SAP and Databricks expand AI capabilities in SAP Business Data Cloud
SAP and Databricks announced an expanded partnership that plans to bring Genie, Lakeflow, Unity Gateway and Lakebase to SAP Databricks within SAP Business Data Cloud. The companies also plan a bidirectional Genie-Joule integration, while SAP Application Data Foundation makes SAP application data available without custom extraction pipelines. SAP Databricks and SAP Business Data Cloud Connect for Databricks are available, but no release dates were provided for the announced additions or the planned integration.
The expansion would bring governed SAP data and Databricks AI tools together for enterprise analytics and AI, while SAP Application Data Foundation is intended to reduce custom extraction work. The planned Genie-Joule integration could bring Genie’s answers and actions into SAP experiences.
Today's AI models are more capable than ever. What they still lack is the business context to understand how your company actually runs. For most enterprises, that context lives in SAP systems. Over 90% of Fortune 500 companies use SAP solutions to manage key business processes, enhance operational efficiency, and gain a competitive edge through data-driven decision-making.
Last year, SAP and Databricks introduced SAP Databricks, which natively embedded the Databricks Data + AI Platform in SAP Business Data Cloud (SAP BDC). Since general availability, customers including Adidas, Zalando, Mondi, and CAF have used SAP Databricks and SAP BDC Connect for Databricks to analyze, govern, and build AI on live, semantically rich SAP Data Products through zero-copy, bi-directional OpenSharing.
This week at SAP TechEd, we are announcing the next phase of our partnership. Now, we’re bringing together the expanded scope of Databricks to SAP Databricks in SAP Business Data Cloud. This makes it much easier and more performant to work with SAP enterprise data, allowing customers to realize AI value from their data.
Customers want to put their data to work: forecasting demand from years of order history, detecting anomalies in the financial close, optimizing procurement decisions, and grounding AI agents in how the business actually runs. Accessing SAP application data has been possible, but it has typically meant building and maintaining custom extraction pipelines that copy data, lose business context along the way, and fragment governance.
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