01
Context
A multi-site healthcare organization relied on SQL Server for analytics and needed to transition to Snowflake as part of a broader modernization effort. The change affected reporting workflows, integrations, scheduled jobs, user access, archival needs, and operational processes.
The work had to move the platform forward without treating cutover as a purely technical event. Reporting continuity, validation, and a defined path back were central to the plan.
02
What I led
I led analytics planning for the migration, including dependency mapping, workload coordination, access planning, job transitions, reporting continuity, archival considerations, rollback readiness, stakeholder coordination, and final analytics approval of the cutover.
The role required translating across business and technical groups so that operational needs were represented in the transition plan.
03
Approach
- Map dependencies. Identify analytics workloads, downstream reporting, scheduled jobs, integrations, and access requirements.
- Plan the transition. Sequence job changes, access controls, archival steps, validation work, and stakeholder responsibilities.
- Prepare for uncertainty. Define checkpoints and a rollback path before the production cutover.
- Coordinate the cutover. Keep business, analytics, engineering, and operational participants aligned through the transition.
- Verify before retiring the prior platform. Confirm the new environment was stable and reporting needs were met.
04
Outcome
The modernization reduced data lag by 14 hours and moved the analytics environment toward a more scalable cloud platform. It also established a stronger foundation for future reporting and analytics work while keeping continuity, validation, and operational risk visible throughout the transition.
Related optimization work reduced selected Power BI semantic model sizes by up to 30 percent by moving appropriate transformation work into Snowflake and removing unnecessary model content.