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I am currently involved with a start-up for-profit graduate and undergraduate educational project.

By
  • Joe Oates, Sid Adelman, Clay Rehm, Scott Howard, Nancy Williams
Published
  • February 03 2003, 1:00am EST

 

 

Q:

I am currently involved with a start-up for-profit graduate and undergraduate educational project (www.northfacelearning.com). I feel pretty good about my ability to come up with materials and books for intro and advanced database courses. I can at least make the students into good SQL programmers, if nothing else. But I want part of the advanced database course to include data warehousing ("Now kids, forget everything you learned about OLTP databases...") and my questions are: 1) Anyone have textbooks to recommend? In fact, are there any textbooks? 2) What topics should be part of a curriculum? 3) Do non-vendor specific teaching materials exist?

A:

Sid Adelman's Answer: You might want to consider the following Web sites and books for your class:

Web Sites

Architecture, Colin White and Mike Fergeson
www.databaseassociates.com

Data Administration
www.EWSolutions.com/newsletter.asp
www.tdan.com

Database and Data Warehouse Information Exchange
www.searchdatabase.com

Data Quality, Larry English
www.infoimpact.com

Data Mining, Herb Edelstein
www.twocrows.com

Data Warehouse . general information
www.datawarehouse.com
www.dwinfocenter.org

The Data Warehouse Institute
www.dw- institute.com

Data Warehouse Journals
www.dmreview.com
www.intelligententerprise.com

Database issues and solutions
www.Dbazine.com

DCI.s CRM community
www.crmcommunity.com

Douglas Hackney, Enterprise Group, Ltd.
www.egltd.com

Jill Dyche, Baseline Consulting Group
www.baseline- consulting.com

Enterprise Information Architecture
www.methodfocus.com

ETL Tool Comparison
http://www.ewsolutions.com/research_paper.asp

Bill Inmon
www.billinmon.com

Sean Ivoghli, The Data Warehouse Consulting Group
www.dwcg.com

Chuck Kelley
www.excellenceindata.com

Ralph Kimball
www.rkimball.com

Meta Data - David Marco, Enterprise Warehousing Solutions
www.ewsolutions.com

Meta Data Tool Comparison Study
http://www.ewsolutions.com/research_paper.asp

Pieter Mimno, tool comparisons
www.mimno.com

Larissa Moss
www.methodfocus.com

Multidimensional, Nigel Pendse and Richard Creeth
www.olapreport.com

Tools/Products
www.dsstar.com
www.itoolbox.com

Books

Adelman, Sid, and Larissa Moss. Data Warehouse Project Management. Boston, MA: Addison Wesley, 2000.

Adelman, Sid, Joyce Bischoff, Jill Dyche, Douglas Hackney, Chuck Kelley, Sean Ivoghli, David Marco, Larissa Moss, and Clay Rehm. Impossible Data Warehouse Situations: Solutions from the Experts. Boston, MA: Addison Wesley, 2002.

Barquin, Ramon, and Herb Edelstein. Building, Using, and Managing the Data Warehouse, Upper Saddle River, New Jersey: Prentice Hall, 1997.

Barquin, Ramon, and Herb Edelstein. Planning and Designing the Data Warehouse, Upper Saddle River, New Jersey: Prentice Hall, 1997.

Berry, Michael J.A., and Gordon Linhoff. Mastering Data Mining: The Art and Science of Customer Relationship Management, New York: John Wiley & Sons, 1999.

Berry, Michael J.A., and Gordon Linhoff. Mastering Data Mining Techniques for Marketing, Sales and Customer Support, New York: John Wiley & Sons, 1997.

Bischoff, Joyce, and Ted Alexander. Data Warehouse: Practical Advice from the Experts, Upper Saddle River, NJ: Prentice Hall, 1997.

Brackett, Michael H. Data Resource Quality, Reading, Massachusetts: Addison Wesley, 2000.

Brackett, Michael H. Data Warehouse Challenge: Taming Data Chaos, New York: John Wiley & Sons, 1996.

Cabena, Peter, Pablo Hadjinian, Rolf Stadler, Jaap Verhees, and Allesandro Zanasi. Discovering Data Mining from Concept to Implementation, Upper Saddle River, NJ: Prentice Hall, 1997.

Devlin, Barry and Lynne Doran Cote. Data Warehouse: From Architecture to Implementation, Reading, Massachusetts: Addison Wesley, 1996.

Dyche, Jill. The CRM Handbook: A Business Guide to Customer Relationship Management, Reading, Massachusetts: Addison Wesley, 2001.

Dyche, Jill. E-Data: Turning Data into Information with Data Warehousing, Reading, Massachusetts: Addison Wesley, 2000.

English, Larry P. Improving Data Warehouse and Business Information Quality. New York: John Wiley & Sons, 1999.

Edelstein, Herb. Data Mining: Products and Markets. Potomac, MD: Two Crows Corp., 1997.

Hackney, Douglas. Understanding and Implementing Successful Data Marts, Reading, Massachusetts: Addison Wesley, 1997.

