Intelligent Enterprise Contributing Editor: THE KIMBALL GROUP The Kimball Group is the definitive source for education and consulting on the Kimball dimensional data warehousing and business intelligence (DW/BI) methods. Each Kimball Group member has focused on DW/BI for a minimum of 15 years. They collectively authored The Data Warehouse Lifecycle Toolkit, 2nd Edition (Wiley 2008). Visit www.kimballgroup.com to learn more about the Kimball Group and Kimball University.
Ralph Kimball
Founder of the Kimball Group, Ralph has been the DW/BI industry's thought leader on the dimensional approach since the mid 1980s. He has trained more than 10,000 IT professionals and sold more than 250,000 copies of his Toolkit books. ralph@kimballgroup.com
Warren Thornthwaite
Warren began his DW/BI career in 1980. He teaches DW/BI project lifecycle and Microsoft data warehousing classes for Kimball University, and co-authored The Microsoft Data Warehouse Toolkit (Wiley 2006). warren@kimballgroup.com . 
Joy Mundy
Joy has worked in the DW/BI industry since 1992, including a stint at Microsoft's SQL Server product development organization. She co-authored The Microsoft Data Warehouse Toolkit (Wiley 2006). joy@kimballgroup.com |
Margy Ross
Margy is President of the Kimball Group and teaches dimensional modeling and DW/BI project lifecycle classes through Kimball University. She co-authored The Data Warehouse Toolkit, 2nd Edition (Wiley 2002). margy@kimballgroup.com
Bob Becker
Bob has focused on DW/BI solutions since 1989, including extensive work with health care industry clients recently. He co-teaches Kimball University's ETL Architecture class. bob@kimballgroup.com |
ARTICLES BY THE KIMBALL GROUP
FUNDAMENTALS/FAVORITES
Kimball University: Microsoft SQL Server Comes of Age for Data Warehousing
With new compression, partitioning and star schema optimization features, Microsoft's SQL Server 2008 has caught up with the state of the industry for data warehousing. Here's why these three features are crucial for scalability and performance on any platform.
Kimball University: Three Ways to Capture Customer Satisfaction
What satisfies, or doesn't satisfy, the customer? Use one of these three powerful data warehouse design approaches to gauge satisfaction and help marketers tease out the customer experience behind various behaviors.
Kimball University: Think Critically When Applying Best Practices
Best practices are precision tools that should be wielded precisely and skillfully. This article describes five best practices drawn from the Kimball Method that often are described incorrectly.
Integration for Real People
These step-by-step guidelines will help dimension managers and users drill across disparate databases.
The Matrix: Revisited
This Swiss Army knife for BI and data warehousing supports planning, integration and stewardship.
DIMENSIONAL MODELING/DATA ARCHITECTURE
Keep to the Grain in Dimensional Modeling
When developing fact tables, aggregated data is NOT the place to start. To avoid "mixed granularity" woes including bad and overlapping data, stick to rich, expressive, atomic-level data that's closely connected to the original source and collection process.
Think Critically When Applying Best Practices
Best practices are precision tools that should be wielded precisely and skillfully. This article describes five best practices drawn from the Kimball Method that often are described incorrectly.
Pick the Right Approach to MDM
It's time to migrate master data management upstream to an integration hub or, ideally, an enterprise MDM system. And if you have yet to do anything about data consistency, take these four steps toward integration and stewardship.
ETL/DATA QUALITY
Kimball University: Should You Use An ETL Tool?
You can still hand-code an extract, transform and load system, but in most cases the self-documentation, structured development path and extensibility of an ETL tool is well worth the cost. Here's a close look at the pros and cons of buying rather than building..
Subsystems of ETL Revisited
These 34 subsystems cover the crucial extract, transform and load architecture components required in almost every dimensional data warehouse environment. Understanding the breadth of requirements is the first step to putting an effective architecture in place.
Data Warehouse Dining Experience
Managing a data warehouse is similar to running a restaurant.
Surrounding the ETL Requirements
Before designing an ETL system, you must first understand all of your business needs.
BI/ANALYTICS
Building a Foundation for Smart Applications
Off-the-shelf apps may offer built-in analytics, but the best approach to supporting operational decisions is to rely on a solid data warehouse that cleans, integrates.
Building and Delivering BI Reports
Here's how to build, test and deploy standard reports for key business processes.
