Reader reviews

Disappointing. The description oversold what is actually inside.

I read this over a couple of weekends alongside a small side project, which turned out to be the ideal way to approach it. The chapters on data visualization are the strongest — the examples are stripped down but complete, and I could follow along without constant guessing. The writing is direct and does not waste space on filler, which I value in a technical book. A few of the examples could be more realistic, but the underlying points come across clearly. Two stars. The subject deserves a better treatment than this.

Better than I expected. Rare to find a technical book this well judged.

I bought this on a whim after seeing it mentioned in a forum thread, and I am glad I did. It is denser than the page count suggests, and I found myself slowing down around the middle. Some of the material is available elsewhere, but rarely presented this clearly. The progression from chapter to chapter is well thought out; nothing feels out of order. One of those books that pays for itself within the first few chapters. Highly recommended.

I have read a lot of books on this subject and this is the clearest.

I bought this on a whim after seeing it mentioned in a forum thread, and I am glad I did. A couple of chapters felt like they could have been merged, but that is a minor complaint. The author avoids over-explaining, which keeps the pace up but means you need to pay attention. If you have the prerequisites, this is an easy recommendation. I will be keeping it on my desk rather than the shelf.

Decent, but uneven. Some chapters are much stronger than others.

A colleague recommended this and I can see why. It does something that few technical books manage: it respects the reader's time. The author is unusually honest about where the simplifications break down, which I appreciated. Some of the material is available elsewhere, but rarely presented this clearly. I particularly liked the way the author builds up from simple cases before introducing the harder material. Fine, but there are stronger books on the same subject if you look around.

Very good, with a few caveats. The core material is strong.

A colleague recommended this and I can see why. It does something that few technical books manage: it respects the reader's time. I appreciated the honesty about what the book does not cover — it saved me from expecting things that were not there. The writing is direct and does not waste space on filler, which I value in a technical book. Some of the diagrams are dense and I had to reread a few sections, though that may just be me. Worth picking up if you already have the basics. Set realistic expectations and you will get a lot out of it.

Finally, a book that treats databases & big data with the care it deserves.

I bought this on a whim after seeing it mentioned in a forum thread, and I am glad I did. Some of the material is available elsewhere, but rarely presented this clearly. The explanations are careful without being condescending, which is a difficult balance to strike. The chapters on databases & big data are the strongest — the examples are stripped down but complete, and I could follow along without constant guessing. One of those books that pays for itself within the first few chapters. Highly recommended.