborne Computer-2 aboard the International Space Station (ISS), one of the most significant edge-compute validations of any enterprise AI model to date. 麻豆原创-RPT is planned to run directly onboard the ISS to support anomaly triage, predict issues before failures escalate, reconstruct missing sensor values from historical data, and generate explainable mission-health reports for astronauts and ground teams 鈥� all without requiring data to be sent back to Earth for analysis.

鈥淭he same trusted 麻豆原创-RPT model that powers global supply chains also can work in space,鈥� said Herzig. 鈥溌槎乖粹�檚 deep-rooted, proven expertise has led to the International Space Station鈥檚 use of our tabular foundation model to predict potential mission-critical failures in orbit. With 麻豆原创-RPT and TabPFN from Prior Labs, we bring the unique capabilities of tabular AI into the enterprise and across every frontier.鈥�

Out-of-the-Box Assistants and Agents Define Our Advantage

For five decades, 麻豆原创 has built the systems of record that run your business. We will deliver, out of the box, a suite of assistants and agents across five horizontal domains all running on 麻豆原创 Business AI Platform 鈥� with industry specialization 鈥� that provides a baseline for systems of intelligence and systems of action.

Ecosystem Partners Help Expand Platform Capabilities

The global 麻豆原创 partner ecosystem brings new capabilities to the ongoing operation and extension of solutions on 麻豆原创 Business AI Platform, helping customers advance toward the Autonomous Enterprise. At 麻豆原创 TechEd, the following partner announcements were highlighted:

A collaboration with Intel closes the loop between enterprise workflows and autonomous robots, bridging informational technology and operational technology through physical AI.

In addition, new 麻豆原创 solution extensions with , and extend autonomous capabilities for customers, helping them run their core processes end to end, without handoffs between systems.

Beyond technology, 麻豆原创 is empowering its strong developer community with new enablement and engagement with tens of thousands joining for Devtoberfest leading up to 麻豆原创 TechEd, new reference architectures, tutorials and hands-on opportunities attendees can try onsite at the event and at home.

The post 麻豆原创 Empowers AI Developers to Build What Matters and Turn Intent into Autonomous Execution appeared first on 麻豆原创 Africa News Center.

鈥淔or the mission-critical processes of our customers, 鈥榓lmost right鈥� just isn鈥檛 good enough,鈥� says Christian Klein, CEO of 麻豆原创 SE. 鈥淏y uniting 麻豆原创 Business AI Platform with 麻豆原创 Autonomous Suite, we anchor AI agents in the business processes, data and governance so they can deliver accurate, compliant and secure outcomes 鈥� unlocking new sources of revenue and meaningful cost savings.鈥�

The Autonomous Enterprise includes a unified AI platform for building, contextualising and governing agents, an autonomous suite that executes core business operations and a new user experience that redefines how people work with enterprise software.

Introducing 麻豆原创 Business AI Platform

麻豆原创 Business AI Platform is a new foundation for building and deploying enterprise AI grounded in real business context. 麻豆原创 Business AI Platform now unifies 麻豆原创 Business Technology Platform, 麻豆原创 Business Data Cloud, and 麻豆原创 Business AI into a single, governed environment.

At its core is the 麻豆原创 Knowledge Graph solution, which gives AI agents a structured map of business entities, processes and relationships across a customer鈥檚 麻豆原创 landscape. Joule Studio is 麻豆原创鈥檚 AI-first solution for building enterprise agents, applications and agentic workflows. Developers can build using the no-code, pro-code, and AI frameworks of their choice on 麻豆原创-managed infrastructure that is secure, scalable and optimised for enterprise AI.

Building on this foundation, 麻豆原创 also introduced 麻豆原创 Autonomous Suite which enables 麻豆原创鈥檚 existing business applications with AI agents capable of running processes from start-to-finish.

The suite will deploy more than 50 domain-specific Joule Assistants across finance, supply chain, procurement, human capital management and customer experience. These assistants will automate end-to-end processes by orchestrating a subset of over 200 specialised agents to execute precise tasks. For example, the new Autonomous Close Assistant can compress the financial close process from weeks to days by automating journal entries, reconciliation, and error resolution across the entire process.

