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Data should be in a consistent state when it is extracted from the source system. More to the point, the information in a data warehouse represents a snapshot of corporate information, so that the user is looking at a single, consistent, version of the truth. Source data should be extracted only at a point where it represents the same instance of time as the extracts from the other data sources. For example, in a customer profiling data warehouse in the telecommunications sector (telco), it is illogical to merge the list of customers at 7 pm on Friday from a customer database with the customer subscription events up to 7 pm on Thursday from a customer events database.

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This would mean that we are likely to find customers for whom there are no associated subscriptions. This problem can be more complex, if the point at which operational data represents the same time period differs between systems. Continuing with the previous example, it is very possible that the customer database may not be updated to reflect new subscriptions until 3 hours after the close of business on the customer events system. This is why we typically have to wait until all the data sources are in line before we begin executing consistency checks. In order to ensure that the various tools, logic modules, and programs are executed in the correct sequence and at the correct time, a controlling mechanism is required to fire each module when appropriate.