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DW 2.0: The Architecture for the Next Generation of Data Warehousing (Morgan Kaufman Series in Data Management Systems) [Paperback]

William H. Inmon , Derek Strauss , Genia Neushloss
3.8 out of 5 stars  See all reviews (4 customer reviews)
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Book Description

14 Aug 2008 0123743192 978-0123743190
Data Warehousing has been around for 20 years and has become part of the information technology infrastructure. Data warehousing originally grew in response to the corporate need for information - not data - and it supplies integrated, granular, and historical data to the corporation. There are many kinds of data warehouses, in large part due to evolution and different paths of software and hardware vendors. But DW 2.0, defined by this author in many talks, articles, and his b-eye-network newsletter that reaches 65,000 professionals monthly, is the well-identified and defined next generation data warehouse. The book carries that theme and describes the future of data warehousing that is technologically possible now, at both an architectural level and technology level. The perspective of the book is from the top down: looking at the overall architecture and then delving into the issues underlying the components. The benefit of this for people who are building or using a data warehouse can see what lies ahead, and can determine: what new technology to buy, how to plan extensions to the data warehouse, what can be salvaged from the current system, and how to justify the expense - at the most practical level. All of this gives the experienced data warehouse professional everything and exactly what is needed in order to implement the new generation DW 2.0. This is the first book on the new generation of data warehouse architecture, DW 2.0. It is written by the 'father of the data warehouse', Bill Inmon, a columnist and newsletter editor of "The Bill Inmon Channel on the Business Intelligence Network". It provides long overdue comprehensive coverage of the implementation of technology and tools that enable the new generation of the DW: metadata, temporal data, ETL, unstructured data, and data quality control.

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DW 2.0: The Architecture for the Next Generation of Data Warehousing (Morgan Kaufman Series in Data Management Systems) + Agile Data Warehouse Design: Collaborative Dimensional Modeling, from Whiteboard to Star Schema
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Product details

  • Paperback: 400 pages
  • Publisher: Morgan Kaufmann (14 Aug 2008)
  • Language: English
  • ISBN-10: 0123743192
  • ISBN-13: 978-0123743190
  • Product Dimensions: 2.4 x 18.8 x 23 cm
  • Average Customer Review: 3.8 out of 5 stars  See all reviews (4 customer reviews)
  • Amazon Bestsellers Rank: 610,676 in Books (See Top 100 in Books)

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Customer Reviews

3.8 out of 5 stars
3.8 out of 5 stars
Most Helpful Customer Reviews
5.0 out of 5 stars AHEAD OF ITS TIME 31 Jan 2014
Format:Paperback|Verified Purchase
Most Data Warehouses I have come across are still somewhere between 1.0 and 1.99 and are in maintenace phases. I would really recoomend that companies re-evaluate their whole DW/BI strategy and make the (quantum) leap to 2.0.
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5.0 out of 5 stars Worth reading 26 Jan 2013
By Emil
Format:Paperback|Verified Purchase
After working on more than a half a dozen of DW projects using Kimball methodology I started to see repeating challenges which lead to decisions or thoughts that I wouldn't classify as Kimball approach. I thought it is the right thing to do but I didn't feel comfortable with that so I thought it is time to check Inmon point of view.

Inmon tries to create a definition of DW 2.0 and I was positively surprised that many examples match my experience and decisions that I didn't feel comfortable with are actually important part of DW 2.0.

Probably the most interesting part for me was that I agree with many aspects (not all) of DW 2.0 but actually my experience is only Kimball which shows quite a significant overlap. The book doesn't go into design details where more distinct differences could be made.

If I compare it to Kimball I would say DW 2.0 is most applicable to large DW which is also what Inmon focuses on in his examples. What I learnt indirectly about Kimball is that it focuses on design and does not try to go into details of other important aspects of building a DW which are outside of the design; Inmon on the other hand does talk about it which I found very useful.

Am I going to use Inmon now? I might use some concepts like interactive area for real time DW (which is rather a pain) and be more flexible with design for instance include exploration area and use Inmon Data Mart approach for Power Users needs but I will most likely stick to Kimball with his Data Mart definition for core DW development but that is largely due to projects I do. For large implementations where people are not at a stage of learning what is a data warehouse I will most likely consider Inmon approach...maybe not all of it but large part that was presented in this book.

