Database in Depth: Relational Theory for Practitioners Review

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(More customer reviews)Over the last week or so, I've been reading C. J. Date's book Database In Depth - Relational Theory for Practitioners (O'Reilly). While it's a well-done title, it's the type of book I have a hard time reading...
Contents:
Introduction; Relations Versus Types; Tuples And Relations; Relation Variables; Relational Algebra; Integrity Constraints; Database Design Theory; What Is The Relational Model?; A Little Bit Of Logic; Suggestions For Further Reading; Index
C. J. Date, along with E. F. Codd (the acknowledged "father" of relational database theory), are probably the two most influential individuals in this field. Much of what we know and practice in today's RDBMS packages all goes back to the work these two have done. Rather than write a textbook style discussion of the finer points of database theory, Date has used this book to update some of his thinking and to consolidate a number of his talks and writings of late. For serious students of relational database concepts, I'd consider this the latest "must read" to keep up with current thinking by one of the masters.
Having said that, I had a hard time slogging through the material. I tend to gravitate to technical reading material that is practical and understandable. Debates over finer points of arcane minutia will cause me to zone out quickly. Unfortunately, I felt that way through a lot of this book. There is a lot of solid technical material here, and it's definitely geared towards serious readers. Date doesn't have a lot of kind words to say about how database vendors have implemented the relational model, nor does he feel SQL is a good thing. I, on the other hand, figure the packages are what they are, and you had better learn to use them to create the systems needed by your customers. That's probably why I'm a developer and not a system architect. Reading a number of pages on why Date and Codd disagree on whether nulls are valid or allowed doesn't do much for me. They're there, you need to understand them, and then you need to move on. Another hard part for me was the heavy emphasis on mathematical proofs and such. Since I don't have that type of background, I'm quickly lost...
Even though I wasn't completely enamored with the book, I still think it is a good title. For the right reader, this will be material that they will benefit from. For the average person who got training on Oracle or DB2 and understand basic relational database theory, this may be a bit more difficult to get through...

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This book sheds light on the principles behind the relational model, which is fundamental to all database-backed applications--and, consequently, most of the work that goes on in the computing world today.Database in Depth: The Relational Model for Practitioners goes beyond the hype and gets to the heart of how relational databases actually work.

Ideal for experienced database developers and designers, this concise guide gives you a clear view of the technology--a view that's not influenced by any vendor or product.Featuring an extensive set of exercises, it will help you:

understand why and how the relational model is still directly relevant to modern database technology (and will remain so for the foreseeable future)
see why and how the SQL standard is seriously deficient
use the best current theoretical knowledge in the design of their databases and database applications
make informed decisions in their daily database professional activities
Database in Depth will appeal not only to database developers and designers, but also to a diverse field of professionals and academics, including database administrators (DBAs), information modelers, database consultants, and more.Virtually everyone who deals with relational databases should have at least a passing understanding of the fundamentals of working with relational models.
Author C.J. Date has been involved with the relational model from its earliest days.An exceptionally clear-thinking writer, Date lays out principle and theory in a manner that is easily understood. Few others can speak as authoritatively the topic of relational databases as Date can.

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Data and Reality Review

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(More customer reviews)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.

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The Data Model Resource Book, Vol. 1: A Library of Universal Data Models for All Enterprises Review

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(More customer reviews)I like this book. It definitely saves a lot of time and mistakes while data modelling which is one thing you better get right in your app as data migration to a new model both at the app and database level is often a time consuming and bug prone process.
That being said the locked cd is a nuisance and sometimes the data model becomes almost ridiculously detailed. For instance in one part of the book the author talks about extending the person data model to include things such as the history of the person's gender (for instance if they had multiple sex changes). I have seen a lot of overbuilt data models that had lots of entities that were rarely used and contributed to a significant amount of clutter and generally overwhelmed developers with useless details and planning for corner cases that never happened.

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Data Modeling for Everyone Review

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(More customer reviews)As I was reviewing this book for a class I was teaching on the subject, I could'nt help but think the author's effort was rushed. This book would be good for someone with a strong data modeling background who wants a new perspective. It is a poor choice for novices to the field. Explanations are lacking in clarity. Book is poorly organized. Check out Inside Relational Databases, Whithorn.