Hoberman, Steve, Data Modeler.s Workbench: Tools and Techniques for Analysis and Design, New York: John Wiley & Sons, 2002.

Imhoff, Claudia, Lisa Loftis, and Jonathan G. Geiger. Building the Customer-Centric Enterprise. New York: John Wiley, 2001.

Inmon, W.H. Building the Data Warehouse, 3rd Edition, New York: John Wiley & Sons, 2002.

Inmon, William H., Claudia Imhoff, and Greg Battas. Building the Operational Data Store. New York: John Wiley, 2001

Inmon, W.H., Claudia Imhoff and Ryan Sousa. Corporate Information Factory, New York: John Wiley & Sons, 1997

Inmon, W.H., John A. Zachman, and Jonathan G. Geiger. Data Store, Data Warehousing and the Zachman Framework ,New York: McGraw Hill, 1997/

Inmon, W.H., J.D. Welch, and Katherine L. Glassey. Managing the Data Warehouse, New York: John Wiley & Sons, 1997.

Kelley, Sean. Data Warehousing: The Route to Mass Customization. New York: John Wiley, 1966

Kimball, Ralph. The Data Warehouse Lifecycle Toolkit: Expert Methods for Designing, Developing and Deploying the Data Warehouse, New York: John Wiley & Sons, 1998.

Kimball, Ralph. The Data Warehouse Toolkit, New York: John Wiley & Sons, 1996.

Marco, David. Building and Managing the Meta Data Repository, New York: John Wiley & Sons, 2000.

Swift, Ronald S. Accelerating Customer Relationships, Upper Saddle River, NJ: Prentice Hall.

Scott Howard's Answer: I can emphasize with you. I faced the same dilemma four years ago after convincing IBM that we should develop non-vendor specific DW training for our Global Services consultants and our customers; the justification being that if we teach folks what works then vendor hype and products are exposed to well-qualified scrutiny. It's like a national clothing chain claims, "an educated consumer is our best customer." I then led the effort to develop our series of vendor neutral DW offerings, DW110, DW120 and DW130. That may be hard to believe, vendor neutral from IBM, but it is very true for this specific training. Well that's not to the point of your question, but I had to present some justification so my response is not viewed as a vendor specific response.

What textbook do I recommend? It's too easy to recognize that the majority of our industry either follows Bill Inmon or Ralph Kimball then reference their texts. Most practitioners recognize that the best approach to DW resides somewhere between their two teachings. I always recommend Barry Devlin's Data Warehouse from Architecture to Implementation. It's a pragmatic approach for those already familiar with OLTP systems presenting the key differentiaters between OLTP and DW systems in a direct and concise manner. My students tell me that it's still used by many major universities as their DW text.

What topics should be included? Well I just shared that I went through the same process four years ago and believe the courses we developed and refined over those years are still very relevant and they are very well receive by students. Go to the IBM training web site (ibm.com/training) and call up the course descriptions for course DW110: Building The Data Warehouse. You'll find it under your country's Business Intelligence curriculum listed as a data warehouse methodology course. The course description may server as a template for designing your training solution. I can provide you a table of contents if you.re interested. Good luck.

Clay Rehm's Answer: There are many good data warehouse books from authors such as Kimball, Inmon and others. As far as a good data design book, I would recommend Database Systems by Connolly and Begg from Addison Wesley Publishing.

If you are indeed serious about data architecture and database design, I would strongly urge you to join the Data Management Organization (www.DAMA.org). They have many resources at their disposal regarding data and the proper design of it. Their whole focus is data management.

Examples of topics should include:

  • Your users are not DBAs, don't expect them to be
  • Data design to make SQL easy and fun
  • Joins - let's keep them to a minimum
  • High performance design
  • High performance regular maintenance and tuning

Nancy Williams' Answer: Non-vendor specific courses/teaching materials that cover the topic of data warehouse data modeling are offered by The Data Warehousing Institute (TDWI). As an instructor for one of these courses, I believe that the course does a good job of comparing and contrasting the differences between OLTP and data warehousing environments and the resulting differences in the data structures and optimization techniques used to support these environments. Additionally, the course addresses a very important related data warehousing topic - the changing role of the DBA.

Joe Oates' Answer: There are several textbooks available, but in my opinion, there are three that are easy reads and cover most of the concepts. They are: 1) The Data Warehouse Toolkit (Second Edition) by Ralph Kimball; 2) Building the Operational Data Store by W. H. Inmon, Claudia Imhoff and Greg Battas; 3) Data Warehouse Design Solutions by Christopher Adamson and Michael Venerable. There are also several books by Inmon that are geared more to the enterprise than the three mentioned above and would be good sources after having read these three.

As to the topics, you should be able to develop them from the contents of the books. Some topics that I have seen to be difficult for many development team members to comprehend include: the differences between database sizes that they have experienced in OLTP systems and the very large database (VLDB) issues; the difficulty in taking the basic principles and expanding them to an enterprise or an enterprise made up of several enterprises; and the amount of work required to extract, transform and load (ETL) data from, in some cases, more than 100 sources to an integrated enterprise data warehouse.

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