Testing is a crucial stage in the software development life cycle. If set up properly, it can speed up the development process dramatically by increasing efficiency and automation, and most importantly it can drastically increase the number of detected defects before pushing new code into production. Undetected defects can lead to unexpected behaviour and seriously damage the customer experience.
Data plays a key role in testing, so how can we obtain data that adjusts to each situation? The optimal choice for testing provides a combination of flexibility and ease of use while still maintaining scalability, privacy and complete coverage.
In this guide, we introduce you to the fast-growing concept of data products (Data as a Product). Practitioners can apply product techniques to data and get access to high-quality, fully-compliant and large volumes of test data on demand with the same schemas, data types and statistical properties as the production data.
We deep dive into our all-in-one DataOps platform enabling intelligent test data and collaboration across internal teams and external partners. We explore the platform’s capabilities and its advantages in comparison with traditional approaches of data-driven testing.