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The Data Warehouse Lifecycle Toolkit: Practical Techniques for Building Data Warehouse and Business Intelligence Systems
A thorough update to the industry standard for designing, developing, and deploying data warehouse and business intelligence systems The world of data warehousing has changed remarkably since the first edition of The Data Warehouse Lifecycle Toolkit was published in 1998. In that time, the data warehouse industry has reached full maturity and acceptance, hardware and software have made staggering advances, and the techniques promoted in the premiere edition of this book have been adopted by nearly all data warehouse vendors and practitioners. In addition, the term "business intelligence" emerged to reflect the mission of the data wrangling the data out of source systems, cleaning it, and delivering it to add value to the business. Ralph Kimball and his colleagues have refined the original set of Lifecycle methods and techniques based on their consulting and training experience. The authors understand first-hand that a data warehousing/business intelligence (DW/BI) system needs to change as fast as its surrounding organization evolves. To that end, they walk you through the detailed steps of designing, developing, and deploying a DW/BI system. You'll learn to create adaptable systems that deliver data and analyses to business users so they can make better business decisions.
672 pages, Paperback
First published August 13, 1998
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420 people want to read
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Displaying 1 - 17 of 17 reviews
December 2, 2018
actually read (most of) this book for an online class ~2008. Learned some things...
March 7, 2020
Read for a class.
March 12, 2020
Good information, but so very dry.
June 3, 2020
This is indeed one of the best books on Data Warehouse and Business Intelligence.
October 29, 2011
I believe I bought this book a week or two after it came out (January 2008) with the intention of reading it immediately. Unfortunately, life happens and I have no idea what came up but I’m sure it was good. And, to be honest, I’m somewhat happy that whatever it was did come up because this was a good time for me to read through this.
I started reading this book in 20 August 2011 and finished it 11 September 2011. Oddly enough, I started this just prior to being told that the data warehousing project that we are planning at my current employer may be coming along a bit more quickly than originally thought. As such, I’m ramping up on some refresher material and this was perfect for that need. (I’m also thinking that I’ll be refreshing my SSRS / SSAS and that I might take a stab at the MCITP 70-452 Business Intelligence Developer exam)
As some background information, I have read several other Kimball Group books, including:
The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling (Second Edition)
which is thoroughly dog-eared and highlighted; a rather rare occurrence for me.
The Data Warehouse ETL Toolkit: Practical Techniques for Extracting, Cleaning, Conforming and Delivering Data
The Microsoft Data Warehouse Toolkit: With SQL Server 2005 and the Microsoft Business Intelligence Toolset.
If you have read more than one of these books you will realize that there is a lot of material that overlaps between them but that each has its’ own focus. The focus of the Lifecycle Toolkit seemed to me to be on the project manager, or at least on giving an overview of the process as a whole. It seemed to me to be more of a “whet the appetite” with the ability to dive in more expansively through some of the other books referenced above. What The Data Warehouse Lifecycle Toolkit provided more than any of the others listed above was to give a good list of all of the tasks that will be required (or at least recommended) to complete a Data Warehouse project. I believe that a good portion of the text was set aside to drive home how much work is really involved and that this is not a trivial task. It continuously mentioned brining in the business, and having the project manager read through what was required in each of the major steps so that this could be conveyed back up the chain.
With that said, this book was a somewhat generic introduction to the topic at hand and no one topic was pursued in depth to the point that you would have all of the knowledge necessary to be an expert. However, it provided lots of great information relating to the relevant portions of the project, from preparing the project definition, to gathering the key players, to what is really necessary for the business requirements and how you can begin to put them together, etc. There is also lots of information relating to the dimensional modeling, the ETL subsystems, data profiling, data quality and the B.I. presentation layers.
As such, I’d recommend The Data Warehouse Lifecycle Toolkit to anyone looking to get involved in a Data Warehouse Project, particularly if you are going to be expected to be in a leadership role on the project. If you are to be involved as a data modeler or an ETL Developer and are a bit strapped for time it might be more advantageous to skip this volume and go straight to The Data Warehouse Toolkit followed by The Data Warehouse ETL Toolkit. (Alternately, you can start with the Microsoft Toolkit if that is the technology stack you will be using).
I started reading this book in 20 August 2011 and finished it 11 September 2011. Oddly enough, I started this just prior to being told that the data warehousing project that we are planning at my current employer may be coming along a bit more quickly than originally thought. As such, I’m ramping up on some refresher material and this was perfect for that need. (I’m also thinking that I’ll be refreshing my SSRS / SSAS and that I might take a stab at the MCITP 70-452 Business Intelligence Developer exam)
As some background information, I have read several other Kimball Group books, including:
The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling (Second Edition)
which is thoroughly dog-eared and highlighted; a rather rare occurrence for me.
The Data Warehouse ETL Toolkit: Practical Techniques for Extracting, Cleaning, Conforming and Delivering Data
The Microsoft Data Warehouse Toolkit: With SQL Server 2005 and the Microsoft Business Intelligence Toolset.
