Databricks
Open lakehouse processing alongside governed SAP data for advanced analytics and AI.
What Databricks delivers
Databricks complements Datasphere and Business Data Cloud when you need open scale compute, data science and machine learning beside your SAP estate. The point is not to replace SAP semantics. It is to process at lakehouse scale without losing business meaning.
Notium designs the boundary clearly: what stays in Datasphere or BW as governed products, what is shared into Databricks, and how results flow back for planning, reporting and AI. Usage and ownership are written down so the two platforms do not become a second source of truth by accident.
Typical patterns include heavy transformation, ML feature work and open format analytics that still reconcile to the SAP models your finance and operations teams trust.
Key capabilities
Governed share from SAP
Work with SAP data products and semantics without stripping the business meaning on the way out.
Lakehouse scale
Process large volumes for analytics and machine learning on an open lakehouse architecture.
Joint architecture
Clear ownership between SAP and Databricks layers, with reconciliation paths back to trusted models.
AI and ML ready pipelines
Feature and training pipelines that sit beside, not against, your SAC and Datasphere estate.
Open formats, SAP context
Use open table formats and tooling while planning and reporting still read a governed SAP view.
Datasphere, BW/4HANA, Business Data Cloud and Databricks form the data layer your services run on.
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