Building the Data Warehouse

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There is then a real difference between operational reporting and DSS reporting. Operational reporting should always be done within the confines of the operational environment.

The Operational Window of Opportunity

In its broadest sense, archival represents anything older than right now. Thus, the loaf of bread that I bought 30 seconds ago is archival information. The only thing that is not archival is information that is current.

The foundation of DSS processing—the data warehouse—contains nothing but archival information, most of it at least 24 hours old. But archival data is found elsewhere throughout the architected environment. In particular, some limited amounts of archival data are also found in the operational environment.

In the data warehouse it is normal to have a vast amount of archival data—from 5 to 10 years of data is common. Because of the wide time horizon of archival data, the data warehouse contains a massive amount of data. The time horizon of archival data found in the operational environment—the “operational window” of data—is not nearly as long. It can be anywhere from 1 week to 2 years.

The time horizon of archival data in the operational environment is not the only difference between archival data in the data warehouse and in the operational environment. Unlike the data warehouse, the operational environment’s archival data is nonvoluminous and has a high probability of access.

In order to understand the role of fresh, nonvoluminous, high-probability-of-access archival data in the operational environment, consider the way a bank works. In a bank environment, the customer can reasonably expect to find information about this month’s transactions. Did this month’s rent check clear? When was a paycheck deposited? What was the low balance for the month? Did the bank take out money for the electricity bill last week?

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