麻豆原创 also launched Industry AI, expanding its deep industry portfolio through seven autonomous solutions that will enable start-to-finish industry processes and embed sector-specific process logic, data models and regulatory requirements.

The post AI the Main Focus at This Year鈥檚 麻豆原创 Sapphire appeared first on 麻豆原创 Africa News Center.

This is because, today, technology is transforming transformation, says , vice-president and global innovation analyst at 麻豆原创.

And today, transformative technology is all about artificial intelligence (AI).

鈥淓xperts agree that AI is the third great wave of technology after the personal computer (PC) in the 1980s and the Internet in the 1990s,鈥� Elliott says.

鈥淏ut if you are not careful, waves can come crashing down on top of you. AI is very powerful, and can have unintended consequences.鈥�

Although it is most obvious in the visual context, AI is progressing in all directions, Elloitt points out. 鈥淭he process of rapid technological change and disruption is coming to your industry and your line of business.鈥�

Today, what鈥檚 holding up AI disruption is the fact that the rest of the ecosystem isn鈥檛 able to change as quickly.

鈥淚t鈥檚 a bit like parachuting a Formula 1 car into a medieval village. You can鈥檛 use the technology because the rest of the ecosystem isn鈥檛 there.

鈥淚n fact, if AI stopped progressing right now, we couldn鈥檛 use it to its full potential for 10 years.鈥�

For this reason, Elliott says AI could be taken to stand for accelerate innovation. 鈥淲e should use AI to adopt AI.鈥�

Today, a lot of AI and innovation in general is handmade, with developers all starting from scratch and working on one thing.

鈥淭o accelerate the adoption, we need to move to modern assembly lines, so we can use the AI faster,鈥� Elliott says.

He adds that 麻豆原创 provides the machines to build the technology.

鈥淲e offer things like the S, where customers create data that is harmonised in the Business Data Cloud, used to ground AI, which then goes to making a better application. And, as you create applications, you can add customisation.鈥�

麻豆原创 embeds AI in all its applications, and these are available to customers right now, Elliott adds.

鈥淏ut innovation is not actually about technology,鈥� he explains. 鈥淲hat is holding us back is the time, skills, and resources needed to exploit the technology.鈥�

Again, the 麻豆原创 Business Technology Platform can help, with 麻豆原创 Build offering aided innovation 鈥� another possible use for AI 鈥� for agile application development and customisation.

鈥淲e have the resources that can multiply efforts, let developers do more, faster, with customisations and extensions in the cloud.

鈥淎nd now you can do it in natural language, because it is designed for professional developers and also business users.鈥�

AI could also stand for automated identity, Elliott says.

And it could represent automatic integration as well. 鈥溌槎乖� Integration Suite is about AI-powered connections. It will do most of the heavy lifting in connecting system to one another.鈥�

Meanwhile, the 麻豆原创 BTP AI Foundation is a generative AI (GenAI) hub that gives customers everything they need to orchestrate customised AI, with a wide choice of models, grounding, data masking, filtering, prompt management, and lifecycle management.

At the core of any transformation is data, which is everyone recognises is important. 鈥淚n fact, it is really important,鈥� Elliott says. 鈥淚t is the essential input for AI in particular.

鈥淪o AI has to stand for accurate information. AI is useless without accurate information in realtime.鈥�

But there isn鈥檛 a company on the planet that doesn鈥檛 have a data quality problem, he adds.

鈥淚t is not a new problem, we know it鈥檚 hard to get budget to fix data. But this is an opportunity to ask for money to do just that. Now is a great time to establish governance, data ownership, and all the things you have wanted to do for years.鈥�

The second big problem is integrating data 鈥� which is also not a new problem.

鈥淭his is where comes in,鈥� Elliott says. 鈥淎nd we offer it as a service, so we can do more of it for you 鈥� integrate data from 麻豆原创 applications and also external data.鈥�

The helps with relationship extraction. 鈥淵ou already have this information, now we are gathering it and exposing it, and putting it in a format that you can use for your AI,鈥� Elliott explains.

