A US-based Fortune 100 property and casualty insurance company was suffering from sub-optimal ETL testing which, in turn, was leading to increased operational data storage costs, compromised data quality, and inadequate test data security and privacy. The company was also clocking unusually high time spans for test data preparation by QA and DEV teams, which was adversely affecting release cycles.
Trianz not only optimized the company’s ETL testing to enhance its product quality, but also decreased operational data storage costs while improving test data security and privacy. It also ensured that time spent by QA and DEV teams on test data preparation was reduced, which eventually improved release cycles.
THE BUSINESS CHALLENGE
The organization was facing challenges like high operational data storage costs, compromised data quality, and inadequate test data security and privacy due to sub-optimal ETL testing.
- Informatica ILM Tool
- Analyzed test data requirements, existing systems, and table relationships
- Imported all the driving tables into ILM workbench
- Designed 20 masking rules to mask secured columns
- Created 97 and 44 tables entity for the two identified subjects | Moved data into test environment based on two months’ data as subset criteria
- Ran ETL code on top of subset data created in test environment and identified valid defects
- Built ready-to-use test data to reduce Dev team’s deployment time (approximately four cycles down)
- Enabled defect detection in early stages of lifecycle due to qualified test data
- Implemented TDM best practices to create realistic, referential intact and secure test data without impacting business information
- Improved test coverage by enabling production like data in DEV and test environments for testing all valid business scenarios
- Solution is currently deployed in multiple projects for the client, and is being leveraged successfully for executing projects
- Trianz is equipped with in-house capability -- with TDM experts -- for providing ongoing support