Letting the Users Sleep, Part 1
Nine decision in the design of a data warehouse
December, 1996 (Vol 9, Num 13) Page 12

Causal (Not Casual) Dimensions
Consider causal dimensions when you want your data warehouse to be more informative
November, 1996 (Vol 9, Num 12) Page 16

It's Time for Data Compression
Data warehouses are ideal targets for the benefits of data compression
October, 1996 (Vol 9, Num 11) Page 18

Factless Fact Tables
Two types of useful fact tables contain no facts at all
September, 1996 (Vol 9, Num 10) Page 16

Dealing with Dirty Data
The science of maintaining clean data in your warehouse, and why nobody talks about it (Feature Article)
September, 1996 (Vol 9, Num 10) Page 55

Dangerous Preconceptions
Discovering the liberating truth that can lead to a successful data warehouse project
August, 1996 (Vol 9, Num 9) Page 14

Aggregate Navigation With (Almost) No Metadata
Design Requirements for Aggregate Environments (Feature Article)
August, 1996 (Vol 9, Num 9) Page S15

Automating Data Extraction
Ralph reviews Carleton Passport, ETI Extract, and Prism Warehouse Manager
July, 1996 (Vol 9, Num 8) Page 16

Mastering Data Extraction
Steps you must complete when migrating legacy data into a data warehouse
June, 1996 (Vol 9, Num 7) Page 14

Monster Dimensions
Design solutions for handling changes in very large dimensions
May, 1996 (Vol 9, Num 5) Page 14

Slowly Changing Dimensions
Unlike OLTP systems, data warehouses can track historical data
April, 1996 (Vol 9, Num 4) Page 18

Drilling Down, Up, and Across
Understanding the vocabulary of navigating dimensions
March, 1996 (Vol 9, Num 3) Page 14

SQL Roadblocks and Pitfalls
Exploring some of the more glaring limitations of SQL
February, 1996 (Vol 9, Num 2) Page 14

The Problem with Comparisons
A freshman in Business needs a Ph.D. in SQL, Part 1
January, 1996 (Vol 9, Num 1) Page 16