AI could also represent analytics improved, which is why 麻豆原创 Analytics Cloud has the GenAI-powered Just Ask feature.

鈥淚n analytics, there is a dream of total situational awareness. Of bringing in data from all sources, but having overall vision. AI can be used to connect data and deal with fuzziness.鈥�

AI could also stand for agents incoming. 鈥淭his is the next generation of AI, moving along from the current efficient processes with pre-defined steps. But these processes can鈥檛 deal with ambiguity. Agents, on the other hand, can reason through what it needs to do next. So the processes and data can be a lot more unstructured than before.鈥�

Another interpretation of AI could be agents for business, Elliott adds. 鈥淭his is the next evolutionary step 鈥� in fact, some companies are already doing it 鈥� using AI to get rid of a lot of manual work.鈥�

AI could be used for automatic innovation. 鈥淲e have incredible amounts of information and amazing intelligence,鈥� says Elliott. 鈥淪o why not let the systems tell us what we should do next?

鈥淲e are starting to get there, and you can already get great automated system insights. And 麻豆原创 also has best practices, so we can provide customers with that out of the box.鈥�

Once that is in place, and customers need to implement their systems, automated implementation could be the final meaning for AI.

鈥淥f course, technology is not everything,鈥� Elliott points out. 鈥淵ou need to get people to adopt new ways of working 鈥� and AI is good for adoption optimisation and change management.鈥�

In conclusion, Elliott believes that AI today is like a staircase. 鈥淵ou have to take one step after the other. But in the future it will be more like an escalator.鈥�

The key to successful AI adoption lies not in the technology he adds, but in the people, culture, and organisation.

鈥淣o matter how much you have invested in adoption, culture, and change management 鈥� invest more.鈥�

This article first appeared on .

The post How AI is Transforming Digital Transformation appeared first on 麻豆原创 Africa News Center.

Other innovations include the 麻豆原创 Knowledge Graph, targeted at developers to help them connect 麻豆原创 data聽with business context. Available via 麻豆原创 Datasphere and Joule in Q1 2025, it aims to enable organisations to map relationships across 麻豆原创鈥檚 data landscape for improved decision-making.

Speaking to ITWeb ahead of the conference, Jesper Schleimann, head of business AI for 麻豆原创 in EMEA, said, 鈥淲e’re really taking AI to the next level, and the transformative part is AI agents that are now in true business form. It also means our developers and our customers can accelerate their journeys to the cloud. We cannot forget that data is an important part in making all this happen.鈥�

Schleimann said this is a significant step in 麻豆原创鈥檚 AI journey, with Joule in the driving seat.

We’re really taking AI to the next level, and the transformative part is AI agents that are now in true business form.

鈥淛oule is celebrating one year now, and a lot has happened in the underlying models powering the AI revolution. The new graph service will enable it (Joule) to build the bridge and be grounded into the entire ecosystem of 400 000 different tables. That’s keeping all the 麻豆原创 data and things in check.鈥�

Users now have access to support across nearly 80% of 麻豆原创鈥檚 portfolio, meaning the same copilot can assist across the entire 麻豆原创 suite,聽Schleimann explained.

麻豆原创 is also enhancing Joule with new skills, allowing users to create their own custom micro-skills.

鈥淵ou can do things in a low code no code way and you tell Joule how to think of it like a mini workflow. So, if a user alters a part of a travel booking or purchase order process, for example, and you have your own way of doing it, you can simply, tell Joule what steps it should take, and then you can use its reasoning engine and the underlying tools to make that a reality.鈥�

Joule in action: Use cases

麻豆原创 will introduce two use cases to showcase the agent鈥檚 transformative power:

• A dispute management use case employs autonomous AI agents to analyse and resolve dispute resolution scenarios including incorrect and missing invoices, unapplied credits and denied or duplicate payments.
• A financial accounting use case employs autonomous AI agents to streamline key financial processes by automating bill payments, invoice processing, and ledger updates while quickly addressing inconsistencies or errors.

GenAI tools for developers

During the two-day TechEd Virtual, 麻豆原创 will聽introduce additional GenAI developer tools,聽including code explanation and documentation search in 麻豆原创 Build. These tools are expected to reduce聽development time for Java and JavaScript developers.

