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The Algebra of Data: A Foundation for the Data Economy, by Gary Sherman, Robin Bloor
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There has never been a universal algebra of data. Mathematics has been widely employed by software in many ways: numerical analysis, statistics, algorithms, mathematical modeling, and so on, but it has never been used to formally define data in all its variety.
This changed when mathematical research into data algebra—carried out for Algebraix Data Corporation by one of the authors of this book—matured and was tested in an extensive range of data management, data integration, and performance optimization contexts. The purpose of this book is to explain that data algebra.
The book is undeniably and unashamedly a mathematics text. However, realizing that the readership would likely include many software developers and users as well as mathematicians, the book is written to be as accessible as possible to anyone with some mathematical skills. As such, this is not your grandfather’s mathematics text. Between the various set theory assertions, expressions, and equations flows a narrative that is both surprising and entertaining.
The subtitle of the book, A Foundation for the Data Economy, is not hyperbole. The mathematical definition of data, and the various set theoretical operations and functions that can be applied to it, provide a new approach to data. It will, in time, become the natural foundation for the emerging data economy that is already growing swiftly.
- Sales Rank: #1232953 in Books
- Published on: 2015-08-09
- Original language: English
- Number of items: 1
- Dimensions: 9.02" h x .41" w x 5.98" l, .58 pounds
- Binding: Paperback
- 192 pages
About the Author
Gary Sherman's long history of studying (PhD - Indiana University, 1971), teaching (Professor Emeritus, Rose-Hulman Institute of Technology, 1971-2006) and doing mathematics (29 refereed publications and Principal Mathematician, Algebraix Data Corporation, 2008-2014) is distinguished by, well, a lack of jail-time.
Robin Bloor, once a software developer, has spent most of his professional life as a technology analyst and IT consultant. He is also a frequent blogger and published author. He has a degree in Mathematics from Nottingham University (UK), a PhD in Computer Science from Wolverhampton University (UK) and, like Professor Sherman, a surprising inexperience of the jailhouse.
Most helpful customer reviews
3 of 3 people found the following review helpful.
COULD NOT PUT IT DOWN
By John Graber
Perhaps I'm predisposed to enjoy this book, as the topic marries what I do for a living (data) with what I'd like to do for a living (mathematics). But regardless of my potential biases, I feel I MUST give it high marks!
Yes, you read the review headline correctly. For my part, this was a book I could not put down, which is admittedly an odd thing to say about a book on mathematics. But the writing style takes what easily could be a very dry topic and makes it both interesting and entertaining (without overdoing it the schtick you often see in tech manuals in my line of work, where authors try to hard to be funny).
Data algebra, as the authors put it, is applied set theory. And it appears to me that they have, indeed, created something of tremendous potential use and importance to data analytics.
The (necessary) introduction to set theory is very well (and gently) done. And each chapter builds upon the previous, clearly explaining the concepts being introduced. And what I found particularly helpful is that the WHY of things is constantly being addressed — why is this an interesting fact? why is it important to understand this particular point? why does this operator work in this case, but not the other? and so forth. And add to the that there are just enough examples to assist in grasping an idea that is being presented for the first time.
So, yes. A whole hearted 5 Star review! I look forward to a more in-depth text to follow this one. Which, if I understand correctly, is "in the works".
1 of 1 people found the following review helpful.
A true innovation
By Avid4IT
It is rare that something genuinely new comes along in the field of data science. I was skeptical when I saw the authors' claims that mathematics has never been used to formally define data in all its variety. However, I am convinced.
This is not an easy read for anyone who isn't comfortable in the world of algebra, but the authors are kind to the reader and make the journey as painless as possible. The writing style is elegant and there is just the right amount of humour. In fact I laughed out loud a number of times - which was an unexpected bonus. I never liked algebra at school, but I can now say I see the point - it is truly useful.
This book is informative, entertaining and possibly revolutionary. I recommend it.
1 of 1 people found the following review helpful.
Highly recommended reading.
By Amazon Customer
I was reading reviews of various books on relational databases when I stumbled upon this book. I could not put it down and read it in one stretch today. I'm absolutely not strong in mathematics when things get more abstract, and I couldn't follow some of the formulas. Nevertheless I think it is a text of extreme importance to anyone in the field of data (in any format, not only in databases). It may well prove to turn the entire way data is stored, processed, queried etc. in the entire field of IT on its head in the coming years. It can possibly also solve various problems with all current relational databases (such as nulls and the normalization process).
Highly recommended reading.
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