Copy of my review from GoodReads.

This is a good "data manual" for managers and business owners. I would even advise recruiters to read it. There is a very good chapter about the different types of data roles, and another one about forming and recruiting for a data team. My recruiter would love it, because it is clear, actionable, and accessible for someone who is not in IT or data.

Simon Asplen-Taylor, PhD and data veteran, explains the role of data in business, the different types of data-related roles (data analyst, data engineer, Chief Data Officer etc.). The book also provides a wealth of information about leveraging data (+ a special chapter about AI), data insights, and what to expect from a data team.

<b>Some things I like</b>
The data periodic table. It is the type of document that would be very useful if you want to communicate a data strategy to the CFO! I never heard about it before, and frankly, it is brilliant.

The chapter about data risk management and ethics is also very useful and well-written. It explains why we need to care about ethics when we store, share and process data. I worked on GDPR compliance when it was first implemented (even gave a couple conference talks on that topic). It was a big shock to the engineering community back then! Many companies and organizations, including large ones, had never thought about how their data could be used if it fell in the wrong hands. GDPR, despite its annoying aspects (who loves regulation with big fines?) brought up a real ethics conversation in the data realm. Compliance is not a curse, it is an opportunity.

The visuals! I love visuals, schemas, anything that helps a visual thinker understand complex things. There are many visuals in the book, but not so many that it turns into a collection of schemas. They are well-done, clear, professional (all of them could be printed, put next to a desk, and would be appropriate even in corporte offices).

<b>What was missing IMHO</b>
FAIR data principles. They are the next big thing. Easy to understand, easy to teach, and surprisingly profund. I would have liked them to be referenced in the book. Or did I miss it?

A chapter about data infrastructure and storage would also be useful.
Way too many businesses end up spending a fortune storing their data. As soon as you start collecting and storing a significant amount of data, you need to talk to IT infrastructure.
It can save a lot of money, protect your data from the most common data loss, and help you with your data inventory as well.

<b>Why not 5 stars?</b>
Because this book is not life changing or absolutely brilliant *for me*.
It is good. I would advise some of my colleagues to buy it. Actually, I am considering buying it for myself, as a useful reference of data concepts (and also something my colleagues could borrow).
But I am not new to data. A lot of the content of this book was hammerred into me when I was studying computer science (and that was nearly 20 years ago). I heard the rest during the many conversations I ended up having with different types of data people. So... I was already spoiled in that area. This is a rather entry-level book.

<b>Long story short</b>
Simon Asplen-Taylor did a really good job here.
The book was also impeccably edited. No tangents, all the examples are relevant, the visuals are great. From the table of contents, you already know what you are signing up for.
A wide audience could benefit from this book.

Thank you #NetGalley, Simon Asplen-Taylor and Kogan Page for the ARC.

Written by a highly qualified writer, this is a great book for data-driven, evidence-based business and marketing.
The insights about AI and machine learning are timely.
The chapters on teams and 'repeat and learn' were especially handy.
Asplen-Taylor goes into detailed insights on many topics such as ethics, growing businesses, automation and leadership.
The case studies, information presented in tables, and the resources consulted make this book very rich in its quality and the author's experience is evident throughout.