Transitioning from legacy data collection systems/databases to a Test Data Management system requires careful forethought and analysis to minimize costs and reduce deployment time. At Customer sites large and small, our Evaluation Teams have identified hidden silos of data that are crucial to overall product quality, and have architected time and cost-efficient methods for extracting, transforming and loading that data into the dedicated test data management system. Leveraging their extensive test and enterprise software expertise, our teams interview stakeholders in Test, Supplier Quality, Contract Manufacturing Management, Operations, Information Technology, R&D and RMA/Field Quality in order to obtain a detailed picture of the factors for a customer’s overall product quality. Once we understand those factors, we can:
- Identify the data silos with highest ROI in quality improvement and yield improvement
- Identify the data silos with the easiest technical and process barriers for ETL
- Identify the analytics that have the highest impact in cost/labor savings
- Architect the data ETL process so that current and future data integrates seamlessly with other data and processes
- Map out product genealogies and life cycles
- Identify data silos that could be enriched (push-pull via API) with IntraStage data or vice-versa
The outcome of this Evaluation process is a formal document that clearly identifies customer needs, data silos, and a deployment plan (including a milestones and dependencies). By having this formal deployment document, our customers can proceed with integrating a test data management solution with minimal risk and a high ROI. Contact us to learn more about our consulting and gap analysis.