Power BI Book Recommendations

@BrianJ Great book that too :slight_smile:, any other books you would recommend?.

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Yeah, that one (The Definitive Guide to DAX, Second Edition) is the absolute bible. A must have IMO for anyone doing Power BI work.

Power BI books are tricky, since the program is updated so frequently that anything other than general reference books go out of date so quickly as to be largely useless.

Here are the ones on my shelf that I find have stood up as valuable over time, other than the Definitive Guide to DAX:

DAX Patterns, Russo and Ferrari - great companion to the Definitive Guide. They’re supposed to come out with a new edition sometime this year, but until then you can get a used copy of the current edition for under 10 bucks.

Collect, Combine and Transform Data Using Power Query in Excel and Power BI, Gil Raviv - IMO best book available on Power Query

M Is for Data Monkey, Puls and Escobar - another very good PQ resource. I believe they’re doing an updated edition this year. (Note: they include the e-book version of this for free with their online Power Academy Training, which is excellent)

Pro DAX with Power BI, Phil Seamark - not absolutely essential IMO if you have the Russo and Ferrari books, but some interesting concepts in this one and I really like the way he explains things.

Would be very interested to hear from others if there are good ones that I’ve missed on this list.

  • Brian

Way back when, I also bought “Microsoft Excel 2013 Building Data Models with PowerPivot”. - Pre PowerBI. But still refer back to it. Remember using Excel 2010 and downloading the PowerPivot add in…


Two that I would add to the list are not Power BI-specific, but are both great resources for developing quality data visualizations:

The Visual Display of Quantitative Information, Edward Tufte - an absolute classic. All of Tufte’s books are worth having on your shelf.

#MakeoverMonday, Kriebel and Murray - a great exploration of the individual components that make for effective visual presentation. The authors are Tableau experts, but the book is platform-agnostic, and highly relevant for Power BI users.

  • Brian

@BrianJ, not heard of those ones. Have read Storytelling With Data though.
Definitely an art to presenting data and to communicate the results effectively and easily.

So many books, so little time…

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I think the book thread (starting at post #3) is worth separating into its own thread and re-titling (something like “Power BI Book Recommendations”), so that members can add to it over time, and find it more easily in search.


  • Brian


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

For someone who is starting off these are 2 great books -= practical examples with hands on practice.

  1. Learn to Write DAX: A Practical Guide to Learning Power Pivot for Excel and Power BI - Book by Matt Allington

  2. Power Pivot and Power BI: The Excel User’s Guide to DAX, Power Query, Power BI & Power Pivot in Excel 2010-2016 Second Edition, Second edition Rob Collins and Avi Singh



Great call on the Allington book. I forget about those because I made the mistake of buying them on Kindle rather than hard copy, the latter of which works way better for me as a reference. There is also a second book in the series:

Supercharge Power BI: Power BI Is Better When You Learn to Write DAX by Matt Allington.

I found this one really helpful as I was working through @sam.mckay’s videos, since their style and way of explaining things, as well as the types of examples they use are very compatible.

  • Brian
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First time ever bought a book related to power BI i.e. The definitive Guide to DAX 2nd edition. I have always relied on online learning now will see how the book will make a difference in DAX concepts.

I agree with @C9411010 and use this book the most

Power Pivot and Power BI: The Excel User’s Guide to DAX, Power Query, Power BI & Power Pivot in Excel 2010-2016 Second Edition, Second edition Rob Collins and Avi Singh

I have most of the other books listed but it seems that Rob & Avi make things seem simpler when I’m trying to do things.



FYI - SQLBI recently released the 2nd edition of DAX Patterns. I ordered the hard copy version and have been going through it since last Friday. IMO, it’s not an essential addition to your library (especially since they completely overhauled the daxpatterns.com website and put all the content up there for free), but it’s really well done and a big improvement (in terms of expanded content and readability) over the 1st edition. Some interesting new patterns worth taking a look at, including like-for-like, transition matrix and some expanded content on hierarchies.

  • Brian
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I am from a financial background and want to get certification in machine learning. Right now looking to get some basics to start with on my own. What are the good online resources to start with?

Thanks for the recommendations in advance.


I haven’t taken it, but have heard great things about this course offered online for free by Stanford Univ:

  • Brian
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Thanks @BrianJ. Will try the course and will update on the forum about it.

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Here’s my take on all the various books out there, most of which I decided I needed at the time, but that has since changed. I think where you are on your journey is important to be aware of. If you are just starting out jumping in the Definitive Guide to DAX can be overwhelming, least in my view.

Just starting out:

  1. Power Pivot and Power BI: The Excel User’s Guide to DAX, Power Query, Power BI & Power Pivot in Excel 2010-2016 by Rob Collie. He does a great job of introducing you to the world of DAX without getting into the thick of it. May be a little outdated now, but the topics and theories are still applicable.

