Customer Reviews

Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications

5 star:		(13)
4 star:		(7)
3 star:		(1)
2 star:		(0)
1 star:		(1)

 

 

Very action oriented. The prose is concise and to the point. A key feature is that at the start of each chapter is a ticklist of action items to do or at least be aware of, for that chapter's topic. This may have value to you, from a management viewpoint. Also similarly useful are the extensive tables at the back of the book, that complement the ticklists.

For me, the most relevant sections were those describing metadata and how this is commonly defined and used by people in the data mining/business intelligence community. I enjoyed the description of a metadata repository/silo as a navigation tool.

The book is readily accessible to a nontechnical manager. There is little mathematical jargon, and there are clear explanations of common data mining techniques. Enough so that you can converse intelligently with personnel in that field. A strength of the book is that is lets you understand and direct a technical team, in a top-down fashion, driven by business imperatives, rather than by technical capabilities.

It is refreshing to read a book that presents in-depth techniques for developing a BI application from cradle to grave in a continuous evolutionary process. Various matrices and WBS samples in Part II of the book serve as a quick reference for iterative planning and delivering of decision-support systems.The authors have done a phenomenal job in integrating business, technical,and management aspects of a BI and decision-support system to present an exhaustive set of guidelines.

After working with numerous clients and having read Inmon's Building the Data Warehouse, Kimball's The Data Warehouse Lifecycle Toolkit as well as various BI white papers, I know that data ETL and data warehouses are a major part of any BI strategy. However, after reviewing the summary of over 20 BI related books, I found that the primary focus of many BI books is normally limited to data presentation and analytical layers only.This book is an exception .

I would recommend this book to expert as well as novice DW/BI professionals alike, who may be business users, data analysts, architects, project managers, statisticians,or executive stakeholders.

This book is impressive in its scope! Starting with the business justification of the project, Moss and Atre emphasize requirements, metadata, and extraction/transformation/ and load. In each chapter is a good overview, things to consider, relation to other steps of the plan, and a clear list of deliverables and the personnel (the roles) involved in each of the steps. Each chapter also offers rules of thumb that could only have been come from someone experienced with setting up a Business Intelligence Solution. Perhaps most important to a project manager tempted to cut out a step, is a warning about the risk of omitting the step.

Each chapter should NOT be thought of as an in-depth analysis of the topic (for example, there are just 4 pages discussing the star versus the snowflake schema when discussing database design), but rather as a map of the steps that need to be done. I was particularly impressed with the metadata discussions, which emphasize testing of the metadata repository, the role of metadata in navigation and context-sensitive-help at the element level, and the use of multiple sources to generate the metadata. The common emphasis on reviews, involvement of the business sponsors, and testing throughout the process was great! The discussion on three parallel development tracks seemed optimistic, as I was not sure that the application track is completely independent of the Extraction/transformation/load steps until the final implementation step. The book probably also should have emphasized security earlier in the process. This book offers a good plan, and I would be happy if our Business Intelligence projects followed the plan laid out here!!

This book is the perfect blend of project management techniques, application of the software development lifecycle framework, and decision support / business intelligence projects. As a project manager for data mart and decision support projects, I am using this book as a reference for making sure all the steps are covered in these types of projects. All areas are at least touched upon if not covered in greater detail. The authors do an excellent job in explaining many of the BI concepts, identifying steps to completion, and raising questions to consider in tailoring the success of these projects to your organization's circumstances. The deliverables and risks presented for each step fits nicely with the Project Management Institute's PMBOK framework and the tips at the back of the book are incredibly helpful.

This isn't a technical book that talks in detail about how to solve design problems. It's a book that tries to explain what a BI project is and why it is so complex.
Even if it isn't a book for developers, the target audience is very broad and includes dw architects, project managers and executives.
The book structure is well designed: each chapter covers a different stage of BI projects using the same structure which includes useful practical things like project flow charts, project roles and risks.
It is essentially a methodology with some technical details, but don't look in it for complete, in-depth technical discussions, or for innovative contents.
For example, dimensional modelling only takes two short paragraphs that are absolutely insufficient to teach a designer how to use it in practical situations.
Even with these limitations this is a good and useful book, and it's clear that the two authors (Shaku Atre e Larissa T. Moss) have a lot of experience and a good understanding of BI projects.

