The Multidimensional Data Modeling Toolkit: Making Your Business Intelligence Applications Smart with Oracle OLAP Review

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(More customer reviews)I thought this book was definitely worthwhile. It gave a good explanation of the multidimensional data framework and what can be done with it. Even though I don't use Oracle, I found the discussion interesting and the concepts useful. I do web marketing as a profession and have been curious about what kinds of analyses can be done with OLAP and business intelligence tools. I think this book did a good job of explaining that. I ran across the book at the office, I picked it up and found it very readable. The book included a lot of technical specifics about how to work with the Oracle system, which I glossed over mostly, but was still able to follow the rest of the book just fine. If you want specifics on Oracle (Analytic Workspaces, Oracle OLAP, etc), you'll find them here, if you want the concepts of OLAP and multidimensional data analysis, you'll find that too, all in a well-written volume with a few funny cartoons.

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The Multi-dimensional Data Modeling Toolkit provides an In-depth treatment of Oracle OLAP as well as a comprehensive examination of analytical techniques in a multidimensional OLAP framework. Application developers and database administrators will appreciate this book, packed with examples, tricks and techniques, and concrete illustrations of the programming elements needed to implement high-performance analytical applications. Data miners, statisticians, and power analysts will find the analysis techniques of particular interest.Written in a tutorial style, this book gives, in plain English, a step-by-step development of the defining principles of OLAP analysis through the lens of the programming language at the heart of Oracle's OLAP database option. This book represents over 15 years of hands-on experience developing multidimensional analytic applications for over a dozen companies.Whether you are new to business intelligence or a seasoned practitioner, The Multi-dimensional Data Modeling Toolkit will have something to offer.

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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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Data Modeling Made Simple: A Practical Guide for Business and IT Professionals, 2nd Edition Review

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(More customer reviews)I think very highly of Data Modeling Made Simple (the first edition), so when this second edition came out I had great expectations - which were not only met but also exceeded. Although this second edition is more than twice the number of pages as the first edition, it is still an easy read.
Here are my favorite things about this book:
1.Clearly delivers on its ten objectives. Read the back cover and you will understand the key takeaways you will get after reading the book. After I read the book, I went back over each of these objectives and I was able to check each of these off as accomplished. Everything from justifying the model to building data models to assessing data models was knowledge I gleaned from the book. If you are interested in just one or a subset of these ten objectives, read the Read Me First section and it will reference the sections and chapters you need to read to meet your specific objective.
2.More examples more thoroughly presented. The first edition took a business card example from beginning to end. This edition further expands the business card example and adds several other examples including an ice cream example and many real world examples. The author uses spreadsheets to illustrate many modeling examples, and I too have found spreadsheets to be a very effective way to communicate data and business rules.
3.Data Model Scorecard. The first edition touched on the Scorecard which is the author's technique to reviewing a data model. This second edition goes into detail including providing the template which I can use on my modeling assignments to review my models.
4.Treating a dimensional model as more than just a physical data model. Many texts treat the dimensional as only a physical data model yet there is a business level that this book illustrates at both the subject area and logical levels.
5.Getting other Greats for free. Bill Inmon, Graeme Simsion, and Michael Blaha have all written chapters in this book. I have already starting using Simsion's technique of a diary on my assignments and found it very useful.
My only area for improvement would be to expand the book with more modeling conventions such as ORM and IDEF1X. There is a chapter on UML though that I did find informative. I question however if adding these extra notations would detract from the book's simplicity.
Overall, an excellent read that I would recommend to every business or techie that works with data.


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Data Modeling Made Simple will provide the business or IT professional with a practical working knowledge of data modeling concepts and best practices. This book is written in a conversational style that encourages you to read it from start to finish and master these ten objectives:
Know when a data model is needed and which type of data model is most effective for each situation
Read a data model of any size and complexity with the same confidence as reading a book
Build a fully normalized relational data model, as well as an easily navigatable dimensional model
Apply techniques to turn a logical data model into an efficient physical design
Leverage several templates to make requirements gathering more efficient and accurate
Explain all ten categories of the Data Model Scorecard
Learn strategies to improve your working relationships with others
Appreciate the impact unstructured data has, and will have, on our data modeling deliverables
Learn basic UML concepts
Put data modeling in context with XML, metadata, and agile development

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