If you have read more than one of these books you will realize that there is a lot of material that overlaps between them but that each has its’ own focus. The focus of the Lifecycle Toolkit seemed to me to be on the project manager, or at least on giving an overview of the process as a whole. It seemed to me to be more of a “whet the appetite” with the ability to dive in more expansively through some of the other books referenced above. What The Data Warehouse Lifecycle Toolkit provided more than any of the others listed above was to give a good list of all of the tasks that will be required (or at least recommended) to complete a Data Warehouse project. I believe that a good portion of the text was set aside to drive home how much work is really involved and that this is not a trivial task. It continuously mentioned brining in the business, and having the project manager read through what was required in each of the major steps so that this could be conveyed back up the chain.
With that said, this book was a somewhat generic introduction to the topic at hand and no one topic was pursued in depth to the point that you would have all of the knowledge necessary to be an expert. However, it provided lots of great information relating to the relevant portions of the project, from preparing the project definition, to gathering the key players, to what is really necessary for the business requirements and how you can begin to put them together, etc. There is also lots of information relating to the dimensional modeling, the ETL subsystems, data profiling, data quality and the B.I. presentation layers.
As such, I’d recommend The Data Warehouse Lifecycle Toolkit to anyone looking to get involved in a Data Warehouse Project, particularly if you are going to be expected to be in a leadership role on the project. If you are to be involved as a data modeler or an ETL Developer and are a bit strapped for time it might be more advantageous to skip this volume and go straight to The Data Warehouse Toolkit followed by The Data Warehouse ETL Toolkit. (Alternately, you can start with the Microsoft Toolkit if that is the technology stack you will be using).
October 13, 2013
Kimball is considered one of the fathers of the data warehousing movement and among many consulting firms is considered the de-facto representation of reporting database infrastructure. This specific book details on a higher-level the step-by-step processes required for a successful implementation focusing on the business users and requirements, while laying common pitfalls in the ETL, data warehouse infrastructure and application-level. For IS professionals, I would consider this a must read and among BI consultants crucial in understanding the field.
I would consider this a more critical read than even Tufte and Few, who are considered the guru's of data visualization movement. The reason being that the infrastructure of any reporting effort underlies these later front-end developments. A most noted aspect of this book is it's heavy emphasis on the business need, the requirements for reporting and making sure you have strong executive support. This is too be expected when dealing with an abstract concept like data analysis and reporting, which is often strongly correlated with interpretation and the ability to act. As one can state, the ability to utilize this infrastructure is based in as much as the culture as the ability of those end-users to make the most of the tool.
I would recommend this to any aspiring IS professional as a theoretical foundation to their career and would even state that this is more important, from a management perspective, than knowing the actual data warehousing elements (which are important in and of themselves).
I would consider this a more critical read than even Tufte and Few, who are considered the guru's of data visualization movement. The reason being that the infrastructure of any reporting effort underlies these later front-end developments. A most noted aspect of this book is it's heavy emphasis on the business need, the requirements for reporting and making sure you have strong executive support. This is too be expected when dealing with an abstract concept like data analysis and reporting, which is often strongly correlated with interpretation and the ability to act. As one can state, the ability to utilize this infrastructure is based in as much as the culture as the ability of those end-users to make the most of the tool.
I would recommend this to any aspiring IS professional as a theoretical foundation to their career and would even state that this is more important, from a management perspective, than knowing the actual data warehousing elements (which are important in and of themselves).
May 30, 2012
This book was the textbook of my Data Warehousing class in the Cal State Fullerton MS in Information Technology program.
I can't say I cared much for some of the books we had in the program but this book was a notable exception. The book was great at explaining the steps and processes associated with data warehouse implementation using the Kimball lifecycle methodology. It also provided great insights into the program management elements necessary to successfully complete medium to large size data warehouse projects.
I can't say I cared much for some of the books we had in the program but this book was a notable exception. The book was great at explaining the steps and processes associated with data warehouse implementation using the Kimball lifecycle methodology. It also provided great insights into the program management elements necessary to successfully complete medium to large size data warehouse projects.
August 3, 2013
Read chapter 6 and 7 (partly). These two were the only ones relevant for my current job.
I have to say that if the reader hasn't got any hands-on experience with building datawarehouse databases this book (chapter 6) has way too few examples. You are required to deduct too much by yourself. I would prefer the author going slower and explaining in more detail.
I have to say that if the reader hasn't got any hands-on experience with building datawarehouse databases this book (chapter 6) has way too few examples. You are required to deduct too much by yourself. I would prefer the author going slower and explaining in more detail.
September 10, 2012
An exhaustive and exhausting read. This book covers all of the bases. I am not a beginner in this subject, and I still learned a lot. That being said a different editor could have shortened this book by 100 pages without losing any information.
December 11, 2008
Excellent Introduction to Data Warehousing. I have read this book and reference it. I would recommend using these principles with some of the methods Bill Inmon teaches.
Want to read
July 24, 2010I need to learn..
March 19, 2014
Recommended by client. For those informally trained in data structure, this is the book you need to put theory with what you're likely practicing professionally already.
February 15, 2015
good read
May 3, 2018
The first "true" book about data warehouses I read a few years ago. Still one on my reference books.
Read
February 13, 2016Starstruck...
Displaying 1 - 17 of 17 reviews