20% SLA improvement by modernizing Teradata workloads on Azure

A global enterprise technology provider for banking, retail, and hospitality industries wanted to move their Teradata workloads to Microsoft Azure for reducing maintenance costs and enhancing scalability and agility. In addition, they were looking to resolve the mismatch in the metadata definition of their enterprise data warehouse and enterprise data lake. To address this, they wanted to leverage a modern data processing engine that would deliver analytics faster.

The Impetus team partnered with the enterprise technology provider to help them migrate one of the most complex finance applications on the modern data platform. The team leveraged automated Workload Transformation Solution to auto-migrate 1860 BTEQ scripts along with ~5000 SQLs and 64 TB data from Teradata to Azure in four steps – assessment and prescription, transformation, validation, and execution.

One of the requirements was to execute the transformed workloads within 6 hours, for which the Impetus team:

• Optimized code by breaking bigger sequential scripts/jobs into parallel executable scripts to meet business SLAs



• Used a single Spark session to execute all the scripts of a specific job to reduce overall execution time
• Recommended target cluster sizing for the production environment

The Impetus Workload Transformation Solution was also used to:

• Migrate code to Apache PySpark programs and executed the code on modern data platforms (Hadoop and Azure)



• Create a mapping sheet to map columns between enterprise data lake and data warehouse for resolving the metadata mismatch
• Automate unit testing for data and logic migration
• Perform cell-level validation to ensure matching data post migration and processing

• Achieved ~90% auto-transformation of Teradata BTEQ scripts
• Executed the migrated code in 5 hours, beating the targeted 6-hour SLA
• Saved 50% cost compared to manual transformation
• Ensured zero business disruption

The Impetus Workload Transformation Solution helped the enterprise technology provider rapidly transform workloads from Teradata to Azure. The solution simplified and accelerated the transformation process with speed, reliability, and minimal coding, while ensuring business as usual.