Databases Reference
In-Depth Information
table. You can also query in reverse. If you want to know the price of
gasoline when gasoline sales transactions occur at 11:00 p.m., then you
start with the “gasoline sales transactions” table. You query the “gasoline
sales transactions” table where the time of day is 11:00 p.m., then join the
“gasoline sales transactions” table to the “price of gasoline” table by join-
ing on the date. The result set will include multiple rows from the “gaso-
line sales transactions” table, each joined with a r ow from the “price
of gasoline” table for the same date. Assuming gasoline sales transac-
tions at 11:00 p.m. occurred on multiple days, that result set will include
multiple days of gasoline sales transactions and different gasoline prices,
but both will correspond with each other by the date. Time Variance
between the price of gasoline and gasoline sales transactions allows the
query result set to join them together, even when the result set includes
multiple dates.
In this way, Time Variance means that Time is the key that joins rows
in a f act table to rows in dimension tables. The business relevance of
Time Variance is that it means the data warehouse can join transaction
data with enterprise data that was in effect at the time of the transaction.
For example:
• In a Telecommunications data warehouse, a phone call that occurred
on Jan. 24, 2010, can be joined with…
• he price of a phone call as of Jan 24, 2010
• he president of the phone company on Jan. 24, 2010
• he aἀ liate contract in efect on Jan. 24, 2010
• he Consumer Price Index as of Jan. 24, 2010
• he baud rate of the telecommunications network on Jan. 24, 2010
• he Wimbledon Men's champion as of Jan. 24, 2010
• Etc. etc. etc. as of Jan. 24, 2010
• In a restaurant data warehouse, a dining room meal that was served
on March 18, 2011, can be joined with…
• he price of the appetizer on March 18, 2011
• he price of the entrée on March 18, 2011
• he restaurant manager on March 18, 2011
• he price of tomato sauce on March 18, 2011
• he price of meat on March 18, 2011
• he president of the United States on March 18, 2011
• he Super Bowl champion as of March 18, 2011
• Etc. etc. etc. as of March 18, 2011
