What is data profiling in ETL testing, and why is it important?

Data profiling in ETL testing refers to the process of analyzing data to understand its structure, content, relationships, and quality characteristics. It involves examining data patterns, distributions, and anomalies to identify issues such as missing values, outliers, duplicates, or inconsistencies. Data profiling helps testers and developers gain insights into the data and assess its suitability for the ETL process. It is important because it helps identify potential data quality issues early in the ETL lifecycle, enabling organizations to improve data accuracy, integrity, and reliability.