Case Study: Johnson & Johnson achieves automated data quality and CI/CD testing with RightData

Johnson & Johnson eliminates custom code maintenance costs with RightData

Johnson & Johnson faced a challenge with the data quality process for its SAP and Primary Access Data Lake (PADL). Their PADL team had developed a custom Python-based testing framework that was expensive to maintain, difficult for the quality assurance team to use, and lacked automated orchestration. They needed a more efficient way to manage data quality within their DevOps pipeline.

The vendor, RightData, implemented its DataTrust solution to automate data quality assurance and control. This no-code platform integrated with J&J's existing systems like Jira and Control-M, providing an automated framework for releases and regression testing. The results eliminated custom code maintenance costs, provided a self-service tool with a minimal learning curve, and the project was approved by the enterprise architecture board as a model for future DataOps implementations. RightData's tool became a single platform for bulk data comparisons, profiling, and data integrity controls.

Johnson & Johnson