Why Data Quality Matters for AI-Driven Insights

In today’s data-driven world, the accuracy of AI insights depends on the quality of your data. Reliable, well-structured data builds trust, supports business processes, and enables informed decision-making.
A robust data platform is key to maintaining consistency and accuracy. By integrating Microsoft Purview Data Quality, organizations can assess and monitor data quality with ease. This solution offers no-code/low-code rules, including out-of-the-box and AI-generated options, plus AI-powered profiling that recommends columns for review and allows human refinement for better accuracy.
During this session, you’ll learn how to implement the Data Quality Life Cycle:

Assign steward permissions in the data catalogue
Register and scan sources in Purview Data Map
Configure connections for quality checks
Run profiling and apply rules

Join us to discover how Purview and Fabric together deliver seamless governance and high-quality, AI-ready data.

Implement the Data Quality Life Cycle in Purview Apply DQ rules Leverage AI-Powered Profiling for Continuous Improvement