Before you begin the testing process, you need to define the right ETL Testing technique. It is important to ensure that the ETL test is performed USING the right technique and that all stakeholders agree to it. Testing team members should be familiar with this technique and the STEPS involved in testing. Below are some types of testing techniques that can be used: 

• Production Validation Testing: Also known as "production reconciliation" or "table balancing," it involves validating data in production systems and comparing it against the source data.
• Source to Target Count Testing: This ensures that the number of records loaded into the target is consistent with what is expected.
• Source to Target Data Testing: This entails ensuring no data is lost and truncated when loading data into the warehouse, and that the data values are accurate after transformation.
• Metadata Testing: The process of determining whether the source and target systems have the same schema, data types, lengths, indexes, constraints, etc.
• Performance Testing: Verifying that data loads into the data warehouse within predetermined timelines to ensure speed and scalability.
• Data Transformation Testing: This ensures that data transformations are completed according to various business rules and requirements.
• Data Quality Testing: This testing involves checking numbers, dates, nulls, precision, etc. Testing includes both Syntax Tests to report invalid CHARACTERS, INCORRECT upper/lower case order, etc., and Reference Tests to check if the data is properly formatted.
• Data Integration Testing: In this test, testers ensure the data from various sources have been properly incorporated into the target system, as well as verifying the threshold values.
• Report Testing: The test EXAMINES the data in a summary report, verifying the layout and functionality, and making calculations for subsequent analysis.