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Data and Reality: A Timeless Perspective on Perceiving and Managing Information in Our Imprecise World, 3rd Edition Third Edition

4.0 4.0 out of 5 stars 50 ratings

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Let's step back to the year 1978. Sony introduces hip portable music with the Walkman, Illinois Bell Company releases the first mobile phone, Space Invaders kicks off the video game craze, and William Kent writes Data and Reality. We have made amazing progress in the last four decades in terms of portable music, mobile communication, and entertainment, making devices such as the original Sony Walkman and suitcase-sized mobile phones museum pieces today. Yet remarkably, the book Data and Reality is just as relevant to the field of data management today as it was in 1978.

Data and Reality gracefully weaves the disciplines of psychology and philosophy with data management to create timeless takeaways on how we perceive and manage information. Although databases and related technology have come a long way since 1978, the process of eliciting business requirements and how we think about information remains constant. This book will provide valuable insights whether you are a 1970s data-processing expert or a modern-day business analyst, data modeler, database administrator, or data architect.

This third edition of Data and Reality differs substantially from the first and second editions. Data modeling thought leader Steve Hoberman has updated many of the original examples and references and added his commentary throughout the book, including key points at the end of each chapter.

The important takeaways in this book are rich with insight yet presented in a conversational writing style. Here are just a few of the issues this book tackles:

  • Has "business intelligence" replaced "artificial intelligence"?
  • Why is a map's geographic landscape analogous to a data model's information landscape?
  • Where do forward and reverse engineering fit in our thought process?
  • Why are we all becoming "data archeologists"?
  • What causes the communication chasm between the business professional and the information technology professional, and how can the logical data model bridge this gap?
  • Why do we invest in hardware and software to solve business problems before determining what the business problems are in the first place?
  • What is the difference between oneness, sameness, and categories?
  • Why does context play a role in every design decision?
  • Why do the more important attributes become entities or relationships?
  • Why do symbols speak louder than words?
  • What's the difference between a data modeler, a philosopher, and an artist?
  • Why is the 1975 dream of mapping all attributes still a dream today?
  • What influence does language have on our perception of reality?
  • Can we distinguish between naming and describing?

From Graeme Simsion's foreword:
While such fundamental issues remain unrecognized and unanswered, Data and Reality, with its lucid and compelling elucidation of the questions, needs to remain in print. I read the book as a database administrator in 1980, as a researcher in 2002, and just recently as the manuscript for the present edition. On each occasion I found something more, and on each occasion I considered it the most important book I had read on data modeling. It has been on my recommended reading list forever. The first chapter in particular should be mandatory reading for anyone involved in data modeling.

In publishing this new edition, Steve Hoberman has not only ensured that one of the key books in the data modeling canon remains in print, but has added his own comments and up-to-date examples, which are likely to be helpful to those who have come to data modeling more recently. Don't do any more data modeling work until you've read it.


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Editorial Reviews

Review

From Graeme Simsion's foreword:

While such fundamental issues remain unrecognized and unanswered, Data and Reality, with its lucid and compelling elucidation of the questions, needs to remain in print. I read the book as a database administrator in 1980, as a researcher in 2002, and just recently as the manuscript for the present edition. On each occasion I found something more, and on each occasion I considered it the most important book I had read on data modeling. It has been on my recommended reading list forever. The first chapter in particular should be mandatory reading for anyone involved in data modeling.

In publishing this new edition, Steve Hoberman has not only ensured that one of the key books in the data modeling canon remains in print, but has added his own comments and up-to-date examples, which are likely to be helpful to those who have come to data modeling more recently. Don't do any more data modeling work until you've read it.

About the Author

William Kent (1936-2005) was a renowned researcher in the field of data modeling. Author of Data and Reality, he wrote scores of papers and spoke at conferences worldwide, posing questions about database design and the management of information that remain unanswered today. Though he earned a bachelor's degree in chemical engineering and a master's in mathematics, he had no formal training in computer science. Kent worked at IBM and later at Hewlett-Packard Laboratories, where he helped develop prototype database systems. He also served on or chaired several international standards committees. Kent lived in New York City and later Menlo Park, Calif., before retiring to Moab, Utah, to pursue his passions of outdoor photography and protecting the environment.

