What is data quality?

This is a podcast episode titled, What is data quality?. The summary for this episode is: <p>This episode of <em>Techsplainers</em> explores data quality—the measure of how well datasets meet criteria for accuracy, completeness, validity, consistency, uniqueness, timeliness, and fitness for purpose. We examine the seven key dimensions of data quality and explain how they impact business decisions, processes, and customer satisfaction. The discussion highlights the critical distinction between data quality, data integrity, and data profiling, while explaining why poor quality data costs organizations an average of USD 12.9 million annually (according to Gartner research). We also explore the growing importance of data quality for AI and machine learning systems, where the "garbage in, garbage out" principle directly affects outcomes. Whether you're in marketing, supply chain management, or healthcare, understanding data quality fundamentals is essential for making reliable, data-driven decisions.&nbsp;</p><p>&nbsp;</p><p>Find more information at&nbsp;https://www.ibm.biz/techsplainers-podcast</p><p><br></p><p><strong>Narrated by Mimi Sun Longo&nbsp;</strong></p>