Implementing Data Quality in Microsoft Fabric with Microsoft Purview

Over the past few days, I’ve had the chance to delve into the new data quality features of Microsoft Fabric and Microsoft Purview. I’m eager to share my experiences in this blog post.

For those who might not be aware, Microsoft Purview has recently undergone a significant update, introducing a host of new features that greatly improve the data governance experience for business users. For more detailed information on these updates, consider reading this informative blog post.

A major highlight of this updated version is the new Data Quality feature. This is a crucial component in all business environments, as bad data quality can negatively impact business operations and the decision-making processes.

Microsoft Purview addresses data quality by providing users with a no-code/low-code system to evaluate data quality. This includes both out-of-the-box rules and AI-generated rules. This new feature is applicable across most regions and supports services such as Azure Data Lake Storage (ADLS Gen2), Azure SQL Database, and Fabric Lakehouse (delta table).

Data Quality within Microsoft Fabric

It’s important to note that Microsoft Fabric is a relatively recent addition to the Microsoft portfolio. As such, integrating it with Microsoft Purview and establishing data quality includes several steps. This process requires attention. The rest of this blog…