Your team redesigned the database. The SSIS package that connects it to everything else still points at the old schema.
Sage Butte Energy's reserves, forecasting, and economics workflows all ran through a single Access database synced to Field Insights Lite through an SSIS package. The team had already built the new database schema. What they needed was the integration work: update the SSIS package, test every downstream connection, and cut over to production with zero unplanned downtime.
Does this describe your migration?
- You have a new database schema ready, but the SSIS packages still reference the old field definitions
- Downstream reports and tools connect through ODBC, and you are not sure which ones will break
- There is no documented rollback plan if the cutover fails during business hours
- Reserves, forecasting, or economics workflows depend on a data sync you cannot afford to interrupt
- Nobody has mapped exactly which data flows reference the fields that are changing
- The migration itself is done, but the integration layer is the part that breaks silently
What Armely did for Sage Butte Energy
Sage Butte Energy's CHP organization runs reserves, forecasting, and economics from one Master Aries Database in Access, synced to Field Insights Lite through SSIS. The team had redesigned and populated the new schema, but the SSIS package and downstream connections still pointed to the old one.
Armely mapped every data flow in the existing SSIS package before changing anything. The package was updated for the new schema, then tested through four days of regression testing in staging.
Armely also delivered a documented rollback plan, then cut over during a planned low-activity window with post-deployment support to confirm all downstream systems.
The result: 13 working days, fixed fee, and zero unplanned downtime. The Aries-to-FiLite sync now runs on the new schema. ODBC-connected economics and reporting tools read the new fields without errors.
At a glance
| Before | After |
|---|---|
| SSIS package built against the old schema, breaking on new field definitions | Updated SSIS package handles the new schema with automated data generation |
| No documentation of which data flows referenced the fields being changed | Full SSIS package analysis mapped every flow before any code changed |
| No rollback plan if the cutover failed during business hours | Documented rollback procedure delivered as a formal project deliverable |
| No staging validation before production deployment | Four days of regression testing in staging with a documented test report |
| Downstream ODBC connections for economics and reports were untested against the new schema | Post-deployment verification confirmed all ODBC-connected systems were operational |
| Cutover risk to reserves, forecasting, and economics workflows during business hours | Production cutover completed during a planned low-activity window with zero unplanned downtime |