The Solution
Databricks on Azure was the client’s platform of choice for modernization, and Infocepts supported the transition with our Flash Databricks Migrate.
Infocepts’ approach started with designing a robust blueprint built on Medallion Architecture, focusing on centralized job cluster configurations and built-in fault tolerance. This architecture ensured resilience and high performance, especially during high-volume processing periods like the holiday season. The migration also involved rewiring MicroStrategy reports to pull data from the new Databricks platform, replacing the legacy Teradata source.
Infocepts followed a structured, four-phase approach:
Blueprint Definition: We developed an architecture blueprint, reviewed policies, and established governance frameworks to ensure compliance and scalability.
Detailed Design and Planning: The team mapped data transformation rules, defined orchestration strategies, and outlined the migration scope. We also prioritized data validation, preparing test cases for historical and incremental data.
Execution and Migration: Infocepts utilized its Flash Migrate toolkit to streamline and expedite key migration tasks, significantly enhancing efficiency.
- Automated polling, provisioning, and data loading reduced development time by 40%.
- The toolkit auto-generated 300 tables and 700 views while converting legacy SQL to Databricks-compatible formats seamlessly.
- Historical data was efficiently transferred from Teradata to Databricks using our toolkit’s automated data transfer utility.
- Our automated validator compared data across Teradata and Databricks tables and compared over 1,500 MicroStrategy reports before and after migration, promptly identifying and resolving any discrepancies.
Infocepts worked closely with the retailer’s IT team to ensure seamless integration with DevOps pipelines and real-time monitoring.
Rollout and Adoption: Following rigorous testing, Infocepts provided support through user acceptance testing (UAT) and post-go-live monitoring to ensure the system met performance and operational expectations.