SAP BW Migration Demo: From Metadata to Snowflake in Minutes
Stop migrating everything. Start migrating what matters — automatically.
Migrating an SAP BW to Snowflake, Databricks, or SAP BDC is a major platform shift. Without the right approach, you risk carrying over years of ungoverned data, unused queries, and legacy code — driving up cloud costs without delivering new value. In this live tool demonstration from the Data Innovation Summit 2026, One Data shows a smarter path.
Transparency first.
The demo begins with the One Data Data Map — a visual representation of an entire SAP BW system extracted at the metadata level. Every data object, from data sources to composite providers to queries, is visible and searchable. By switching to relevance and criticality layers, teams can instantly see what’s actively used and business-critical versus what can be safely decommissioned. In many cases, large portions of the query layer turn out to be unused — objects that never need to be migrated at all.
Business-aligned design.
From the Data Map, the workflow moves into the Use Case Canvas — a collaborative environment where data engineers and business stakeholders define which use cases to migrate first. Supporting assets and full upstream data lineage are attached automatically, giving teams a complete picture of the current state before designing the target structure.
AI-powered target generation.
With a single click, One Data’s AI agents generate a target structure for Snowflake based on the selected SAP BW objects. Names can be automatically adjusted for the new environment, and the AI takes functional requirements, coding standards, and metadata into account. The result: a fully designed target use case, ready for deployment.
Automated code-conversion.
The final step translates the ABAP transformation code behind each SAP BW object into SQL scripts — in this case, Snowflake macros — automatically. An AI log explains each decision and transformation in real time, giving full transparency into what was generated and why.
The result:
What used to take months of manual analysis and coding is compressed into a transparent, AI-assisted workflow — saving up to 80% of migration effort and cost.