AI-Based Data Migration — ETL Optimization
Client
A large health insurance provider serving several million members across multiple states.
Challenge
- Manual source-to-target mapping was labor-intensive and error-prone at scale.
- Long migration timelines inflated project costs and delayed delivery.
- Inconsistent, hand-written SQL created performance bottlenecks.
- A high risk of data-quality and mapping errors threatened downstream analytics and reporting.
Solution: Sanciti AI – ETL Migration Optimization
Leveraged Sanciti AI for automated source-to-target mapping and ETL script generation, eliminating manual effort.
Results
- Reduced ETL migration cost and overall timeline
- Improved performance via optimized SQL query generation
- Eliminated manual mapping errors at scale
Impact
- Faster, lower-cost migration that accelerates time-to-value for downstream analytics.
- Higher data quality and reliability, increasing trust in reporting and decisions.
