Many large businesses have organically grown their SAP estate and the Datawarehouse over a long period. Support packs and upgrades have been applied. SAP BW was migrated to HANA inmemory DB; a portion of the estate was migrated to the cloud; more and more solutions were built.

But did you optimise your development principles for your Datawarehouse in the mean time? Or is there still significant legacy, with as a consequence slow, non-agile development; higher data footprint and higher run & maintain costs?

Our SAP Datawarehouse health check service has been created to assess if your DW analytics platform approach has adopted modern, agile principles including but not limited to:

• Ingestion mechanism, i.e. extractors vs SLT, SDI replication vs virtualization
• 1+ persistence principle (persist once for corporate memory, then virtualize rest or at best the calculated business logic only)
• A logic grouping framework for artefacts (developers to follow)
• Data tiering adoption (aged / column store data can be place in warm/cold)
• Design principles/guidelines