Test data management is a crucial practice for enterprise quality assurance teams, as it provides the test datasets needed for various environments. However, traditional solutions for TDM can be complex, time-consuming, and expensive, making them inadequate for modern DevOps teams. These teams require a solution that can automatically deliver datasets in minutes, which is API-based so it integrates easily into CI/CD pipelines.
Legacy TDM solutions involve a ticket request-based process for data preparation, anonymization, delivery, and refreshes. This centralized and manual process makes it difficult for teams that aspire to increase delivery velocity and adopt automated CI/CD and DevOps frameworks. The process also requires a lengthy data preparation, including mapping datasets to test requirements, searching for relevant entity objects, applying subsetting algorithms, identifying sensitive data fields, and applying anonymization while maintaining referential integrity. This process is time-consuming, complex, DBA and SME-centric, storage-intensive, fragile, and expensive.
In contrast, modern TDM solutions offer a practical way to copy the entire production database, allowing for faster delivery and greater flexibility in refreshing test datasets. They also provide self-service delivery, reducing the dependency on central teams and offering test data masking for added data privacy. These solutions can integrate easily into CI/CD pipelines and offer a lower storage footprint and cost.
Ultimately, modern TDM solutions offer a more efficient and effective approach to managing test data, supporting the needs of modern DevOps teams and helping to increase delivery velocity.
Learn more on how modern TDM works in this whitepaper: Accelario | Reinventing TDM for DevOps