Take care
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3.0 out of 5 stars Inspirational, but not operational 29 Jun 2009
Format:Paperback|Verified Purchase
The lettering and layout with lots of original figures and vignettes is a delight. Also, the content and ideas are certainly inspirational but the somewhat contemptuous attitude towards alternative approaches with a well proven track record is not befitting. The presented ideas does not seem to present a fully coherent and complete methodology, but that does not matter, really, when so much is original and not just a reiteration of other texts and previous work. - Pretty advanced, not for newcomers to DW/BI.
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0 of 1 people found the following review helpful
2.0 out of 5 stars Too High level... 6 Aug 2010
I'm afraid I found this book too high level, too academic...perhaps I should have been looking for a technical implementation document from one of the major vendors.
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Amazon.com: 3.6 out of 5 stars  8 reviews
31 of 32 people found the following review helpful
3.0 out of 5 stars Inmon 2.0 26 Sep 2008
By Erik Gfesser - Published on Amazon.com
Format:Paperback|Verified Purchase
Awareness of this book arose following my recent reading of a white paper on Data Vault data modeling by Dan Linstedt that a recent client of mine had suggested. And although I was not impressed with that white paper, what I found intriguing is that Lindstedt quotes Bill Inmon as saying that "the Data Vault is the optimal choice for modeling the EDW in the DW 2.0 framework." Thus the acquisition of this text by Inmon. Almost everyone vaguely familiar with this industry space is probably familiar with Bill Inmon and Ralph Kimball. What is interesting is that Inmon, the "Father of Data Warehousing", is credited alongside two other individuals with writing this text. It is not transparent as to who actually wrote most of the content for "DW2.0", but what is quickly apparent is that most of the statements contained in the book are generalities, and the vast majority of the diagrams are deplorable, consisting mostly of inferior clip art that adds little to nothing to the discussion. Most of the material is presented in a theoretical manner with very little practical substance. This reviewer hesitates to even recommend this latest Inmon effort to client management. Even outside the domain of data warehousing, there seems to be something amiss with what the authors attempt to present. For example, chapter 6 consists of a 17-page discussion on "methodology and approach", and for the first 7 pages of this chapter, the authors discuss the spiral, waterfall, and iterative methodologies. Keeping in mind that there are various interpretations for each of these methodologies (see my reviews for "Agile & Iterative Development" by Larman and "Balancing Agility and Discipline" by Boehm and Turner, for example), the push of the authors to introduce spiral methodology as a "critical step toward success in second-generation data warehousing" is seemingly illogical. Despite all of this, however, what this text provides is as follows: (1) one of the first attempts to standardize data warehousing terminology in what is a very fragmented market segment, (2) explanation of high-level data warehousing concepts, and (3) suggestions on how to avoid some of the problems that have plagued enterprise data and how to manage the high influx of unstructured data that corporations are now creating. Keep in mind, however, that this book is tied into marketing "DW2.0" consulting and certification training, which may provide an explanation as to the vagueness of the material.
23 of 25 people found the following review helpful
3.0 out of 5 stars DW reloaded?? 9 Aug 2008
By Uli Bethke - Published on Amazon.com
First of all, this book is not written with the DW novice in mind. Some of the chapters require a thorough understanding of DW theory and concepts.

Generally I found the book useful and I got some ideas that I will apply in one of my next projects. The biggest weakness of DW 2.0 is its lack in detail. In a lot of areas I found the book to be patchy and too high level. In my opinion DW 2.0 as presented in the book is not (yet) an elaborate data warehousing methodology.

What follows is a discussion of some of the more interesting concepts and chapters in the book.

(1) The different sectors of DW 2.0

To me it did not become fully clear what exactly the Interactive Sector is. Is it a cumulation of an enterprise's operational systems or is it a real time replication of these systems as an additional physical layer? A practical example really would have helped here. Personally I have my doubts if all the operational reporting requirements can be met by the Interactive Sector, e.g. how can a requirement that needs to query data from both the Interactive and Integrated Sector be met?

(2) Fluidity of technology sector

While this offers some interesting thoughts on how to shield the DW 2.0 from changes in business requirements and the operational source systems it only scratches on the surface. The idea as presented by the authors is to physically separate data that structurally does not change frequently (semantically stable date) from data that changes often (temporal data). From the book it does not become clear how this can be achieved. The only advice the authors give here is: "The answer is that semantically static and semantically temporal data should be physically separate in all database designs." (p.121). The authors mention Kalido as a software vendor that provides technology to separate the two different sets of data. From this it seems that they refer to generic data modelling to achieve this separation. However, this does not become clear at all. In my opinion the most frustrating chapter in the book. It raises very interesting questions that it does not answer.

