- Paperback: 276 pages
- Publisher: 1st Book Library (April 20, 2000)
- Language: English
- ISBN-10: 1585009709
- ISBN-13: 978-1585009701
- Product Dimensions: 5 x 0.6 x 8 inches
- Shipping Weight: 10.4 ounces
- Average Customer Review: 11 customer reviews
- Amazon Best Sellers Rank: #4,280,202 in Books (See Top 100 in Books)
Enter your mobile number or email address below and we'll send you a link to download the free Kindle App. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required.
To get the free app, enter your mobile phone number.
Data and Reality
Use the Amazon App to scan ISBNs and compare prices.
"Children of Blood and Bone"
Tomi Adeyemi conjures a stunning world of dark magic and danger in her West African-inspired fantasy debut. Learn more
Customers who bought this item also bought
Customers who viewed this item also viewed
What other items do customers buy after viewing this item?
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.--This text refers to an out of print or unavailable edition of this title.
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.
--This text refers to an out of print or unavailable edition of this title.
Author interviews, book reviews, editors picks, and more. Read it now
Top customer reviews
There was a problem filtering reviews right now. Please try again later.
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.
His exposure and description of relationships and how to address them was enlightening.
I have to admit that I had to read the earlier version book three times and the reality came about when I reviewed my models and other models against the backdrop of the perspectives described in the book and attempted to apply some of the ideas William has put forth.
What is also helpful is that William did not attempt to put forth singular solutions, but describes the problem in detail so you can appreciate all the perspectives before deciding how to deal with the problems and challenges in an informed way. When dealing with data, ignorance is not bliss. Reality should rule.
For example if you have to model roles and relationships you will attest to the fact that there is no best solution. Other books provide prescriptive solutions that eventually limit the use of data. They are too simplistic. William looks at this problem from a distance and then delves into the microscopic view. It provides a Grand Unified Theory for data.
This version of the book offered me an opportunity to renew my understanding and appreciation for data and with the additional content provided by Steve Hoberman, some helpful examples and clarifications of the concepts. More reality.
Anyone in the field of data including data architects, designers and developers should read this book and internalize the concepts and issues identified in it. Only then will you have a "real" perspective on data.