  2. M Is for (Data) Monkey: A Guide to the M Language in Excel Power Query by Ken Pus and Miguel Escobar. Written in the same fashion as #1 (less formal, more conversational) it provides someone just starting out a good starting point

  3. Power Query for Power BI and Excel by Chris Webb. Goes a little deeper that #2 above, but still relatively painless.

After getting through those I would then venture into more technical books:

  1. Definitive Guide to DAX, The: Business intelligence for Microsoft Power BI, SQL Server Analysis Services, and Excel by the SQLBI. Pretty much the bible of DAX. Anything and everything is included.

  2. The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd Edition The Definitive Guide to Dimensional Modeling by Ralph Kimball. While not PowerBI specific, this book is a tremendous help on how to set up a correct dimensional data model, of which DAX is optimized for.

  3. Analyzing Data with Power BI and Power Pivot for Excel by the SQLBI. Specific to Data Modeling, though I think having the knowledge from #2 above would be greatly beneficial, which is why I put it before this book

  4. Collect, Combine, and Transform Data Using Power Query in Excel and Power BI by Gil Raviv. Excellent book on PowerQuery and M.

Others books:

  1. DAX Patterns: Second Edition by SQLBI.

  2. Power BI MVP Book: A book of tricks and techniques for working with Power BI Has some interesting things in it, but I wouldn’t buy it again

  3. Pro Power BI Architecture: Sharing, Security, and Deployment Options for Microsoft Power BI Solutions by Reza Rad. My version was riddled with spelling errors/pages missing and generally just hard to follow. Wouldnt buy this again knowing what I know now

  4. Pro DAX with Power BI: Business Intelligence with PowerPivot and SQL Server Analysis Services Tabular by Phillip Seamark and Thomas Martens. Different way of looking at a lot of the same topics in other books. But sometimes that is helpful.

With all that being said, I got the most out of Sam’s course. I think it comes down to what type of learner you are. For me, I am visual so while reading it can help actually getting into helped alot more. Things can seem way to easy just reading in a book that you can start to think “oh, yeah, I can do that” till you are faced with a blank PBI file and have to go to work.


A few more recommendations to add to the list:

I’ve gotten a lot of questions recently from folks who want to start incorporating statistical analysis using R into their Power BI reports. I am in the process of putting together a detailed list of R resources. However, before jumping into R, it’s critical to have a sound understanding of fundamental statistical concepts, including population vs. sample, data distributions, hypothesis testing, choosing the right test statistic, p values and interpreting results, parametric vs. nonparametric statistics, etc.

For developing this foundational knowledge for those without a statistics background, I am a huge fan of statistician and writer Jim Frost (https://statisticsbyjim.com/), who is able to convey these concepts in clear, plain English in a very readable style with lots of examples for the non-statistician. He currently has written three books, all of which I very highly recommend. The third one is available currently only as an e-book, but the hard copy for those of you like me who prefer to go old-school for your reference library is expected out later this month. I think anyone who worked their way through all three books would have a great foundation on which to incorporate sound statistical analysis into your reports.

Introduction to Statistics: An Intuitive Guide for Analyzing Data and Unlocking Discoveries, Jim Frost, August 2020.
Hypothesis Testing: An Intuitive Guide for Making Data Driven Decisions Paperback , Jim Frost, September 2020
Regression Analysis: An Intuitive Guide for Using and Interpreting Linear Models, Jim Frost, October 2020

Also, a couple of things about @Nick_M’s recommendation of The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd Edition by Ralph Kimball. On a recent, excellent interview on the SSBI Podcast, Marco Russo was asked what he thought the essential books for Power BI users were (other than his own). This book was the first one on his list.

However, the new 3rd edition is really expensive ($57 for hard copy). What I found though is that there are now tons of used copies of the 2nd edition available. The key concepts of dimensional modeling haven’t changed much over the years, so I went for a very good condition used copy of the 2nd edition for $6 plus shipping and saved myself almost $50 bucks.

  • Brian

This is exactly what I had been looking for to build good foundations in Statistics. Yes, you are right, it is important to have good understanding of statistical analysis before jumping into R language.
I had always felt that I am in the wrong field and had always wanted to be in Data Sciences plus Graphics Designing.
I guess it’s never too late to start doing what you really love.
Thanks a lot for the learning resources :+1:

I also recently picked up
Star Schema The Complete Reference 1st Edition by [Christopher Adamson]

I think it was like $25 or so at amazon and for purposes of PBI and such, is a great resource. If you have to chose, I would go with this book over an older Kimball book. But dont think you can go wrong either way.



Thanks for the recommendation. I’m curious – how much actually changed between the second and third editions of the Kimball book?

  • Brian