One of the most frequent questions asked in IronEdge Group’s training courses is how we learned Microsoft Power BI. Our trainers all took different learning paths, but we assembled a list of beginner resources to share. We hope this series can be helpful for folks hoping to learn Power BI skills. Future posts will focus on intermediate resources and niche advanced topics.
First, when choosing learning materials how do you learn best? Videos, books, online documentation, or a combination of all three? We’ve selected free or affordable examples of all types. These resources should get you beyond the beginner level across all major Power BI topics. To help you and your coworkers become Power BI pros, we recommend your organization book IronEdge Group’s virtual or in-person training courses.
- Previously we recommended the edX course Analyzing and Visualizing Data with Power BI, however, much of the content is likely dated given the course was produced in 2017-2018. Instead we recommend using Microsoft’s Power BI Guided Learning which has some of the videos from the aforementioned course but is continuously updated to utilize current Power BI features.
- No one knows Power BI like Alberto Ferrari and Marco Russo. Their site SQLBI offers two free video courses: Introducing DAX and Introduction to Data Modeling. These topics are required to master Power BI.
- Easily digestible and updated frequently, Microsoft’s Guy in a Cube series is a great source for all skill levels. These experts have a playlist for beginners and hundreds of videos covering Power BI features, solutions, guides, and integrations with other products. Their videos are a great source for Power BI continuing education.
- Collie, Singh: Power Pivot and Power BI: The Excel User’s Guide to DAX, Power Query, Power BI & Power Pivot in Excel 2010-2016 (Amazon)
Yes, that’s right, an Excel book. Did you know DAX and Power Query were Excel tools long before Power BI existed? All the book’s explanations, tips, and exercises can be replicated in Power BI. The author explains how DAX formulas work, not just what they do.
- Allington, Matt: Learn to Write DAX: A practical guide to learning Power Pivot for Excel and Power BI (Amazon)
Another book featuring Excel and a great companion book to Collie’s. This book is easy to read and does deep dives into DAX functions. You will benefit from reading it cover to cover, but you can also use it as a resource to look up a function and learn more about it.
- Puls, Escobar: M Is for (Data) Monkey: A Guide to the M Language in Excel Power Query (Amazon)
Before you write DAX, you need to load the data! The first 2/3 of the book focus on loading data and data transformations In Power Query, while the final third are more advanced examples of M (the Power Query language) syntax and how to best utilize it.
You may have noticed all three books feature Excel heavily. While there are introductory Power BI books, we believe these books’ content are valuable enough to stand the test of time.
Documentation, Blogs, and other Web Resources:
- Back to SQLBI; their blog is a great source for DAX deep dives along with general Power BI tips for keeping your reports optimized and accurate.
- Matt Allington also has a great blog that covers the entire range of Power BI topics; data loading, data modeling, DAX deep dives, and solutions to complex problems.
- DAX guides: DAX is often critiqued as easy to learn, but hard to implement. We’d recommend SQLBI’s DAX Patterns and DAX Guide for learning more about DAX syntax and how to combine DAX functions to achieve your goals.
- Finally, we recommended Microsoft’s Power BI Guided Learning earlier, but please note the recently overhauled site also contains loads of documentation about various product aspects.
We hope this list assists you on your learning journey. Stay tuned for our next post in this series which will focus on intermediate resources for DAX, Power Query, and report design.
Interested in a hands on training experience? Check out our Power BI courses and find the perfect package for you and your team here.