Point the accelerator at your BW system. It maps every flow from DataSource to query, converts standard BW patterns with the built-in rules of the Intellus framework, uses AI to translate custom ABAP into Python or SQL notebooks, and generates bronze, silver and gold pipelines with a star schema in gold. On Azure, AWS or GCP, with the ingestion route you choose.
Moving BW to Databricks is mostly translation. Hundreds of transformations, start and end routines, master-data lookups and delta rules all have to arrive as working code. Done by hand, each routine is opened, understood and rewritten one at a time, and the lineage back to BW gets lost along the way.
Every DataSource, ADSO and transformation rebuilt by hand in Spark: reading ABAP routines line by line, re-deriving delta logic, and designing the gold model from scratch while the BW reports keep running.
The BW landscape is mapped automatically, standard objects are converted by framework rules, custom routines arrive as reviewed notebooks, and bronze, silver and gold land in one consistent structure. Data engineers spend their time on validating results and on the routines that need real judgement.
Predictable by design: because the bulk of a BW landscape follows standard patterns, most objects go through framework rules instead of AI. That keeps results repeatable across runs and environments, and keeps AI cost limited to the routines that genuinely need it.
Lineage first: the BW dependency tree is the backbone of the migration. Only flows that are actually used come along, and each Databricks object can be traced back to its BW source for reconciliation.
The cloud and the ingestion route are choices you make per project. The generated Databricks layers stay the same on every path. Pick a combination to see the route.
Each BW object's metadata and code is read and its Databricks equivalent built inside the framework. Standard patterns go through framework rules, the same way every time. Custom ABAP goes through AI and is reviewed. Anything that needs a human decision is flagged, never guessed.
Reads metadata over RFC and maps the dependency tree from DataSource through transformations and ADSOs to CompositeProviders and queries. Unused objects stay behind.
Standard transformations go through framework rules, with no AI. Custom ABAP routines are translated by AI into Python or SQL notebooks, each kept next to its source routine for review.
The framework builds bronze ingestion, silver conformed tables and a gold star schema: facts at the grain of your ADSOs, dimensions from your InfoObjects.
Jobs and pipelines deployed to Databricks on Azure, AWS or GCP, wired to the ingestion route you chose and registered in Unity Catalog.
A demo takes 30 minutes. Bring your own BW flows.