Is quality going down the drain with the pipeline?" Without data, the digital transformation enabled by CI/CD pipelines is meaningless. Organizations are implementing pipelines only to have challenges with quality, validation, and performance. Why? The data for design, engineering, and delivery is lacking.
There must be a deliberate strategy, process, and tool chest for creating and managing SDLC data. Techniques like data profiling, synthetic data generation, and self-service dataset reservation improve the pipeline and can be automated. Historic approaches like masking production data are both risky and fall short.
Topics will include
•Identify types of data needed across the SDLC
•Explore data profiling, synthetic generation, and overall test data management (TDM)
•Understand approaches to automating TDM
•Tying TDM into the DevOps pipeline
Attendees will be exposed to test data management and how it ties into DevOps/ continuous engineering and walk away armed to discuss technical challenge areas and a few inherent people/cultural implications.