SAP enhances Datasphere and SAC for AI-driven transformation

SAP announced today a host of new AI copilot and AI governance features for SAP Datasphere and SAP Analytics Cloud (SAC). Jurgen Mueller, SAP CTO and executive board member, called the innovations, which includes an expanded partnership with data governance specialist Collibra, a “quantum leap” in the company’s ability to help customers drive intelligent business transformation through data.

“SAP is executing on a roadmap that brings an important semantic layer to enterprise data, and creates the critical foundation for implementing AI-based use cases,” said analyst Robert Parker, SVP of industry, software, and services research at IDC.

SAP unveiled Datasphere a year ago as a comprehensive data service, built on SAP Business Technology Platform (BTP), to provide a unified experience for data integration, data cataloging, semantic modeling, data warehousing, data federation, and data virtualization. At SAP Datasphere’s core is the concept of the “business data fabric,” a data management architecture delivering an integrated, semantically rich data layer over the existing data landscape, and providing seamless and scalable access to data without duplication while retaining business context and logic.

With today’s announcements, SAP is building on that vision. The company is expanding its partnership with Collibra to integrate Collibra’s AI Governance platform with SAP data assets to facilitate data governance for non-SAP data assets in customer environments.

“We have cataloging inside Datasphere: It allows you to catalog, manage metadata, all the SAP data assets we’re seeing,” said JG Chirapurath, chief marketing and solutions officer for SAP. “We are also seeing customers bringing in other data assets from other apps or data sources. In this model, it doesn’t make sense for us to say our catalog has to understand all of these corpuses or data. Collibra does a fantastic job of understanding it.”

The expanded partnership gives customers the ability to use Collibra as a “catalog of catalogs,” with Datasphere’s catalog also managed by the Collibra platform.

“It enables the business data fabric, where data is managed according to the meaning of data,” said Chirapurath. “You can collaborate on these sets, so partners like Collibra, Databricks, Google BigQuery, DataRobot, Confluent can help you utilize that fabric in a way that’s most meaningful in the context they have.”

David Menninger, SVP and research director at ISG’s Ventana Research, sees the partnership as a sign that SAP is serious about working with ISVs.

“That hasn’t always been the case,” Menninger said. “Customers should be encouraged. Nearly every customer has an information architecture that expands beyond SAP. And while the SAP products are very capable with respect to its data estate, Collibra has built its entire architecture around governing and working with a variety of products.”

Integrating gen AI

In addition to governance, SAP also announced it integrated SAP SAC, the company’s business intelligence and planning solution, with its generative AI copilot, Joule, enabling it to automate the creation and development of reports, dashboards, plans, and more. The combination enables SAP to offer a single data management system and advanced analytics for cross-organizational planning.

Chirapurath noted that planners will now have a single tool that cuts across data silos for data preparation, modeling, and planning. The new Compass capability in SAC enables complex simulations via a chat interface that planners can use to evaluate predictive outcomes and adjust controllable variables.

“You can ask Joule inside SAC to develop financial plans or some other type of plans, and it will help develop that for you,” Chirapurath said.

The automation of Joule in SAC is powered by the new Vector Engine capabilities in SAP HANA Cloud. Vector embeddings represent data (including unstructured data like text, images, and videos) as coordinates while capturing their semantic relationships and similarities. The SAP HANA Cloud Vector Engine, unveiled a few months ago, is a multi-model engine that can store and query vector embeddings like any other data type.

“SAP application data is largely tabular, so the vector embedding is important to introduce unstructured repositories such as large language models into the overall knowledge graph,” IDC’s Parker said.

Chirapurath further explained that when training AI, it’s not enough to simply work with relational data. To truly unlock the potential of an AI copilot, it needs to be able to access and understand unstructured data such as PDFs and email. To illustrate this point, he gave the example of asking a copilot to generate a dashboard that shows all invoices.

“Invoices as an object inside an enterprise could be an email or a PDF document; it could be a text file,” Chirapurath said. “SAC has to be able to understand all those things and then provide links to it. That combination of SAC, with Joule, now working natively against HANA with its vector database capabilities, makes it a much more compelling value proposition for customers.”

Ventana Research’s Menninger agrees.

“At first, the SAP gen AI features in SAP Analytics Cloud appear to be similar to other copilot types of capabilities like chat interfaces to data and analytics,” Menninger said. “But what makes the SAP capabilities unique is their ability to use Joule with the planning capabilities in SAC, not just to query the data but create new planning models as well as scenarios.”

Copilots across the portfolio

SAP isn’t just integrating Joule with SAC. The company is making the copilot available across its range of SaaS applications.

“Joule will behave in the context of an application or product that you’re working in,” Chirapurath said. “In the SuccessFactors application, Joule will behave like an HR assistant. In the app dev platform, SAP Build, it will behave like a developer’s assistant, generating code.”

Menninger sees generative AI unlocking the power of ERP and similar software applications by transforming the fundamental nature of how users interact with them.

“ERP applications and others require people to think like computers, to understand how they work, and to frame their interactions in the structured way that they operate,” he said. “A chat interface using gen AI enables people to do so in a much more natural way using conversational interfaces. Rather than putting the burden on the user to understand how the application works, with gen AI, the burden is on the computer to understand what the user wants.”