Originally published at norvik.tech Introduction Explore the critical signs indicating your data quality framework is failing. Understand the impact on tech development and how to address it. Understanding Data Quality Frameworks and Their Importance A data quality framework is essential for organizations that rely on accurate data for decision-making. It consists of processes, standards, and tools designed to ensure that the data used is accurate, complete, and timely. The importance of such frameworks cannot be overstated; according to industry estimates, poor data quality can cost organizations up to $15 million annually in lost revenue and productivity. Organizations must recognize that having a framework in place is not enough; it needs to be effective and regularly evaluated. [INTERNAL:data-quality-framework|Understanding the Basics] Key Components of a Data Quality Framework Data Profiling : Analyzing existing data sources to assess their quality and identify issues.…