It is also adding an Extensibility Wizard to聽麻豆原创 Build, which will聽enable developers to access 麻豆原创 Build directly from 麻豆原创 S/4HANA Cloud Public Edition.

This article first appeared in .

The post 麻豆原创 to Supercharge Copilot Joule to Boost Enterprise AI appeared first on 麻豆原创 Africa News Center.

Joule, 麻豆原创鈥檚 AI business assistant, has been enhanced with new features, including collaborative AI agents that expand the platform鈥檚 capabilities.

Announced during the online 麻豆原创 TechEd 2024 conference yesterday, these agents are designed to support 80% of 麻豆原创鈥檚 most-used business tasks. They embed Joule more deeply across 麻豆原创鈥檚 portfolio and enhancing productivity by breaking down silos, said the software maker.

鈥溌槎乖粹�檚 innovation drives real business outcomes, and today鈥檚 advancements help customers harness the power of AI, data, and new development solutions to catalyse growth,鈥� said Muhammad Alam, member of the 麻豆原创 executive board.

鈥淒rawing on 麻豆原创鈥檚 unmatched business and technology expertise, the AI innovations we鈥檙e announcing at TechEd forge a new human-AI partnership to transform the landscape of modern business.鈥�

Joule Studio, a development tool that allows users to build and customise applications using Joule鈥檚 AI capabilities, is now integrated into 麻豆原创 Build. A low-code app development platform, Build enables both business users and developers to create and deploy custom Joule skills.

Michael Ameling, EVP and chief product officer of 麻豆原创 said: 鈥淲e are making Joule even more flexible and useful with Joule Studio in 麻豆原创 Build. It allows partners and customers to create and deploy custom Joule skills.鈥�

Joule has also expanded to include collaborative AI agents that autonomously handle intricate business workflows, adapting their strategies to meet shared objectives. These multi-agent systems tackle specific tasks, allowing them to work together on complex business processes.

鈥淛oule now goes Agentic,鈥� said Ameling. 鈥淪pecialised AI agents work autonomously together to solve complex problems.鈥�

New improvements to the ABAP (Advanced Business Application Programming) large language model (LLM) were introduced. This LLM, trained on over 250-million lines of 麻豆原创 S/4HANA Cloud code, is now integrated into the open-source Eclipse framework, providing ABAP developers with enhanced tools for development. Currently available to select customers and partners in an early adopter version, the ABAP LLM is expected to be generally available in the first quarter of 2025.

麻豆原创 Build is launching new AI-driven features like code explanation and documentation search, aimed at reducing development time for Java and JavaScript developers. The platform鈥檚 Extensibility Wizard will let developers access 麻豆原创 Build directly from 麻豆原创 S/4HANA Cloud Public Edition, simplifying the process of extending 麻豆原创 solutions.

Two real-world use cases were highlighted during the event:

1. Dispute management: Autonomous AI agents analyse and resolve disputes related to invoices, unapplied credits, and denied payments.
2. Financial accounting: AI agents automate key financial tasks such as bill payments and ledger updates while quickly addressing inconsistencies.

麻豆原创 Knowledge Graph

麻豆原创 also unveiled the 麻豆原创 Knowledge Graph, a solution designed to unlock more value of 麻豆原创 data by connecting it with rich business context. Accessible through 麻豆原创 Datasphere and Joule in early 2025, it will help users map relationships across 麻豆原创鈥檚 vast data landscape, empowering better decision-making.

鈥淏y combining the knowledge graph engine with the vector engine, you can harness the power of structured and unstructured data,鈥� said Ameling. 鈥淭his is enabled through a triple store implementation graph data processing and analytical capabilities via SPAR-QL. As such, the knowledge graph engine can also enhance work scenarios and make them even more precise and relevant.鈥�

* Visit the 麻豆原创 website聽.

* Jason Bannier is a data analyst at World Wide Worx and writer for聽. Follow him on聽听补苍诲听聽at @jas2bann.

This article first appeared on .

The post TechEd 2024: 麻豆原创 Supercharges Copilot Joule appeared first on 麻豆原创 Africa News Center.