How AI Agents Help Engineers Recover Hidden Logic in SAP-to-Cloud Migrations

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Migrating data from SAP to cloud platforms is technically straightforward, but preserving the business knowledge embedded in legacy systems — such as join logic, status mappings, and ownership — is far more complex. A synthetic case study involving over 5,000 SAP HANA calculation views, thousands of cloud tables, and parallel BI tools like Qlik and Spotfire illustrates the scale of this challenge. To address it, engineers have designed an Enterprise Data Discovery Assistant built on a bounded Snowflake Cortex Agent that queries four evidence layers: HANA repository code, BI artifacts, a reporting metadata catalog, and schema and lineage metadata. The assistant is read-only and does not modify source systems; instead, it surfaces recovered logic, ownership details, and dependencies to help engineers draft grounded SQL for validation. This approach reframes migration as an evidence-discovery problem rather than a pure code-conversion task.

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