A multinational retail and food service holding company, running its business analytics on Teradata, had reached the limits of what that setup could support. Scalability issues, slow query speeds, and the growing complexity of managing complex data analytics tasks were making it harder to keep pace with rising workloads and resource demands. The company wanted a smooth transition of data to the cloud, one that didn’t compromise on secure transfer, minimal downtime, data integrity, resource optimization, and strong access controls through automated translation. It also wanted to shift from Teradata to Microsoft Azure specifically to enhance business analytics performance, reliability, and scalability, but doing that meant navigating a genuinely complex migration: converting schemas, scripts, and ETL processes without losing a step. The client needed an automated approach that could expedite the migration process without expanding the risk that usually comes with a move this size.
Ascendion delivered a comprehensive data modernization solution encompassing every facet from inception to execution, built around a meticulously crafted migration strategy for schema, coupled with an equally meticulous ETL process design.
Ascendion’s team harnessed the DS Migrate Process Converter solution to orchestrate the seamless conversion of Teradata DDL, BTEQ scripts, and Korn shell scripts into their Synapse counterparts, Synapse DDL, Synapse Stored Procedures, and Azure Data Factory pipelines. This engagement was pivotal in orchestrating the intricate conversion of ETL processes and navigating the landscape of migrating complex scripts at scale.
Tech Stack:
Delivered 50% faster time to market with an extreme automation approach that enhanced business velocity.
Achieved up to 60% cost-effectiveness, as the platform provides a significant reduction of manual effort through configurable, automated, and self-service capabilities.
Delivered a 60% reduction in TCO, with engineering and support teams assured through packaged services for customer success.
Increased tech engineers' productivity, as the platform comes with an in-built modern data platform's best practices and guidelines to optimize performance.