This is an excellent book and, more importantly, it's very useful. It's loaded with specifics and checklists on what to do and how to do it (it also tells you what not to do). It lays out the pitfalls and tells you how to avoid them. The stages and steps outlined in the book are very specific and the authors, with their wealth of experience, tell you how to implement a successful data warehouse. The work breakdown structure (the tasks you need to implement the data warehouse), the deliverables matrix, and entry and exit criteria for each step are very detailed and alone are worth the price of the book.

The book will give those responsible for a data warehouse the information they need to establish best practices within their own organization and will give these folks the ammunition and support to ask for the necessary resources to implement a data warehouse.

There are a number of business intelligence and data warehousing books out in the market today. Most of them have missed the concept of business intelligence road mapping. Larissa Moss and Shaku Atre have put together a great guideline for building a business intelligence system including the risks and pitfalls on every step of the way. In addition, the writers have clearly spent a lot of time researching the subject matter, as it is evident from the deep content as well as the extensive bibliography at the end of each chapter. In my opinion, BI is such a vast and complex process that such research raises the quality of the book as it is describing the experiences and opinions of not just the writers, but also a number of other researchers and experts who specialize in the various sub-fields of business intelligence.
I teach a Data Warehousing and BI Class in the Extension section of University of California in Los Angeles, and I will certainly use this book as the text for my class.

Most IT books are dry at best, and really boring at worst. Once again, Larissa Moss has provided a readable, helpful text dealing with a very complex topic. She and Shaku Atre present clear guidelines for seasoned project managers to follow in implementing decision support applications. I thought it was too late to teach an old dog new tricks, but I gathered several ideas that I plan to use on my next big project.

Every IT project manager should read this book. While it is intended for BI projects, the more traditional development projects could benefit from the wisdom shared.

Am currently in the process of executing a DW/BI project, my background is JAVA application Project management. This book has been great in getting me upto speed on the basic architecture and lingo of BI/DW.

Book lays out step by step the different parts to a DW. The front office, the back office, meta data repository. Highlights how DW/BI phases are different from other application dev phases. It doesn't go into how to do data modelling - for this get the lifecycle toolkit. But it gives a great overview of planning a BI/DW initiative. Much better than the pure Project Management books.
To get a complete picture I'd use this book along with the Toolkit book.

I purchased this book after reading a lot of the user reviews from this site. After giving the book a read, I have to admit that the ratings are well deserved. For starters, I was worried about two things

a) The book was published almost a decade ago. With the changing landscape in the BI industry, I wasn't sure if the content was still relevant.
b) I have been in the BI industry for 13 years and wasn't sure if I will learn anything new from this book

If you have the similar concerns as the ones listed above then you have not much to fear. In my opinion, the book is more process focused than technology focused. This made the book weather some of the changes in the BI landscape. It does not talk about Agile/SCRUM etc as these have gained momentum in the last few years. However, the book talks about the iterative nature of BI and the mindset required to go through a BI initiative. IT walks the user through the areas that are critical to the success of a BI initiative (Standards, governance, common metadata definitions) and how to draw visibility to these and other aspects of the initiative.

From a Project management perspective, it walks you through the overall WBS and helps you understand what activities are super critical, the order of execution, the degree of parallelism and the kind of resources that should be in your project

Couple of areas that I feel the book falls short of are

a) The process of estimation is a key component of a BI initiative. The book loosely touches on this; however does not go into to much detail on when it should be done and at what level. For instance in the Cost-Benefit analysis sections it talks about drawing out costs from "IT", but how does one go about getting cost without knowing enough about the high level data manipulations needed especially since that forms 80% of the development effort. A specific step to call this out in more detail would have helped.

b) The book has a lot of detail. It is a primer of sorts. Therefore, a CD with chapters in an electronic format would have helped us refer to key sections often. The included CD only contains the WBS.


Other than that a good value add.