Data is critical in modern enterprise, particularly in this brave new world of generative artificial intelligence (genAI).

But data is increasingly unwieldy and voluminous — the world is estimated to create a staggering estimated 2.5 quintillion bytes of data a day. Yet, much of that isn’t accessed or even put to work. In fact, enterprises are only using 32% of it.

To help organizations derive greater insights from their data, SAP is today announcing several new and enhanced genAI-powered tools. The tech giant is looking to differentiate itself in an ever-intensifying, competitive landscape where new AI platforms are rolled out every day.

Daniel Yu, SAP’s SVP for solution management and product marketing, pointed out that the world is moving to a “new operating model” based on genAI and trust in data.

“Everything will be backed by some type of intelligent AI algorithm,” he said. “Data is going to be the most important asset.”

Underpinned by business data fabric

SAP’s tools are built on the business data fabric concept, which centralizes, connects, manages and governs data across different systems and applications.

Gartner, for its part, describes data fabric as “an emerging data management design for attaining flexible, reusable and augmented data integration pipelines, services and semantics.” The firm predicts that this year, data fabric deployments will have quadrupled efficiency around data usage and cut human data management tasks in half.

Yu noted that most organizations have multiple disparate clouds, data repositories (warehouses, lakes, lakehouses) and on-premises investments.

“The idea with data fabric is to connect all this different data together,” he said. This provides a semantic overlay so that users can easily see their data and act on it more effectively.

A problem to this point has been that “a lot of workers still don’t have the context to make the right business decisions,” said Yu.

Knowledge graphs provide context

To help provide insight into enterprise data relationships and patterns across apps and systems, SAP is also today introducing its new SAP Datasphere knowledge graph.

Knowledge graphs are semantics used to search data across multiple sources and forge connections between them. This can help users better understand how their data, metadata and business processes work together, Yu explained.

“It’s not about providing more data, it’s about providing better context,” he said. “With knowledge graphs, users are able to ask much more sophisticated questions.”

For example, users could ask the AI-powered system to provide top sales products by region over the last 24 months. Or, Yu said, they could posit: “What would be the most sophisticated marketing campaign based on my supply chain processes?”

Previously, gathering this kind of information would require collaboration across multiple different platforms, he pointed out.

“When you pair knowledge graphs with traditional techniques and data, you’re able to produce much more high-quality and relevant data for non-users,” said Yu.

Automating reports, dashboards and plans

But organizations, naturally, want to move beyond just visibility. “It’s not only about analyzing something,” said Yu, “but about taking action.”

To support this, SAP’s genAI copilot Joule is today being integrated into SAP Analytics Cloud to automate the creation and development of reports, dashboards, plans and other materials.

The integration is supported by SAP HANA Cloud vector capabilities, which combine large language models (LLMs) with relevant business data.

Users can log into SAP and have a “chat-like experience” backed by Joule, said Yu, adding that this is not just a “generic copilot” — it provides context from the model itself.

“SAP Analytics Cloud understands the context of plans, the context of models,” said Yu. “It’s able to generate dashboards and planning services on top of that.”

Similarly, a new SAP Datasphere integration with SAP Analytics Cloud will provide a data management system that supports advanced analytics and cross-organizational planning. Users can break down barriers between departments and use one tool for data preparation, modeling and planning.

Additionally, business users have access to a new compass capability in SAP Analytics Cloud that allows for data-driven simulation. They can run scenarios through a chat interface, evaluate predictive outcomes and continually adjust, Yu explained.

Expanded partnerships to bolster AI and data governance

Finally, SAP’s data tools now incorporate Collibra’s AI Governance platform. This will help organizations ensure they are meeting regulatory, compliance and privacy policies, Yu explained.

Most companies today are struggling with data governance and AI governance, he noted. Ultimately, they are “two sides of the same coin.”

SAP will integrate Collibra to provide a single “cockpit” that will look at models being used and data lineage as well as policy management, he explained.

It’s not enough just to understand enterprise data and where it comes from, he emphasized; organizations must be able to manage it based on quality and privacy rules to ensure fairness and reduce bias.

“We are expanding the partnership to bring AI and data governance together,” said Yu.