Standard Reports: Basics for Business Users
How to plan, prioritize and design the primary vehicle for delivering business intelligence.
PROJECT LIFECYCLE
Educate Management to Sustain DW/BI Success
Data warehousing and business intelligence success cannot be taken for granted. You must create an ongoing education and communication program to maintain your success and extend it across the organization.
Overcoming Obstacles when Gathering Requirements
How do you cope with "abused users, overbooked users, comatose users, clueless users" and "know-it-all users" during the requirements-gathering stage of a data warehouse/BI project? Kimball group offers its advice for proactively working with (or around) the uncooperative, unavailable, uninsightful and irrepressible types who sometimes make it hard to know just what the business needs.
Think Critically when Applying Best Practices
Best practices are precision tools that should be wielded precisely and skillfully. This article describes five best practices drawn from the Kimball Method that often are described incorrectly.
RELATED TECHNOLOGIES
Dimensional Relational vs. OLAP
The choice between deploying relational tables or OLAP cubes is not a trivial matter. Weigh these 34 pros and cons of each approach early in the design of your extract-transform-load system.
Pick the Right Approach to MDM
It's time to migrate master data management upstream to an integration hub or, ideally, an enterprise MDM system. And if you have yet to do anything about data consistency, take these four steps toward integration and stewardship.
|
KIMBALL UNIVERSITY
June 24-27, 2008, Seattle, WA
ETL Architecture in Depth
July 15-18, 2008, San Jose, CA
Kimball University: Microsoft Data Warehouse In Depth
July 22-25, 2008, Chicago
Kimball University: Data Warehouse Lifecycle in Depth
August 12-15, 2008, San Francisco
Kimball University: Dimensional Modeling In Depth
September 16-19, 2008, Minneapolis
Kimball University: Microsoft Data Warehouse In Depth
September 23-26, 2008, New York
Kimball University: Data Warehouse Lifecycle in Depth
September 30-October 3, 2008,Washington D.C. (Arlington, VA)
Kimball University: Dimensional Modeling In Depth
October 6-9, 2008, New York
Kimball University: ETL Architecture in Depth
November 18-21, 2008, San Francisco
Kimball University: Data Warehouse Lifecycle in Depth
December 2-5, 2008, San Diego, CA
Kimball University: Dimensional Modeling In Depth
September 23-26, 2008, New York
Kimball University: Data Warehouse Lifecycle in Depth
December 2-5, 2008, Dallas
Kimball University: Microsoft Data Warehouse In Depth
December 8-11, 2008, San Diego, CA
Kimball University: ETL Architecture in Depth
-->
KIMBALL BOOKS
 The Data Warehouse Lifecycle Toolkit: Tools and Techniques for Designing, Developing, and Deploying Data Warehouses.
This new second edition by Ralph Kimball, Margy Ross, Bob Becker, Warren Thornthwaite and Joy Mundy provides a detailed guide to the data warehouse project, with no-nonsense techniques from inception through deployment. A supporting Web site offers a comprehensive set of useful templates and project tools.
 The Microsoft Data Warehouse Toolkit: With SQL Server 2005 and the Microsoft Business Intelligence Toolset
Warren Thornthwaite and Joy Mundy co-authored this guide to building a successful business intelligence system and its underlying data warehouse databases using Microsoft SQL Server 2005. They provide invaluable advice about designing, developing, deploying, and operating your Kimball Method data warehouse system on the Microsoft BI platform.
 The Data Warehouse ETL Toolkit: Practical Techniques for Extracting, Cleaning, Conforming, and Delivering Data
This book, written by Ralph Kimball and Joe Caserta, is a roadmap for planning, designing, building, and running the back room of a data warehouse. We expand the traditional ETL steps of extract, transform, and load into the more actionable steps of extract, clean, conform, and deliver, although we will resist the temptation to change ETL into ECCD. We build on a set of consistent techniques for delivery of dimensional data.
 The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling, 2nd Edition
Ralph Kimball and Margy Ross co-authored the second edition of Ralph’s classic guide to dimensional modeling. It provides a complete collection of modeling techniques, beginning with fundamentals and gradually progressing through increasingly complex real-world case studies. With more than 60% new content, the book significantly enhances and expands upon the concepts and examples presented in the original Data Warehouse Toolkit.
|
|
|
|
