You may have heard of Data is the new oil, a phrase coined by Clive Humby, a data scientist and mathematician.

In testing, data help yield value-creating insights. With an array of data, testers use a re-usable test logic that improves test coverage, 'Data Driven Testing'.

This week, let’s explore some effective reads on Data Driven Testing (DDT)!

A Detailed Guide To DDT
So what is data driven testing? If you need a complete breakdown into what it is and how you can implement it, here’s a complete resource for you!

Benefits Of DDT - Infographic
Make your benefits data-driven! Here's why!

Scenarios Data-Driven Testing Is Useful Explore some practical scenarios where data driven testing proves essential.

Things You Should Know About Test Data (And Why) A read to improve your overall understanding of test data and insights that will allow your teams to acquire the best test data possible.

The Test Data Bottleneck And How To Solve It
A lot of time is lost finding the right test data cases. Know how you can solve this test data bottleneck, read on.

Test Data Preparation Techniques With Example
What should you know about test data and the sauce behind creating best test data.

Reasons Why Test Data Management(TDM) Is Important Than You Think
Average data quality will provide mediocre results after testing, and no one ever wants that. Here's why test data management is important.

Highly Effective Strategies For Managing Test Data
Paul Merrill shares 3 basic patterns for managing test data more effectively.

Methods And Tools For Data-Driven API Testing
Here’s a recommendation for testers looking to advance their testing carrer to code a little in order to test their programs at the API level.

Data Driven VS Keyword Driven Frameworks For Test Automation
What circumstances would make these appropriate for an automated test suite?

Data Driven Testing With Testsigma
Here’s an article by the ArtOfTesting community as to how Testsigma performs data driven testing.

How To Measure When Enough Testing Is Done?
No testing is enough, but we can maximize the test coverage using multiple data-driven techniques discussed here.

Cast your vote!

Data validation can be quite repetitive and boring 🥱
How do you determine that enough testing has been done?
Drop your answer!

Combine automated tests with a data source to test faster and more accurately!

Hope you are finding our recommendations resourceful.

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With 💚,
Team Testsigma