Customer Reviews

The Data Warehouse Toolkit: Practical Techniques for Building Dimensional Data Warehouses

5 star:		(26)
4 star:		(6)
3 star:		(4)
2 star:		(1)
1 star:		(0)

 

 

Kimball has done an excellent job by writing this book. You don't require any mentionable knowledge about data warehousing or dimensional modeling to completely comprehend this book. He has explained all of the concepts of Dimensional Data Warehouse with the help of real-life examples. Perhaps that makes this book so unique and pragmatic.It is easy to read and also chapters are well arranged to gain a very systematic progression of the subject. All the concepts are explained and postulated in the context of some examples. So don't plan to skip any chapters. That doesn't work with this book.

I would recommend this book, to anybody who wants to practice DDW, as the first book to be read on the subject to gain most.

Because of its entirely example-based approach, the book may not be of much use in an exclusive conceptual/academic perspective.

The only omission I have noticed in this book is, it doesn't speak much about data extraction complexities. Even though Kimball dedicates a few pages towards the end of the book for this purpose, it is largely insufficient and gives no worthful advice to a practioner of data extraction process. So if you are looking for a solution to your data extract nightmare, this book is of little use.

This book is writen in very good language and very easy to understand. For the beginner it's the best choice, but for the advanced project manager or system analyst i will recommend other one from R. Kimball : The Data Warehouse Lifecycle Toolkit. Thanks to Ralph and to their team - it's one of the best books about DW in the market.

A good book, but a bit tough reading, especially when you get to the examples and building of fact tables and dimensions. I would suggest reading the content and skipping the examples the first time and the read the entire book. It helped to have that understanding first. A few of my colleagues have put the book aside for lack of wanting to "Plow through" the examples. I managed to read through the book this way in a matter of a few days. It helped to clarify what pieces I was missing ans strengthened what I knew.

Hello

This book will be helpful for people who are tasked with building Data Marts that could benefit from the use of dimensional modeling and can also be represented as a dimensional models.

Dimensional data models, which have been around for a very long time, have proved quite useful in a number of business decision making scenarios where decsision making power - through an intentionally limited but versatile set of information - can be made available to business users.

This book focuses on the data modelling for decision support in a Data Mart environment, and also where star schemas - intuitive data models - are used to represent business information in a business-people friendly structure and format. In this area - dimensional modeling and sophisticated use of SQL - the author is probably the best around at this moment in time.

So yes, buy this book if you need a rapid learning aide for dimensional modelling and if you want to know more about the general area of Data Warehousing and some of is best principles and practices then also go for a couple of books by Bill Inmon - the father of data warehousing.

Best regards,

Martyn R Jones iniciativa

I have been working in the commercial reporting / data warehousing market for over 5 years. I have read many books on the subject, most of which deal with the higher level conceptuality of data warehousing and implementation. Since reading this book I have designed and implemented a multi-dimensional data warehouse, using most of the techniques laid out in this book, with a European manufacturing company in BD2/400 and SQL datamarts. I found this book outstanding in terms of breaking down the problems of creating a multi-dimensional data warehouse and giving a very practical analysis to implementation model. It is possible within the right company to implement a large data warehouse following the methods in this book. To complement this book I would recommend reading other books that deal with client expectation management and the use of middle ware tools to ease the actual building and management of a multi dimensional design. Also look at other design models, make sure that a multi-dimensional design fit's the client situation, there are other designs...

For people who have a transactional database background, such as myself, and are moving into the data warehouse arena, this book should be the bible! Kimball eloquently shows how a company's business model and thier data needs can be meshed perfectly, and leaves the reader wondering why this is not done in every case. In fact, he actually answers that question several times throughout the book.

The real-world examples serve to cement Kimball's concepts in your mind and you try to forget most of you've learned about how to construct normalized, transactional databases.

This is actually the first software "textbook" I've enjoyed reading in my 15 years as a database designer.

Every once in a while a technical book comes along that changes the way the world looks. "The Data Warehouse Toolkit" is just such a book. If you have spent your career in the world of relational database models, you owe yourself a read of this book to see a new and different paradigm. This book shows where the "rubber meets the road" for data warehouses accessed by end-users to answer real business questions. As a technology consultant specializing in data warehouses, I don't leave home with out the book I have now used to build data warehouses on three continents.. Kimball presents not only a new way to view data organization, but also provides the practical information necessary to apply it to the real world (with examples on CD-ROM including a live OLAP tool). The multidimensional model with relational database management systems described by Kimball is the key to success for any sizable data warehouse. We don't call it "The Bible" for nothin'.

Data warehosuing is a difficult subject to grasp. There are many disciplines that have to come together to make data warehousing work : database design, business understanding, management expertise, data mining, creating reports, project management, OLAP and more.

Finding a book that can full explain the full data warehousing picture is not possible, what one must look for is a series of books or materials that will together paint the full picture.

Building Dimensional Data Warehouses is one of the books that can help readers in the process of painting the whole data warehousing picture. Ralph Kimball is an experienced data warehousing leadder who has stayed away from hype and concentrates on facts.

The focus of this is book is creating the data structure for repositories in the data warehouse set-up. This is a highly recommended book for technical readers looking to enhance on their database design skills for building large data repositories that are optimized for providing analysis.

Business readers may obtain more value from reading some of the other of Mr. Kimball's books.

Please let me know if you have found this review helpful.

This book contains concepts and implementation methodology associated with building and deploying a data warehouse.

To understand data warehouse, it is important to understand the difference between an OLTP system and a data warehouse (an OLAP system). The author first emphasizes this difference before getting into the nitty gritty of data modeling.

The author is a leading advocate of Dimension modeling. He gives clear reasons for doing so and then jumps into the techniques for dimension modeling, also called as Hub-and-Spoke architecture.

Book contains examples (in the form of chapters) of data warehouse models for many verticals such as shipping, insurance, banking, subscriptions, inventory. Going through these examples will help anyone to understand data modeling and to create a dimension model based on specific requirements.

The best book for fundamentals of data warehouse and especially, Dimension modeling.

Every college who is just thinking of designing a data warehouse should read this book. The descriptions of the dimensional modelling techniques are clear and accurate, and there are some very good examples of different industries. The book have logical structure and is ease to understand. What I missed is the loading part so as the design of staging areas. Extraction and stating can easy turn to a nightmare. So if you are looking for an approach concerning the backend of a data warehouse, this book is of little use. But anyway I consider this book as one of the classics in data warehousing.