01 / Inside the engagement
Situation
A major-version upgrade of the enterprise data-virtualization layer: more than two thousand views consumed by business reporting, where a single silent change in results would reach decision-makers before anyone noticed.
Before
- Original data views
- Major-version upgrade
- Report consumers
After
- Old and new view outputs
- Python comparison
- Validated release
Simplified workflow. The case text describes the contribution, delivery stage and evidence.
Explore the full conceptual diagram
02 / Inside the engagement
What UTIS did
- Designed and led a Python regression-automation framework: automated old-versus-new output comparison, row-level and aggregate reconciliation, discrepancy detection and root cause.
- Added Splunk audit dashboards and metadata monitoring, and an automated monthly utilization report that replaced a manual one.
- A second UTIS engineer now carries the platform, its SAP BusinessObjects reporting estate and a new access-management foundation.
03 / Inside the engagement
Results
- 2,000+ views validated automatically; migration defects caught before production; go-live green.
- The engagement extended into AI-assisted engineering follow-on work.
Why it matters to you
An upgrade is successful only if every report still means what it meant before. Comparing old and new results at row and aggregate level is the check that catches the silent differences a technical smoke test never will.
Stack
How we measured it: automated comparison results at go-live.