Building the Data Warehouse

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The operational environment of a bank, then, contains very detailed, very current transactions (which are still archival). Is it reasonable to expect the bank to tell the customer whether a check was made out to the grocery store 5 years ago or whether a check to a political campaign was cashed 10 years ago? These transactions would hardly be in the domain of the operational systems of the bank. These transactions very old, and so the has a very low probability of access.

The operational window of time varies from industry to industry and even in type of data and activity within an industry.

For example, an insurance company would have a very lengthy operational window—from 2 to 3 years. The rate of transactions in an insurance company is very low, at least compared to other types of industries. There are relatively few direct interactions between the customer and the insurance company. The operational window for the activities of a bank, on the other hand, is very short— from 0 to 60 days. A bank has many direct interactions with its customers.

The operational window of a company depends on what industry the company is in. In the case of a large company, there may be more than one operational window, depending on the particulars of the business being conducted. For example, in a telephone company, customer usage data may have an operational window of 30 to 60 days, while vendor/supplier activity may have a window of 2 to 3 years.

The following are some suggestions as to how the operational window of archival data may look in different industries:

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