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Data Modeling is about gathering, documenting, and communicating the elements and structure of business information. What begins as a conceptual interplay of logical data units, through the application of relational theory, becomes the basis for creating a physical database design.Data Modeling is a core skill for data professionals, and is a full time job for a small but growing number of IT practitioners. It is a crucial stage prior to good quality relational database design.Data Modeling for Everyone is for those who:Have no previous data modeling experienceWant to understand the role of the data modeler in database designNeed to know how to capture the essence of a system but don't know where to startWant more than just the theory and learn best from real world experienceRequire a book before other data design books – helping you develop a logical model rather than assuming one exists that needs to be implemented in a databaseData Modeling for Everyone provides a solid foundation in the following tools & techniques:The different types of data modeling – enterprise, transactional, and dimensionalThe stages of analysis – developing conceptual, logical, and physical modelsWhat to do if you need to work with existing systems – reverse engineering and forensic analysisGeneral principles for converting logical models to physical onesModeling scope – focusing on what's important but allowing for future development of your modelDefining detail – entity relationship (E/R), key based, and fully attributed modelsDocumenting your understanding of the business in the modelGraphical data modeling, focusing on the IDEF1X notation--This text refers to an out of print or unavailable edition of this title.

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Data Modeling Made Simple: A Practical Guide for Business & Information Technology Professionals Review

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(More customer reviews)For over a year I'm looking for a good book to help business analysts to understand data models drawn by others and to train them in creating basic data models needed to cover business needs. I found a lot of good books but all too heavy, too many pages, too detailed and very nice if you want to become a real heavy duty data-guru. There is absolutely nothing wrong with data gurus, every organization needs a few of those, but it needs quite a few more of the 'casual' modellers. This book .. not too big.. a good read.. and even better reread.. It contains exactly everything that is needed for those modellers.
So, if you're a Business Analyst, Information Manager and need a good understanding of Data Modelling, even occasionally need to make one yourself, without having to spend years in training: buy this book..


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Ever have a bad data day? If you're a business user, architect, analyst, designer or developer, then you've probably had some bad data days. It comes with the territory. Overcoming these problems is much easier if you have an in-depth understanding of the actual data. That's where a data model comes in handy. It's a diagram that uses text and symbols to represent groupings of data, giving you a clear picture of your business and application environment. Data Modeling Made Simple provides the tools you need to read, create and validate models of your business and applications.

This book contains everything about modeling you need to know but were too afraid to ask, such as:
-What are the traditional and nontraditional uses of a data model?
-How do subject area, logical, and physical data models differ?
-When do I build a BSAM, ASAM, or CSAM?
-What is the easiest way to apply normalization?
-Where can I best leverage abstraction?
-How do I decide whether to use denormalization or dimensionality?
-What are primary, foreign, alternate, virtual, and surrogate keys?
-What is the best approach to building the models?
-How can I use the Scorecard system to validate a data model?

Plus over 30 exercises to reinforce concepts and sharpen your skills!

Reviews:
"What a great book—and a fun read too! Steve has captured the essence of data modeling and made it simple. For those who are not data modelers but need to work with them, this book is an excellent primer. For those who model data occasionally but not routinely, it is an invaluable quick reference. And for those of us who are experienced (and incorrigible) data modelers, Data Modeling Made Simple is a terrific reminder that we really can keep it simple!"
David Wells, Director of Education, Data Warehousing Institute

"An excellent introduction from someone who knows his subject and knows how to teach it"
Graeme Simsion, University of Melbourne

"Data Modeling Made Simple is a must read for all professionals new to data modeling as well as those that want to ‘speak the language' and understand the concepts.Steve writes as though he is right there with you, walking you through the terminology, explaining the symbols, and telling you what you should consider doing before, during and after you have modeled your data."
Robert S. Seiner, President, KIK Consulting & Educational Services, LLC andPublisher of The Data Administration Newsletter, tdan.com

"Data Modeling Made Simple is an excellent training guide for anyone entering the data modeling field. Steve Hoberman takes the fundamental concepts of data modeling and presents them in an easy to understand and entertaining manner that I'm sure you will find valuable."
David Marco, President, EWSolutions

