W. H. InmonBuilding the Data Warehouse
J**E
Four Stars
On the money, Nickels!
A**R
Great book
One of the imprescindible books to start with datawarehousing and BI. A shame for Amazon to deliver it in a month and a half!
C**Z
Excelente!!!!
Excelente!!!!
H**A
Five Stars
I like it
M**R
Nice Job, Bill!
A little over fifteen years ago, I was working for the then great, and now deceased, Chicago area consulting firm of Greenbrier and Russel. On their behalf, I was often called upon to speak publicly on matters relating to logical data modeling and relational database design. One of these occasions was a meeting of the Milwaukee chapter of the Data Administration Management Association. When I spoke before these wonderful folks, the speaker following me was one Bill Inmon. How could I have known then how close was I to one of the real future "rock stars" of the Data Warehousing World? (I must also report that some folks said I gave the better presentation that day. But that had everything to do with the excellent presentation graphics put together by the outstanding staff at G&R. Inmon, obviously, still lacks such artistic, professional support.)In any case, Inmon's book, now reviewed, is really quite a good introduction to the important, and still emerging, topic of corporate data warehousing. It is, as some other reviewers have averred, a bit light technically. However, it does provide something of a "soup to nuts" introduction to the topic. I was particularly struck by how nicely Bill dealt with the evident controversy still extant between what is styled as his data warehousing approach versus that of Ralph Kimball. Inmon respectfully cites Kimball in the corpus of this text. In so doing, he simply, and I'd judge fairly, illustrates the difference between the approaches, allowing his readers to reach their own conclusions. In the sometimes acrimonious world of technical debate, I found this approach refreshing and praise worthy.As a practitioner of many years in the discipline, I can recommend Inmon's book as an excellent and comprehensive introduction to the important and still emerging topic. God bless.
S**I
360 view of data warehousing but not readable
I read the 3rd edition of the book.It covers the data warehousing field completely - giving a 360 degree view to a reader. However it is not very readable. The ideas are expressed in a difficult way and you can not figure out the author's higher level of flow of thought while going through one specific chapter.There are too many diagrams. Nearly all are useless. They do not add any further clarity to the topic or the situation . If the topic will mention about a simple data flow from A to B then it will refer to a diagram which will have two rectangle boxes connected with an arrow and that is it. A mention of a slight modification in the same date flow will result in referring to a new diagram. This way of explanation frustrates the reader especially because mostly the diagrams are not placed on the same page where they are being referred to. You generally have to flip 2-3 pages to reach to the diagram page then you flip back to the topic page to discover that another reference is being made to another diagram 4-5 pages away. This frustrated me so much that I later skipped noticing the diagrams.The book does explains a lot of things around data warehousing but it lacks the tactic to mesmerize a reader .It is definitely not for a newbie as it requires good knowledge of the field to be able to grasp the abstractness of the ideas.If you can somehow remove the repetitive mentioning of differences between OLTP and DWH and the statement that DWH can not be build in one cycle, the book will literally shrink to half of its current size.
F**O
BI for smarties
In my opinion Kimball vs Inmon is not a war of religion, they both have pro and cons in different situation. I believe people seriously interested in BI should read the book and take several advices from it. There are situation in which an Inmon design is good, there are some in which it isn't BUT to be able to judge you need to know both an be able to decide based on the customer's necessity.The pictures in the book are really ugly and useless, nevertheless the concepts are clearly stated and easily understandable. If I have to say something wrong about it is that you need to already know what a BI system is in order to get the most out of the book. It is not for newcomers but it is definetely a good book on BI.
A**R
Five Stars
excellent book!
S**.
For Information Only
I needed this book to get a clear perspective of what the Inmon approach is. And I think it is good for that purpose only. It is very haphazard - especially if to one who has gone through the Kimball works.The material repeats itself simply because there is no clear approach. Also, I agree with some other viewers that practical world doesn't follow this approach. No business is willing to pay a fortune for a solution that does not deliver a high performance reporting solution within a couple of quarters at most. A 3NF model does not deliver that and the duration is hardly enough to take the solution through phases outlined in the book.The approach defined here is great in theory and is a lip smacking opportunity for any person who finds a sponsor patient and visionary enough to implement it. The book does not help for any sort of implementation as it lacks content and clear approach.It is also a bit out of line in outright rejection of star schema given that it is being adopted (successfully) by designs of market leading products.
G**Y
The Bible of Data Modeling
This book is the bible of data modeling for a data warehouse. The principles mentioned in this book are used across the industry in various data warehouse implementations.The book gives clear insight into how a table is to be designed for a particular scenario and why. This book is a must-have for any architect and aspiring database developers.
C**L
Ein Muss im Bereich DWH
Ein absolutes Muss für jeden DWH Berater in der BI Branche, verständlich und nachvollziehbar geschrieben.Top Lektüre an die man nicht vorbeikommt.
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