I’m going to start by saying I really enjoyed this book. I’ve worked with data for nearly 20 years but there’s always something new, interesting and energising to learn.
However, my bugbear is creating a bubble for data geeks, data nerds and big data consultants. Insights are for everyone and data is one resource we can tap into for that. I am always on the lookout for books that help non-techies understand techie concepts and most importantly, what’s in it for them. This book falls squarely into that plain English, no bull approach.
Meta S. Brown aims this book squarely at domain experts – people who already have the know how that comes from working daily in their chosen fields. She then goes on to demonstrate how they can benefit from one method of manipulating data for insight: data mining.
I won’t pretend this book is perfect – it’s not. I understand some of the decisions, for example to focus on visual tools over text based ones. This is a minor niggle. The rest of the books covers in a good balance between succinctness and detail the *methodology* and *approach* to data mining.
This is key. With this grounding, the learning curve to pick up using a specific tool is reduced. And you’ll need to invest in that because that’s where this book fails to deliver. However, I’m pretty sure it would have been twice the size had Meta attempted to correct this, so as I mentioned, a minor niggle.
Bottom line: should you read this and what’s in it for you?
TLDR; Yes you should. Especially if you already do data jiggery pokery using spreadsheets, have that essential domain knowledge and want to up your game.
Even if you’re an expert data zen master, you’ll benefit from comparing Meta’s experiences, methodology and approach based on CRISP-DM to your own. A little practice-based analysis is a good thing.