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SAP Datasphere adds data governance, GenAI for analytics

SAP introduced new functionality in SAP Datasphere to help customers better manage their data environments with governance, modeling and GenAI.

SAP is bringing new capabilities into its SAP Datasphere platform that are intended to solve data quality and access issues for organizations.

New capabilities, introduced today at the SAP Data Unleashed virtual event, add data modeling, data governance and generative AI (GenAI) to the Datasphere platform, launched last year as a cloud service for enterprises to manage and use data from sources across the organization in a single environment. Datasphere is built on SAP Business Technology Platform (BTP) for development and integration and is available as part of BTP's cloud services.

One of the top priorities for organizations today is implementing a holistic data and analytics strategy. But this is also one of the top challenges, said Juergen Mueller, SAP chief technology officer at the SAP Data Unleashed event.

"Now is the time to put the right data architecture in place that will enable you to manage big data sets without data redundancy, gain valuable insights and make intelligent decisions at scale without rebuilding the semantics you already have in your SAP system," Mueller said.

To address these data challenges amid the movement toward more enterprise GenAI adoption, SAP is introducing the following Datasphere capabilities:

  • SAP Datasphere Knowledge Graph, which lets organizations model data across all systems, including business semantic information. This knits together relationships between data, metadata and business processes. Doing so can uncover patterns and hidden insights in the data and provide context for GenAI applications.
  • Analytics and planning features from SAP Analytics Cloud (SAC), an SaaS BI tool, which will include SAP's Joule GenAI assistant to help users create dashboards or planning models.
  • A "compass" capability within SAC to help run simulations that can take in thousands of variables in a self-guided chatbot experience. For example, organizations can use the compass functionality to examine predictions for business scenarios and continually adjust controllable variables to find the optimal plan.
  • Expansion of the partnership with data governance vendor Collibra to build data catalogues that keep tabs on data inventory, provenance and overall quality as well as who created the data.

The new capabilities are in private preview for select customers now.

An open data ecosystem

SAP took the right path by emphasizing an open data ecosystem and semantic layer above all sources with Datasphere, said Doug Henschen, an analyst at Constellation Research.

SAP's partner systems, including Collibra, Databricks, Google BigQuery and Snowflake, have become integrated in a customer's Datasphere. SAP is now using contextual understanding of its applications and customer business objectives to power vector search, the Knowledge Graph and GenAI, Henschen said.

"SAP customers tell me that the fabric-style architecture of Datasphere gives them flexibility to access everything they need in the cloud without having to move or replicate data at great expense," he said.

SAP customers tell me that the fabric-style architecture of Datasphere gives them flexibility to access everything they need in the cloud without having to move or replicate data at great expense.
Doug HenschenAnalyst, Constellation Research

However, data quality is a separate integration and data-preparation issue, which SAP can address with its integration platform-as-a-service technologies such as BTP, Henschen said.

"SAP Datasphere is about data access, which enables organizations to harness all data within the enterprise," he said. "It also enables data marketplaces and the data mesh concept, wherein you enable distributed teams to make the most of their data and monetize it in new ways while also providing company-wide access and governance capabilities over all data within the enterprise."

It's important that SAP continues to lay the groundwork for quality data management and governance, said Joshua Greenbaum, principal at Enterprise Applications Consulting.

"This is because the problems with messy data and poor data management strategies are a plague that affect all aspects of business transformation and the use of enterprise data to drive advanced AI functionality," Greenbaum said.

Because of this, the new Datasphere features are quite timely. But SAP faces obstacles in its installed base due to the presence of competing products and strategies as well as the continued widespread existence of data silos and decentralized data management, he said.

"The nut of the problem is in change management as much as or more than a lack of good technology," Greenbaum said. "Fixing the latter without addressing the former will only make the technology look like it alone bears responsibility for these problems."

Jim O'Donnell is a senior news writer for TechTarget Editorial who covers ERP and other enterprise applications.

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