All,
Two more books I would add to the recommended list above:
DAX Cookbook by Greg Deckler - this is a newly published and fascinating book. It’s like DAX Patterns on steroids - over 120 different “recipes” including statistical, financial and time intelligence, as well as advanced DAX techniques such as unpivoting and transposing in DAX, using measures in situations where they are typically not allowed, and the most comprehensive strategy I’ve ever seen for debugging complex DAX. For each recipe, he has a section called “How it Works” that walks through step-by-step how/why the code provided works. If I were establishing a DAX library, I would buy Russo and Ferrari’s Definitive Guide to DAX 2nd ed. first and then this book second. Between the two, you really wouldn’t need much else.
R for Data Science by Hadley Wickham and Garrett Grolemund - If you’re interested in using R in conjunction with Power BI, this book is an excellent place to start. It goes through the basics of how to import, clean, transform, visualize and model data within R in a very clear and step-wise manner. However, it is NOT a statistics primer - it assumes you already have a solid grounding in statistics. In addition, this book assumes use of and adherence to a related group of R “packages” (add-on functionality) known as Tidyverse. Personally, I think using Tidyverse is the way to go - they are proven packages, and grouped together they make setting up R much less daunting to the new user. But not all R users agree, and so just beware that this book is very Tidyverse-centric.
Let’s keep this very useful thread alive. If you have any other recommendations, please continue to post them.
- Brian