(3) Methodology

Very good summary chapter on why agile and iterative methodologies also advocated by other practicioners in the industry work best for data warehouse projects. If you need to justify an agile approach to your data warehouse project this is a good chapter to refer to.

(4) Performance

Some good ideas on how to improve performance of data warehouses. What I found particularly useful is the concept of farmers and explorers as users of the warehouse that have different analytical needs.

(5) Cost justification

A chapter you can refer to if you need to justify your data warehouse project to management.

(6) Unstructered data

In my opinion this is the best chapter in the book. Before reading the book I had never thought much about unstructured data and how it can be integrated with structured data in the warehouse. The book gives you a good overview on how this might be achieved. However, once again it just scratches at the surface of the problem. It is probably a good idea to refer to Inmon's other book on unstructured data to get more detail.

Overall the book gives a good overview on the concepts of DW 2.0 and what will be required for the next generation of DW 2.0. However, in all chapters it lacks detail and practical examples. The discussion remains somewhat abstract, theoretical, and scientific. It would be nice to see a case study of a data warehouse built on the principles of DW 2.0. Also the quality of graphics and images are of poor quality and let the book down.

One area the authors get wrong is how they define ELT (in opposition to ETL). In contrast to what the authors say ELT does not load the data into the data warehouse and only then applies transformations to it. In ELT tools (such as Oracle Data Integrator or Oracle Warehouse Builder) transformations take place on the data warehouse server(s) using the data warehouse's database engine (using SQL or some dialect). However, transformations happen while the data is loaded or before (staging area on data warehouse servers). This is in contrast to traditional ETL where transformations take place on a separate server ETL server using Java or some other procedural language.
14 of 15 people found the following review helpful
1.0 out of 5 stars Book is built on hype but no substance 22 Dec 2009
By RichardS - Published on Amazon.com
Format:Paperback|Verified Purchase
I bought this book because it had good reviews, however, after reading it I was extremely disappointed with Inmon as it does not appear to be a detailed discussion about data warehousing at all, but an over hyped book which tries to explain fundamental data warehousing techniques in a way that you would explain to a baby (repeated a thousand times and with diagrams of various shapes including triangles, circles, and squares). Seriously! Triangles, Circles and Squares!!!

This book is way overpriced for what it is and the fact that Inmon's name is printed on it, does not mean that the book follows Inmon's traditional data warehousing books. This book is different because it does not deliver much content nor does it deliver any new concepts, breakthroughs or strategies of building data warehouses today.

So whats in the book? Honestly, not much. Just very simple concepts scattered around the book in such little detail that it would be impossible to implementation or incorrect to apply in a real world scenario. For example, if you wanted to look at methods of correcting data in todays complex environments, you can turn to page 330 and find the most useless generic statement "A third approach of correcting values in DW 2.0 environment is the practice of finding bad records and then changing the values in those records". Really? So this is what an expert in the field has to say about it? I think not!

You can see DW 2.0 plastered all over the book for some of the most fundamental concepts that having nothing to do with the next generation of data warehousing, nor are many of these concepts discussed recommended for building the next generation of data warehouses.

If you would like to learn more about DW 2.0, I would recommend reading the free literature from Oracle, Hyperion, IBM, Cognos, Business Objects, and other data warehouse leaders. Although some of these may have product specific information, they have the latest and up to date information on techniques that you can use for DW 2.0.
3 of 3 people found the following review helpful
2.0 out of 5 stars Pretty disappointing 8 Sep 2009
By Maciek - Published on Amazon.com
Some ideas found in this book were pretty interesting and I am looking forward to put them into use in my workplace. However, a 50 page-long "DW 2.0" chapter of some other book would be a much better place to put entire content of this book into.

The major disappointment comes from lack of medium-level details I would expect. Most ideas are described from a helicopter-view perspective and are being repeated again and again and again through 400 pages.
5.0 out of 5 stars Five Stars 16 July 2014
By James Rodriguez - Published on Amazon.com
Format:Kindle Edition|Verified Purchase
Great book. Inmon has a strong delivery and easy to follow ideas.
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