Case Study Summary
Bitwise helped a large, US retail company successfully migrate their Data Integration (ETL) platform from a leading expensive ETL tool to Informatica. The first and primary step in this migration was to complete the inventory analysis and then scope the exact ETL jobs to be migrated. The approach included a collaborative effort with client teams
and the STIMA utility (an automated assessment tool put together by Bitwise), which helped in laying the Bitwise ETL Converter:
- Complexity definition of each ETL job
- Identification of common features across all the ETL jobs
The Bitwise ETL Converter enables the automation of the migration process, thereby minimizing the time-to-production and brings in better quality within the new ETL Platform. Its support for various ETL Tools and easy customization, based on the client’s needs, enables it to lead the market in offering a dynamic and complete conversion toolset.
A NYSE listed, $109 Billion company, making it one of the world’s largest retailers focusing on “customer-first” strategy and providing state-of-the-art solutions in order to serve consumer needs.
The client had to move their entire ETL Platform from a leading expensive ETL tool to Informatica, covering the following aspects:
- Development of the Informatica mappings after analyzing the original ETL tool Initio graphs
- Unit testing, which involved the field level comparison of a leading expensive ETL tool outputs against Informatica
- System integration and performance testing
- Deployment to stage environment followed by the production environment
All of the above aspects had to be covered for about 1500 graphs spread across 40 subject areas within the fixed timeline to avoid expensive ETL tool license renewal. The graphs were of varied complexity with 58% graphs in the Medium-to-Complex category.
Bitwise ETL Converter service provided by Bitwise enabled the client to reduce time-to-market and save on licensing costs. The Bitwise conversion solution helped in identifying the scope accurately and optimizing the migration process with the help of features provided by this accelerator, listed below:
- Automated assessment of hidden data elements that can be retired if no longer in use
- Phased migration approach
- Consistency and standardization across the data conversion jobs
- Automated data validation