A data-driven testing approach is a method of functional testing where a series of test scripts are executed repeatedly with the use of data sources like Excel, CSV FILES, Spreadsheets, XML files, and SQL databases. Data sources like these are USED as inputs for generating output. Next, the output is compared to what was expected to verify the system or software. 

A data-driven approach is preferable because testers often have multiple data sets for a single test, and it can be time-consuming to create individual tests for each data set. By using data-driven testing, data and test scripts can be separated, and the same test script can be RUN for different combinations of input data, resulting in efficient testing results. 

Example: Let's assume we want to test the login system with 100 different data sets and multiple input fields. We can have the below three approaches: 

• Approach 1: Write 100 scripts, one for each DATASET, and run each test individually.  
• Approach 2: Change the value in the script manually and run it SEVERAL times.  
• Approach 3: Import Excel data and pull test data one by one from Excel rows, and then run the script.  

The first two scenarios listed are arduous and time-consuming. As a result, it would be best to utilize the third approach (data-driven testing).