What Is ETL Testing? Master Data Validation and Accuracy

Here is a neutral, objective, and interesting summary of the text: ETL (Extract, Transform, Load) testing is crucial for businesses as it ensures that data extracted from various sources is accurate, complete, and actionable, safeguarding decision-making and future-proofing data operations. The stakes are high, with poor data quality costing organizations an average of $12.9 million annually. ETL testing goes beyond database testing, focusing on the entire data integration process to verify source-to-target mapping, validate transformations, and guarantee data integrity. By catching inconsistencies and errors early, businesses can avoid costly missteps and ensure operational continuity, cost savings, and improved analytics accuracy. The article provides a step-by-step guide to ETL testing, best practices, and types of ETL testing, as well as strategies for tackling challenges like complex transformations, evolving data sources, and scaling requirements.