"How does one who is not a formally trained ‘data modeler' understand the basics of data modeling?Steve Hoberman has created an informative, fun, easy to follow, and practical book sharing data modeling concepts which are essential for any professional involved in information technology. Mr. Hoberman clearly answers key questions behind the what, why and how of data modeling and reinforces the explanations with appropriate examples, analogies and exercises."
Len Silverston, Best-Selling Author of The Data Model Resource Book, Volumes 1 and 2

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Data Modeling: A Beginner's Guide Review

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(More customer reviews)This book is perfect for beginner who wants to learn about data modeling in RDBMS. This book has good TOC and very easy to find what you want to read.
Very useful tips like "Ask the Experts" section. Very easy to understand when a book comes with step-by-step section. Good examples to show tables and data relationships.
I am new to data modeling in RDBMS but after reading this, I can easily create a small test database with some test data and check out the examples from this book. At the end ...., I say hey..it works!!!


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Essential Skills--Made Easy!
Learn how to create data models that allow complex data to be analyzed, manipulated, extracted, and reported upon accurately. Data Modeling: A Beginner's Guide teaches you techniques for gathering business requirements and using them to produce conceptual, logical, and physical database designs. You'll get details on Unified Modeling Language (UML), normalization, incorporating business rules, handling temporal data, and analytical database design. The methods presented in this fast-paced tutorial are applicable to any database management system, regardless of vendor.
Designed for Easy Learning
Key Skills & Concepts--Chapter-opening lists of specific skills covered in the chapter
Ask the expert--Q&A sections filled with bonus information and helpful tips
Try This--Hands-on exercises that show you how to apply your skills
Notes--Extra information related to the topic being covered
Self Tests--Chapter-ending quizzes to test your knowledge

Andy Oppel has taught database technology for the University of California Extension for more than 25 years. He is the author of Databases Demystified, SQL Demystified, and Databases: A Beginner's Guide, and the co-author of SQL: A Beginner's Guide, Third Edition, and SQL: The Complete Reference, Third Edition.

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Database Modeling and Design, Fifth Edition: Logical Design (The Morgan Kaufmann Series in Data Management Systems) Review

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(More customer reviews)I have to underscore a statement in the preface with which I am in total agreement: "This book can . . . be used by the advanced undergraduate or beginning graduate student to supplement a course textbook in introductory database management . . ." In fact, the authors point out that the fifth edition of this book has been split into a second work, PHYSICAL DATABASE DESIGN: THE DATABASE PROFESSIONAL'S GUIDE, 1st edition (a title that is not in print at the time of this review). As a book about "Logical Design," explaining WHY (not HOW) is the strength of the work. This is not a book one would primarily rely upon for developing an application. But it is an excellent work for giving solid background in the underpinnings of database design. The HOW (as the author's stated) is spawned off in another work, in this case.
I'm a non-professional IT person who has designed and implemented dozens of LAMP (Linux-Apache-MySQL-php) applications, and database design activities dating back to the 1980's, primarily in the honorable environment of the various MS-DOS flavors of the day. All of this with zero formal training (which isn't the same as NO training). With that background in mind, after going through this book I confirmed that I had picked up a lot of bad habits and developed a lot of good practices. My worst habit? A preference for flat databases over relational ones (see Chapter 8 - Object-Relational Design). My hardest earned (and confirmed by this book) good practice? The absolute importance of "requirements analysis," or, rigorous interviewing of the end user population to "determine exactly what the database is to be used for . . ." (see Chapter 4 - Requirements Analysis and Conceptual Data Modeling). In both of these cases this book was excellent in explaining WHY.
Since I work almost exclusively with web based databases now, I found Chapter 9 (XML and Web Databases) to contain one of the most concise and elegant explanations of XML I've ever read.
One annoying, but not fatal, flaw of this work: the quite serviceable index appears before the appendices, instead of the almost universal location of the last section of the book. I.e., when I turned to the back of the book to use the index, it wasn't where I expected. After a little fumbling, I did find it, but this is, in my opinion, a logical design flaw of the book.
I wouldn't hesitate to recommend this book as a purchase to an undergraduate MIS student even if it isn't a class requirement. This is a good book to develop a solid conceptual foundation. Also, since this book is primarily conceptual in its focus, it should have a shelf life much longer than works which focus on specific hardware and software which evolve continuously. Most of the concepts described in this book would have been relevant to me in my MS-DOS database days.

