By Published On: December 12, 2025Categories:

Microsoft Purview: Data Catalog, Governance & Data Quality

This hands-on course shows how BI professionals use Microsoft Purview to build practical governance workflows for data cataloging, glossary management, lineage, and data quality across Power BI, Microsoft Fabric, Azure Lineage, and ADLS.

  • Build a complete Purview catalog from Azure Lineage, ADLS, Power BI, and Fabric assets
  • Create business glossary definitions and ownership for shared data language
  • Use lineage and quality checks to improve trust in BI and AI decisions

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Catalog

AI measure drafting

Lineage

Fabric query support

Quality

Validation framework

Catalog-first workflow

Business glossary in practice

Lineage for BI confidence

AI-ready governance

What Our Students Say

Trusted by learners who want practical BI outcomes, not AI hype.

Awesome jump-start for Copilot in Power BI. Loved the generating DAX part. Great Learning Experience!

– Vera

Florian is an excellent instructor. The examples and sample data give a hands-on experience. Not just AI buzz talk!

– Anthony

Learned a lot how to speed up my Power BI report development! Perfect course structure and pace. Totally recommended.

– Marc

Your 4-Step Purview Learning Journey

1. Discover Assets

Scan sources and build a searchable data catalog for your environment.

2. Define Meaning

Create glossary terms and ownership for consistent business language.

3. Trace Lineage

Understand where data comes from and how it flows into reports and models.

4. Govern Quality

Apply trust and quality checks so analytics and AI outputs are reliable.

In Short

This course teaches Microsoft Purview for practical data governance and trusted analytics. You will learn how to catalog data assets, create business glossary terms, understand lineage, apply data quality thinking, and connect governance work to Power BI, Microsoft Fabric, Azure SQL, and ADLS use cases.

Who This Is For

  • Data governance professionals and BI teams
  • Analytics leads and data owners
  • Power BI and Fabric practitioners
  • Anyone building trusted data foundations for AI

What You Will Learn

  • Build a complete Purview catalog by scanning Azure SQL, ADLS, Power BI, and Fabric sources.
  • Create and maintain a business glossary to align definitions and ownership across teams.
  • Explore end-to-end lineage to track movement from source to transformation to dashboards.
  • Apply data quality concepts, profiling, and trust checks for analytics readiness.
  • Integrate Purview governance thinking with Microsoft Fabric and Power BI workflows.
  • Use governed, high-quality data as a foundation for AI-ready analytics.

Purview Governance vs Traditional Spreadsheet Governance

Traditional Governance

Often manual, inconsistent, and difficult to scale. Definitions live in separate files, lineage is unclear, and trust depends on tribal knowledge.

Purview Governance

Centralized cataloging, glossary terms, ownership, lineage, and governance workflows that support trusted analytics and AI decisions at scale.

Governance Quality Checks

Microsoft Purview provides structure, but governance quality still depends on implementation discipline. Definitions, ownership, metadata consistency, and lineage validation need regular review to keep analytics trustworthy.

  • Are glossary terms aligned with business language?
  • Are data owners and stewards clearly assigned?
  • Is lineage complete for critical reporting datasets?
  • Are quality checks defined for high-impact data assets?
  • Can stakeholders trace report numbers back to trusted sources?

Course Curriculum

Understand core Purview concepts, governance goals, and where Purview fits in modern data platforms.

Learn scanning, metadata capture, asset discovery, and how to structure catalog content for usability.

Create glossary terms, assign stewardship, and standardize business definitions across teams.

Explore lineage to trace transformations and improve trust in downstream BI reporting.

Connect governance concepts with Fabric workloads and practical BI implementation patterns.

Apply quality thinking and governance controls to improve reliability for analytics and AI outputs.

About Your Instructor

Hi, I am Dr. Florian Detzel, a Business Intelligence professional, data governance expert, and Udemy instructor with a PhD in Information Systems. I specialize in Power BI, Microsoft Fabric, Microsoft Purview, data modeling, process mining, and practical governance for analytics and AI.

My goal is to teach modern BI and governance topics in a clear, practical, and accessible way so learners can apply the concepts in real projects.

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Frequently Asked Questions

Microsoft Purview is used for data governance, data cataloging, business glossary management, metadata visibility, lineage tracking, and data quality workflows across modern analytics environments.

No. Purview can support teams of different sizes. The course focuses on practical patterns that can be scaled from smaller BI teams to larger governance programs.

Yes. Purview governance concepts can be applied to Power BI and Fabric workflows to improve trust, visibility, and documentation across your analytics stack.

Basic Azure familiarity is helpful, but the course explains Purview concepts in a practical and accessible way for BI professionals.

AI systems need trusted and well-documented data. Purview helps you establish definitions, ownership, lineage, and quality controls before AI-driven decisions are made.

Ready To Build Trusted Analytics With Purview?

Start learning practical Microsoft Purview governance workflows for data catalog, lineage, and quality today.