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Data Quality Rules: Rules for Event Histories
April 2008
Arkady Maydanchik

Time is arguably the most important aspect of our life. We are surrounded by calendars and watches, and rare is the activity that does not involve time. When my son entered elementary school, his life became a collection of timestamps and time intervals: school schedule, soccer schedule, play date, time to do homework, TV time, time to play video games, time to go to bed, number of days until Christmas and to the next vacation, and even the number of years left to accumulate college funds. And it stays that way for an entire life, except for rare Hawaii vacations.

This phenomenon stays true in the databases we build. Much of the data is time-stamped, and the absolute majority of the database entities contain histories. In the previous article (Data Quality Rules: Rules for Historical Data in the January 2008 issue of the IAIDQ newsletter) we discussed data quality rules for simple value histories. In this article we will discuss event histories.

In the fourth installment of his series of book excerpts, Arkady Maydanchik demonstrates how we can derive data quality rules from event dependencies, conditions, and constraints.