Why Data Quality Matters for AI-Driven Insights
Proposed session for SQLBits 2026TL; DR
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.
Session Details
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.
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.
3 things you'll get out of this session
Implement the Data Quality Life Cycle in Purview
Apply DQ rules
Leverage AI-Powered Profiling for Continuous Improvement
Speakers
Erwin de Kreuk's other proposed sessions for 2026
Build Your AI Foundation with Fabric Metadata-driven Framework - 2026
Empowering Data Products and Data Agents through Data Mesh in Microsoft Fabric - 2026
From Insight to Oversight: Securing Power BI with Purview - 2026
Erwin de Kreuk's previous sessions
Managing access to data sources in your data estate with Microsoft Purview
One of the new applications within Microsoft Purview Governance Portal are Access Policies.
Access policies in Microsoft Purview allow you to manage access to different data systems across your entire data estate.
The big advantage of these policies is that you do not have to apply RBAC roles and you have an overview of all applied policies.
Are you a data consumer? Then the self-service access policy is an easy way to request access to data while browsing or searching for data.
Are you a data producer? Then access policies helps you to easily create and publish access to data sources
In this session, I will explain and show you how to create and publish policies and how to set up a self-service access workflow.
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