Data Quality is a measure of how well data fulfills the expectations based on its intended usage in business operations, ensuring that data used for decision-making, reporting, and analysis is reliable and trustworthy. It is not a one-size-fits-all concept and evolves based on changing business contexts, requirements, and experiences. High-quality data is crucial for informed decision-making, operational efficiency, regulatory compliance, customer satisfaction, and gaining a competitive advantage. Data Quality can be measured across multiple dimensions including accuracy, completeness, consistency, integrity, uniqueness/deduplication, and validity. Master Data Management and Entity Resolution play critical roles in achieving high data quality by providing a single, trusted view of data and identifying linked records from disparate systems. Ensuring data quality involves a combination of people, processes, and technology through strategies such as data governance, profiling, cleansing, tools, audits, and activation.