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Database systems and database design technology have undergone significant evolution in recent years. The relational data model and relational database systems dominate business applications; in turn, they are extended by other technologies like data warehousing, OLAP, and data mining. How do you model and design your database application in consideration of new technology or new business needs? In the extensively revised fifth edition, you'll get clear explanations, lots of terrific examples and an illustrative case, and the really practical advice you have come to count on--with design rules that are applicable to any SQL-based system. But you'll also get plenty to help you grow from a new database designer to an experienced designer developing industrial-sized systems.
In-depth detail and plenty of real-world, practical examples throughout

Loaded with design rules and illustrative case studies that are applicable to any SQL, UML, or XML-based system



Immediately useful to anyone tasked with the creation of data models for the integration of large-scale enterprise data.

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The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling (Second Edition) Review

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(More customer reviews)There are a lot of data warehousing books out there that try to answer the question: 'Why'? Why data warehouses are needed to help businesses make better decisions - why the OLTP systems that run the business can't do this - and sometimes even why businesses ought to invest in data warehouses. These books were terrifically useful to us years ago, when we needed help (and scholarly footnotes) in our data warehouse project proposals. This book is not one of those - it is all about:
How
How to actually design and build a repository that will deliver real value to real people. In this reviewer's opinion, Ralph Kimball's many contributions related to the 'how' of data warehousing stand alone.
An engineer wishing to jump-start his or her data warehouse education would need to read Ralph's Data Warehouse Toolkit first edition, his Data Webhouse Toolkit... a bunch of "Data Warehouse Designer" Intelligence Enterprise magazine articles... AND lurk on the Data Warehousing List Server...for a few years (all terrific resources - by the way) - in order to stockpile the knowledge that is crisply presented here.
No shortcuts taken by the authors that I can spot: all of the toughest dimensional design issues that I've tripped on - and that I can remember surfacing on in discussion groups over the past few years - are addressed in this significantly updated text. Not all of the solutions are 'pretty' - but it is clear that they thoughtfully address the problem. This approach, in my opinion, instills student confidence - and lets us know that we are getting sound instruction - not dogma.
The authors have been listening to and addressing the data warehouse community's 'pain' through periodicals and posts for years - but this book pulls these point solutions together very nicely. I learned a surprising number of really useful new techniques, and was genuinely enlightened by the 'Present Imperatives and Future Outlook' section.
As in the first edition, there is minimal philosophical lecturing, and zero religion. Instead, we get generous helpings of real-world case studies - aptly applied to progressively more advanced series of design concepts.
This style absolutely works for me. And I suspect that engineering mindsets typical of the folks that build these things will likely agree. In short, the Data Warehouse Toolkit Second Edition will significantly lighten the load of books that I carry between data warehouse engagements.
Jim Stagnitto
Llumino, Inc.
www.llumino.com

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The latest edition of the single most authoritative guide on dimensional modeling for data warehousing!
Dimensional modeling has become the most widely accepted approach for data warehouse design. Here is a complete library of dimensional modeling techniques-- the most comprehensive collection ever written. Greatly expanded to cover both basic and advanced techniques for optimizing data warehouse design, this second edition to Ralph Kimball's classic guide is more than sixty percent updated.
The authors begin with fundamental design recommendations and gradually progress step-by-step through increasingly complex scenarios. Clear-cut guidelines for designing dimensional models are illustrated using real-world data warehouse case studies drawn from a variety of business application areas and industries, including:
* Retail sales and e-commerce
* Inventory management
* Procurement
* Order management
* Customer relationship management (CRM)
* Human resources management
* Accounting
* Financial services
* Telecommunications and utilities
* Education
* Transportation
* Health care and insurance
By the end of the book, you will have mastered the full range of powerful techniques for designing dimensional databases that are easy to understand and provide fast query response. You will also learn how to create an architected framework that integrates the distributed data warehouse using standardized dimensions and facts.
This book is also available as part of the Kimball's Data Warehouse Toolkit Classics Box Set (ISBN: 9780470479575) with the following 3 books:

The Data Warehouse Toolkit, 2nd Edition (9780471200246)
The Data Warehouse Lifecycle Toolkit, 2nd Edition (9780470149775)
The Data Warehouse ETL Toolkit (9780764567575)

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