Discussions

One of the coolest parts about data driven testing is how flexible it is with different data sources. Instead of hardcoding values into your test cases, you can feed them directly from external files like spreadsheets, CSVs, or even live databases. This not only saves time but also makes your tests a lot more reusable.

Let’s start with spreadsheets (like Excel). Many QA teams love them because they’re easy to update and don’t require technical know-how. You can create rows of input values and expected outputs, and your automation framework will simply loop through them. This makes it really simple for non-technical stakeholders to contribute test cases as well.

CSVs are another favorite—lightweight, easy to parse, and perfect for automation. Most programming languages and testing frameworks support CSV imports natively, which means you can plug them right into your test scripts without much hassle. They’re also great when you want to keep things version-controlled in Git.

Databases, though, take it to the next level. Pulling test data directly from a database lets you test against real-world conditions and ensures consistency. It’s especially useful when your application relies heavily on dynamic data. That said, the challenge lies in maintaining test isolation—you don’t want your tests messing with production data!

The trick is finding the right balance between these sources based on your project needs. Some teams even mix them: spreadsheets for high-level test management, CSVs for automation pipelines, and databases for integration scenarios.

Tools like Keploy make this process even smoother by automatically generating test cases and mocks from real traffic, reducing the manual effort of preparing data. Combined with data driven testing, this helps you catch more issues while keeping your tests reliable and maintainable.