Large-Scale Data Migration to Azure

I specialize in executing complex data migration projects to Azure, ensuring seamless and efficient transitions for businesses. Below is an outline of the process and key components of a successful migration project:

Data Sources

Ingestion

Storage

Testing

Data Sources:

The migration involved over 5 billion records from structured CSV files, ensuring data consistency and completeness. Each file was meticulously processed to guarantee accuracy and reliability.

Ingestion:

For the ingestion process, a robust workflow consisting of over 150 automated steps was implemented, each equipped with detailed logging for traceability and troubleshooting. This ensured a transparent and fail-safe migration pipeline.

Transformation:

Advanced automation techniques were used to generate SSIS packages through BIML (Business Intelligence Markup Language) deployed on Azure Data Factory. This approach significantly reduced manual effort and enhanced the accuracy of data transformations.

Storage:

Migrated data was securely stored in Azure Data Lake, optimized for scalability and high-performance processing. Structured datasets were transitioned to Azure SQL Databases, ensuring their readiness for further analysis and reporting.

Testing and Validation:

To ensure data integrity, over 150 unit tests were designed and executed, verifying the accuracy and completeness of every data migration step.