It’s time for another short post on the free books that various authors have been kind enough to send me over the last few months. Full disclosure: these aren’t reviews as such, they’re more like free publicity in return for the free books, and I don’t pretend to be unbiased; also the Amazon UK links have a affiliate code in that gives me a kickback if you buy any of these books.
Deciphering Data Architectures, James Serra
I’ll be honest, I’ve had this book hanging around in my inbox since February and I wasn’t sure what to expect of it, but when I finally got round to reading it I enjoyed it a lot and found it very useful. If you’re looking for clear, concise explanations of all of the jargon and methodologies that are in use in the data industry today then this is the book for you. Do you want to understand the difference between Kimball and Inmon? Get an honest overview of data mesh? Choose between a data lake and a relational data warehouse? It’s all here and more. It’s an opinionated book (which I appreciate) and quite funny in places too. Definitely a book for every junior BI consultant to read and for more senior people to have handy to fill in gaps in their knowledge.
Extending Power BI with Python and R (second edition), Luca Zavarella
I posted about the first edition of this book back in 2021; this new edition has several new chapters about optimising R and Python settings, using Intel’s Math Kernel library for performance and addressing integration challenges. As before this is all fascinating stuff that no-one else in the Power BI world is talking about. I feel like a future third edition covering what will be possible with Power BI and Python in Fabric in 2-3 years will be really cool.
Data Cleaning with Power BI, Gus Frazer
It’s always nice to see authors focusing on a business problem – in this case data cleaning – rather than a technology. If you’re looking for an introductory book on Power Query this certainly does the job but the real value here is the way it looks at how to clean data for Power BI using all of the functionality in Power BI, not just Power Query, as well as tools like Power Automate. It’s also good at telling you what you should be doing with these tools and why. Extra credit is awarded for including a chapter that covers Azure OpenAI and Copilot in Dataflows Gen2.
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Hi Chris,
What books on data/Power BI/CS overall, from the last couple of years have blown you away ? I mean not just limited to these reviews but overall. In the past I always had a backlog of at least a few tech books with stellar reviews, but once these were done, I found myself struggling finding the next excellent read.
A few examples for what I mean are Designing Data Intensive Applications by Kleppmann, Marco and Alberto’s book on DAX, Itzik Ben Gan’s on SQL, Python Distilled by David Beazley or Ramalho’s Fluent Python. There is plenty to read on ML and AI, but on data the past few years seem very lacking.
Most of the recent books on data, modeling, architectures, etc. feel like dry compendiums of concepts or rehashed info from documentation and blogs (in most cases not even authors’ blogs) that add little to no value to the scene, and were written mostly for profit.
I’m waiting for Marco and Alberto’s Optimizing DAX and I just started Delta Lake Up and Running which looks promising so far.
Honestly, I can’t think of any genuinely life-changing data books that I’ve read recently. I guess that’s because the market moves so quickly that there is no time to get the knowledge and experience needed to write an in-depth book before everything changes. Also, no-one makes money from writing books – they make money from the reputational enhancement that having written a book brings. Of course there are always some people who write great books because they have something worth sharing but it also means a lot of other books get written for the wrong reasons. Certain publishers (naming no names) have built a business model around this.