Product details

  • Publisher ‏ : ‎ Technics Publications, LLC; Third edition (March 19, 2012)
  • Language ‏ : ‎ English
  • Paperback ‏ : ‎ 162 pages
  • ISBN-10 ‏ : ‎ 1935504215
  • ISBN-13 ‏ : ‎ 978-1935504214
  • Item Weight ‏ : ‎ 14.5 ounces
  • Dimensions ‏ : ‎ 8 x 0.37 x 10 inches
  • Customer Reviews:
    4.0 4.0 out of 5 stars 50 ratings

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William Kent
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William Kent (1936-2005) was a renowned researcher in the field of data modeling. Author of Data and Reality, he wrote scores of papers and spoke at conferences worldwide, posing questions about database design and the management of information that remain unanswered today.

Though he earned a bachelor’s degree in chemical engineering and a master’s in mathematics, he had no formal training in computer science. Kent worked at IBM and later at Hewlett-Packard Laboratories, where he helped develop prototype database systems. He also served on or chaired several international standards committees.

Kent lived in New York City and later Menlo Park, Calif., before retiring to Moab, Utah, to pursue his passions of outdoor photography and protecting the environment.

Customer reviews

4 out of 5 stars
4 out of 5
50 global ratings

Top reviews from the United States

Reviewed in the United States on January 6, 2012
I did my PhD in database in the early 80s. This book by W. Kent was around already and I heard about it but did not have a copy of it. Had I read the book, my research work would have been 10 times better. This current printing is the reprint of the original one. The author mentioned in the preface that he was asked to update the book but he didn't because he thought it was still up to date (and I absolutely agree).

If you are in data modeling and database area, believe me, this is a must read. It is about the philosophy of data modeling and how data and reality are related. In my opinion, its content cannot be obsolete. It is technology independent. The concept of naming and identification alone is priceless for data modelers. I can't believe I have been working in the database area for more than 30 years without it.
22 people found this helpful
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Reviewed in the United States on August 6, 2011
I found this book following a reference from a Martin Fowler book.

It's been a while since I read it, very interesting discourse on modelling data.
Reviewed in the United States on November 7, 2017
This is an excellent introduction to the ambiguities that make designing a database difficult and some of the more philosophical aspects of designing databases. A lot of the historical detail is interesting for modern practitioners. I would strongly recommend trying to obtain an edition of this book other than the "third edition" which has been significantly modified by Steve Hoberman. I am in complete agreement with this review (https://www.amazon.co.uk/gp/customer-reviews/RZUKQF8JV7DM3/ref=cm_cr_dp_d_rvw_ttl?ie=UTF8&ASIN=1935504215). I would recommend attempting to get hold of an older edition, like this one, while emailing Penguin asking them for a new edition of the original book.
5 people found this helpful
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Reviewed in the United States on April 3, 2021
The audiobook is very unapproachable. The topic itself doesn’t fit with the auditory model of sharing information. Philosophical books rarely do. Good luck soaking the information here deeply unless you’re running it at .8x playback.

Worse yet, as others have described, the audiobook is littered with what I think are footnotes, that are read aloud in a way that diverges the listener’s attention away from the topic at hand.

I strongly recommend that this audiobook be discontinued. The paperback experience of this book might be very different, but the audiobook was a slog that I regret putting myself through.
One person found this helpful
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Reviewed in the United States on August 17, 2011
This book does bring a sense of "reality" to data and data modeling. The author provides a fresh perspective on data and data modeling without being dogmatic about which way is the best way to represent data. He exposes some of the subtle but critical factors which everyone working with data needs.
His exposure and description of relationships and how to address them was enlightening.
2 people found this helpful
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Reviewed in the United States on April 17, 2013
Some very important considerations for data modeling. Clearly explained with lots of good examples. William Kent does an excellent job of delving into the philosophy but always pointing back to the need to keep things practical for your use case. This will change the way you think about data and how it is represented.
2 people found this helpful
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Reviewed in the United States on March 10, 2006
This text is deemed fundamental by, for instance, Christopher J DATE, the current leader in the field of Relational Data Management. This alone is reason enough to grant it a place at my wishlist.
11 people found this helpful
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Reviewed in the United States on October 8, 2014
A study group book. Good discussion but everyone pretty much agreed it was too vague and out of date.
One person found this helpful
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Top reviews from other countries

