SAP Databricks: Unlocking the SAP data treasure trove for AI and analytics

SAP systems form the backbone of many large companies - around 77% of the global transaction volume today touches an SAP system. Over the years, valuable business data from finance, supply chain, HR and sales has been collected there. In times of artificial intelligence (AI) and advanced analytics, this treasure trove of data is turning into gold: it provides context-rich, business-critical information that makes modern AI models really powerful. In short: those who activate their SAP data for AI and analytics gain a decisive competitive advantage.

At the same time, the importance of data-driven applications is growing rapidly. Whether predictive analyses, personalized customer approach or automated decisions - without the integration of operational SAP data into modern analysis platforms, a lot of potential remains untapped. Traditionally, however, it has been difficult to leverage the value of this data beyond SAP boundaries. In the next section, we look at the traditional hurdles.

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Solution: SAP Databricks - seamless integration in the Business Data Cloud

This is precisely where the partnership between SAP and Databricks comes in. SAP Databricks is embedded in the SAP Business Data Cloud (BDC ) as a native Databricks service managed by SAP and is available on all major cloud platforms (Azure, AWS, GCP). This gives companies a uniform environment in which they can analyze their SAP data together with all other data sources and refine it with AI - without time-consuming in-house integration or permanent data replication.

Important: The SAP business context is retained in full. All SAP data appears as data products with complete semantics. This allows AI and analytics applications to be built directly on trustworthy business data.

Technical advantages at a glance

• Zero-copy data sharing
  Delta Sharing provides SAP data bidirectionally, without physical copies. Changes can be used immediately for analysis, results can flow back into SAP. No expensive ETL pipelines, always live data.
• End-to-end ML functionality
  Spark, SQL, Notebooks and MLflow are available directly in the BDC. From data engineering to model deployment, everything runs on one platform.
• Real-time analytics
  Databricks SQL and streaming capabilities enable ad-hoc queries and dashboards in seconds - ideal for demand forecasting or supply chain monitoring.
• Context-rich database
  SAP data is provided as curated data products; terms, structures and relationships remain intact. No need for time-consuming metadata maintenance.
• Consistent governance
  SAP authorizations and Unity Catalog interlock. Security and compliance remain consistent - even with mixed SAP and non-SAP data.

Business benefits

• Faster, more informed decisions
  Real-time data from SAP and external sources flow together; decisions are based on current facts instead of outdated reports.
• Higher data quality
  A single, curated truth prevents errors caused by manual merging.
• AI readiness
  Data science teams start projects without lengthy data preparation and bring models directly into the business processes.
• Lower costs, higher ROI
  Elimination of redundant copies and simplified architecture significantly reduce storage and integration costs.
• Future-proof flexibility
  Open, cloud-based architecture for IoT, partner or log data. Scalable from proof-of-concept to company-wide lakehouse.

Conclusion

SAP Databricks removes the hurdles of ETL marathons, silos and loss of context. Companies receive a modern, federated data architecture in which SAP transactions and AI applications work together harmoniously. Those who activate their SAP data now transform isolated information into actionable knowledge - and create the basis for innovation, efficiency and sustainable business success.

The technical means are ready - now it's time to actively shape the change to data-driven decision-making. Let us check how we can activate your SAP data with the help of Databricks in a non-binding initial appointment.