Beautiful Data

Author: Toby Segaran & Jeff Hammerbacher
Publisher: O'Reilly, 2009
Pages: 480
ISBN: 978-0596157111
Print: 0596157118
Kindle: B002L4EXGA
Aimed at: Those with an interest in data presentation
Rating: 3

Pros: Lots of varied content
Cons: Little of it either inspiring or essential
Reviewed by: Mike James

This is a very mixed bag and how you react to it depends on what you think a book called “Beautiful Data” might be all about. Given the subtitle of “The Stories Behind Elegant Data” you might expect that its focus would be on data structures or perhaps elegant database design. If so you would be disappointed because most of the book is about data visualisation or some other strange aspect of interacting with data.

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If you are interested in data presentation then some of the stories will be worth reading – however none of them make it into the category of generalisable techniques. As a result the main reason for reading this book is for fun or to gain some insight into how a fairly random group of people tackled a fairly random group of projects.

We have something about using GPS data to allow people to log what they are doing and see their effect on the environment. Then something about data collection which proposes the obvious truism that customisable forms are better. Then some thing very technical – embedded image data processing on Mars – great fun but how many of us are going to have the chance to design anything like it. Then we tackle cloud storage, encounter an essay on the role of the “data scientist”, together with chapters about presenting geographic data, indexing form data, capturing real time movement, visualising urban data, interactive visualisation, data and statistics, natural language exemplar data, DNA, data cleaning, data mining the web, presenting housing data, presenting political data and how the semantic web/AI can break down data silos….

As promised the book is a considerable random walk through the less technical aspects of data. If you are new to any of the topics then you might find the comments useful, but if you know your stuff you will probably find the level on the low side. Either the authors are not expert enough to present us with an overview or they are expert enough and try to present an overview in too few pages.

The irony is that for a book on beautiful data it is also spoiled by poor print quality, including in the the colour plates bound into the middle. Beautiful data should at least be presented beautifully. The bottom line is that this isn’t an inspiring book and it isn’t an essential book – it has some entertaining chapters but they suit a magazine format rather better than a book.

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Deep Learning (No Starch Press)

Author: Andrew Glassner
Publisher: No Starch Press
Date: July 2021
Pages: 750
ISBN: 978-1718500723
Print: 1718500726
Kindle: ‎ B085BVWXNS
Audience: Developers interested in deep learning
Rating: Mike James
Reviewer: 5
A book on deep learning wtihout an equation in sight?



Math for Programmers (Manning)

Author: Paul Orland
Publisher: Manning Publications
Date: January 2021
Pages: 688
ISBN: 978-1617295355
Print: 1617295353
Audience: Python developers interested in math
Rating: 4
Reviewer: Mike James
Of course you need to learn math, don't you?


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Last Updated ( Saturday, 28 April 2018 )