Data quality is the foundation of analytics we can trust. But what does “quality” actually mean? How do we know our reports are telling the truth, both now and in the future? How can we catch bad data before it reaches our customers? What principles from assembly line manufacturing can we apply to our data pipelines?

In this session, we’ll walk through building a robust data quality program in Microsoft Fabric. You’ll learn:

- The dimensions of data quality, and how to apply them in your context
- How to define & implement quality checks across multiple Fabric workloads
- How to apply the native capabilities of Fabric and Delta Lake
- Use of open‑source frameworks like Great Expectations and Soda Core to upgrade our workflows

By the end, you’ll understand how to design and implement an end‑to‑end data quality process in Fabric, from ingestion all the way to the Power BI reports your business relies on.