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Artemios Vogiatzis
5.0 out of 5 stars Must read
Reviewed in Germany on March 24, 2020
We should have made some progress in data management since this book was first published in 1978. The more the people that read it, the more the chances that the problems described in the book become obsolete in the (near) future.
Amazon カスタマー
1.0 out of 5 stars 期待と異なる。
Reviewed in Japan on June 11, 2020
データモデリングの具体的な方法論が記述してあると思っていたが、もっと抽象的な内容だった。(同じとは何かとか)
好きな人は好きなんだろうが、求めていたものと異なる。
Ken Evans
5.0 out of 5 stars It didn't stop there!
Reviewed in the United Kingdom on June 28, 2005
This book covers essential concepts that are even more essential to understand than they were when the book was written (circa 1977). In the intervening years, the consequences of poor data management have become much worse. The good news is that help is on the way!
In the last 25 years, solutions have been developed to many of the data problems described by Kent. Sadly, it seems that very few developers or analysts really understand the issues raised by Kent which is probably why so many software projects end up as expensive failures.
Chapters 1-9 expose the data management problems and the awful limitations of what in 1977 passed as "data models" (e.g. the necessity to force fit "many to many" concepts into the inflexible "1 to many" structure of the traditional heirarchical databases and the aparrent lack of any widespread understanding of conceptual models and abstract domains. (Still true today)
Chapter 10 gives interesting insights into the relational model which at the time (1977) was only 8 years old and was not widely available in database products.
Chapter 11 is entitled "Elementary Concepts: Another Model?"
In this excellent chapter, Kent explains n-ary relationships and shows how binary relationships are best seen as instances of the set of n-ary relationships.
Chapter 12 contains insights into the hidden effects of language on thinking.
Many of the ideas in Chapter 11 later appeared in NIAM (Nijssen's Information Analysis Methodology). In the mid 1980's Terry Halpin worked with Sjir Nijssen and formalised NIAM as ORM (Object-Role Modeling language). Terry's most recent books on this matter are:
1: "Information Modeling and Relational Databases" -MKP 2001.
This 754 page book is the ORM Bible and is a set book for University Students in the USA.
2: "Database Modeling with Microsoft Visio for Enterprise Architects" MKP 2003.
This book shows you how to use the ORM tool which provides solutions to most of the problems that Kent describes in his book. This book is also a set book for University students in the USA. (I'm pleased to have co-authored this book with Terry)
Historical Note:
An ORM tool was developed in 1989 and first appeared as a product called "InfoDesigner". This tool evolved through the 1990's as "InfoModeler" which was bought by Visio who incorporated it into the high end Visio product. Microsoft then bought Visio and the fruits of Terry's many years of hard work and dedication are now (fairly deeply) embedded in Microsoft Visual Studio.NET for Enterprise Architects. (You can download the latest beta from the Microsoft Website).
In conclusion:
"Data and Reality" gives an excellent description of the horrendous data definition problems that are still with us today.
If you read "Data and Reality" and then say "Wow! Yes! William Kent has articulated problems to which we urgently need a solution!, then I strongly recommend that you investigate ORM.
8 people found this helpful
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Adrian Kosmaczewski
1.0 out of 5 stars Insulting
Reviewed in Germany on October 15, 2022
This book is an insult to the original. The reviewer had the unexplainable idea of cutting sections from the original, has added his own "takeaways" at the end, and broke the flow of the book with notes and diagrams that are completely out of place. I understand the need for "commented editions" of classic books, but when done properly, those comments go on footnotes, so as to not disturb the reading flow of the original, providing context only where needed. Context, not fanboy opinions. This is a disaster of a book. It's unreadable, annoying, unnecessary.
One person found this helpful
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David Allsopp
5.0 out of 5 stars Excellent, though incomplete conclusion
Reviewed in the United Kingdom on July 22, 2005
Kent blows away misconceptions and confusions about data modelling and highlights many of the fundamental problems with trying to represent complicated real-world data in simple computer systems. This book is old, but the message is as fresh as ever. The only disappointment is that Kent begins to outline a system for better data modelling then admits it is incomplete and leaves much unfinished - an exercise for the reader, if you like! Readers with a technical background in databases or ontologies will find a lot of his insights spookily familiar.
5 people found this helpful
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