Scenario: You are tasked with testing an ETL process that extracts customer data from multiple sources, transforms it, and loads it into a data warehouse. During testing, you discover that some data transformations are not working as expected, resulting in incorrect data being loaded into the warehouse. What type of ETL testing is needed to address this issue?

Data Quality Testing is required in this scenario to ensure that the data transformations are working correctly and that the data being loaded into the warehouse meets the expected quality standards. This involves validating data accuracy, completeness, consistency, and integrity throughout the ETL process. By performing comprehensive data quality tests, you can identify and rectify issues related to incorrect data transformations, ensuring the accuracy and reliability of the data in the data warehouse.