SQL Data Partners Podcast

Episode 286: Data Governance and Security In Microsoft Fabric

In this episode of the SQL Data Partners Podcast, host Carlos L. Chacón is joined by Kevin Feasel and Eugene Meidinger for a deep dive into data governance and security within Microsoft Fabric. As part of Season 8’s focus on Fabric, the trio explores how governance tools and practices are evolving with Microsoft’s platform, including the use of domains, Purview integration, and the challenges that arise from pricing and tool fragmentation. With their usual banter and insights, the hosts lay out foundational concepts around organizational data governance and highlight some key components Fabric offers out-of-the-box. They also candidly discuss gaps between marketing promises and real-world implementation—especially around documentation and administration. Whether you're building out your governance framework or trying to decipher where Purview fits in, this episode brings clarity and context with plenty of humor along the way. We hope you enjoyed this conversation on data governance and security in Microsoft Fabric. If you have questions or comments, please send them our way. We would love to answer your questions on a future episode. Leave us a comment and some love ❤️on LinkedIn, X, Facebook, or Instagram. The show notes for today's episode can be found at Episode 286: Data Governance and Security In Microsoft Fabric. Have fun on the SQL Trail!

Episode 285: Who Is Using Microsoft Fabric

Fabric personas were originally designed to break down the various functional roles within Microsoft Fabric—such as Power BI, Data Factory, Data Activator, Data Engineering, Data Science, Data Warehouse, and Real-time Analytics—into more manageable, bite-sized sections. The goal was to prevent users from feeling overwhelmed by the platform’s breadth. However, this feature has since been discontinued, as it did not effectively communicate the seamless integration between these roles. Still, the underlying concepts can be useful when thinking about how you might approach Fabric from a functional standpoint. Do you like the change on one large white canvas, or did personas have a use for you? Let us know in the comments below. We hope you enjoyed this conversation on personas in Microsoft Fabric. If you have questions or comments, please send them our way. We would love to answer your questions on a future episode. Leave us a comment and some love ❤️on LinkedIn, X, Facebook, or Instagram. The show notes for today's episode can be found at Episode 285: Who is Using Microsoft Fabric. Have fun on the SQL Trail!

Episode 284: The Four-Letter Word ETL - Data Movement

Once you have your data stored in OneLake, you'll be ready to start transforming it to improve it's usability, accuracy, and efficiency.    In this episode of the podcast, Belinda Allen takes us on a delightful journey through Data Flows, Power Query, Azure Data Factory (Pipelines), and discusses the merits of shortcuts. We also learn about a handy way to manually upload a table if you have some static data you need to update.  There are many tools and techniques that can be used for data ingestion and transformations. And while some of these options we discuss will be up to individual preference, there are pros and cons to each. One of the blessings and curses of Fabric is that there are many ways of achieving the same result, so what you choose may depend on the nature of the data you have and your goals, but might also be dictated by personal experience.  We hope you enjoyed this conversation with Belinda on ingesting and transforming data in Microsoft Fabric. If you have questions or comments, please send them our way. We would love to answer your questions on a future episode. Leave us a comment and some love ❤️on LinkedIn, X, Facebook, or Instagram. The show notes for today's episode can be found at Episode 284: The Four-Letter Word ETL - Data Movement. Have fun on the SQL Trail!

Episode 283: Data Lakehouse vs Data Warehouse vs My House

Microsoft Fabric offers two enterprise-scale, open-standard format workloads for data storage: Warehouse and Lakehouse. Which service should you choose? In this episode, we dive into the technical components of OneLake, along with some of the decisions you’ll be asked to make as you start to build out your data infrastructure. These are two good articles we mention in the podcast that could help inform your decision on the services to implement in your OneLake. Microsoft Fabric Decision Guide: Choose between Warehouse and Lakehouse - Microsoft Fabric | Microsoft Learn Lakehouse vs Data Warehouse vs Real-Time Analytics/KQL Database: Deep Dive into Use Cases, Differences, and Architecture Designs | Microsoft Fabric Blog | Microsoft Fabric We hope you enjoyed this conversation on the nuances of data storage within Microsoft OneLake! If you have questions or comments, please send them our way. We would love to answer your questions on a future episode. Leave us a comment and some love ❤️ on LinkedIn, X, Facebook, or Instagram. The show notes for today's episode can be found at Episode 283: Data Lakehouse vs Data Warehouse vs My House. Have fun on the SQL Trail!

Episode 282: OneLake - A Deep Dive

In Episode 281, we introduced Microsoft OneLake with a high-level overview. Now we're going deeper with a discussion on the Parquet format, why Microsoft went with the Delta Lake variation, and what Delta Lake format brings to the table (no pun intended). We'll also examine some "behind the scenes" aspects of file management, and why you'll still be using the GUI to create most of your objects. Onelake is Microsoft's solution to the demand for centralizing all data in one location, eliminating the need to transfer it across multiple systems. We expect this to play out further however, when we consider scenarios like data sovereignty, geographical data distribution, separation of subsidiary data, and even departmental budgets that may necessitate multiple instances of OneLake. We round out our OneLake deep dive with a conversation on the Direct Lake Mode option for importing data into Power BI and Eugene shares his perspective on why everyone may not be rushing to jump on the bandwagon just yet. We hope you enjoyed this deep dive into Microsoft OneLake! If you have questions or comments, please send them our way. We would love to answer your questions on a future episode. Leave us a comment and some love ❤️ on LinkedIn, X, Facebook, or Instagram. The show notes for today's episode can be found at Episode 282: OneLake - A Deep Dive. Have fun on the SQL Trail!