Coforge's Data Cosmos Data Migration Tool

The Data Migration Tool from Coforge is an end-to-end automated accelerator for enterprise database schema and data migration across on-premises and cloud platforms on Azure. Part of the Coforge Data Cosmos Supernova portfolio, it eliminates the manual, error-prone processes that plague traditional migration projects by delivering intelligent auto-mapping, metadata-driven conversion, and visual validation.

Challenges Addressed: • Manual migration processes consuming weeks of engineering effort with high error rates • Inconsistent schema mappings leading to data loss, type mismatches, and broken downstream pipelines • Lack of visibility and governance — no audit trails, reconciliation gaps, and compliance risks

Core Capabilities: • Metadata Extraction – Automated discovery and extraction of source schemas, data types, constraints, indexes, and relationships for target platform preparation • Schema & Data Migration – Automated conversion supporting full-load strategies across heterogeneous platforms with type mapping, constraint preservation, and DDL generation • Intelligent Data Mapping – AI-assisted auto-mapping of source-to-target fields with user review, edit, and approval capabilities for governance compliance • Visibility & Governance – Real-time dashboards, success/error summaries, and audit-ready reconciliation reports for complete migration traceability

Supported Platforms: Oracle, Azure Synapse Analytics, PostgreSQL, Microsoft Fabric, Greenplum, Azure Data Lake Storage Gen2, and Snowflake with universal on-premises and cloud compatibility.

Quantified Impact: • ~50% efficiency boost in migration speed vs. manual approaches • ~60% error reduction through automated mapping and validation • ~30% scalability improvement for complex, large-scale datasets

Industry Examples: • BFS – Core banking database migration from Oracle to Azure Synapse for BCBS 239 regulatory modernization • Insurance – Policy administration data migration from Oracle to Snowflake on Azure for unified underwriting analytics • Travel – Reservation system migration from legacy databases to Azure for real-time booking analytics • Healthcare – EMR data migration from on-premises to HIPAA-compliant Azure Data Lake

The 6-week implementation covers: assessment & source profiling, metadata extraction, schema conversion, data mapping configuration, migration execution, validation & reconciliation, and knowledge transfer.

Target Audience: Data Engineers, Cloud Migration Architects, Database Administrators, and Platform Teams.