1. Data Modeler Tool Kit
THE DENORMALIZATION SURVIVAL GUIDE - PART 1
This the first of two articles on the Denormalization Survival Guide, adapted from Chapter 8 of
Steve Hoberman's book, the Data Modeler's Workbench.
This first article focuses on the dangers of denormalization and introduces the Denormalization Survival Guide, which is a question-and-answer approach to applying denormalization to our data models.
http://www.tdan.com/i020fe02.htm
modify link | report broken link
|
2. How to Learn Data Modeling
Logical data and process modeling are two essential first steps in the development of information systems, for both transaction processing and decision support (data
warehousing).
http://www.tdan.com/i028ht01.htm
modify link | report broken link
|
3. Data Modeling in the Government Information Factory
The data model is an intellectual roadmap to the contents of the government information factory. One of the essential design components of the Government Information Factory (GIF) is the data model. The data model is an intellectual roadmap to the contents. The data model is used for many purposes, such as -
http://www.b-eye-network.com/view/182
modify link | report broken link
|
4. Denormalization Survival Guide II
Denormalization Survival Guide, which is a question-and-answer approach to applying denormalization to our logical data models. This article will discuss the questions and answers that comprise this guide when modeling a
http://www.tdan.com/i021ht03.htm
modify link | report broken link
|
5. Business Rule Validation
Top 3 validations to correctly capturing business rules in your design “What do you find most difficult about modeling?” I was asked this question while walking briskly to my Data Modeling Workshop at the Boston TDWI World
Conference this last August.
http://www.tdan.com/i028fe01.htm
modify link | report broken link
|
10. "Competing on Analytics" by Professor Thomas H. Davenport.
Ask more. Learn more. Do more with your data! Many of our customers, including Amazon.com, Capital One, Cingular Wireless, Neiman Marcus and others, leverage their data to a competitive advantage. Visionary companies have built their businesses on their ability to collect, analyze and act on data. Learn more. Read "Competing on Analytics" by Professor Thomas H. Davenport.
http://www.netezza.com/netezza58/page.cfm
modify link | report broken link
|
|
 |
sponsored ad
Business Intelligence Network
Premier source for Business Intelligence, Data Warehousing, Business Performance Management and Data Quality News, Blogs, RSS Feeds and more
|
