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Customer dimension table
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1011 1022 1302 1499
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Davis, Robert Nguyen, Tamara
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Rodriguez, 4/5/1972 MA Jason Johnson, Sue 3 /2 /1961 AZ Record for Sue in Dimension table product_ key 10119 quantity _ordered 5
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Orders fact table customer_ key 1499 BEFORE AFTER Customer dimension table customer_ key 1011 1022 1302 1499 customer_ id 1140400 3305300 7733300 9900011 customer_ name Davis, Robert Nguyen, Tamara date_of_ birth state day_key 2322
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Rodriguez, 4/5/1972 MA Jason Johnson, Sue 3/2/1971 AZ Record overwritten with new date of birth quantity _ordered 5 Old fact references updated dimension row
Orders fact table customer_ key 1499 day_key 2322 product_ key 10119
Figure 3-7
A type 1 change: before and after
Preexisting Facts Have a New Context
A type 1 change has an important effect on facts, one that is often overlooked. When a record is updated in a dimension table, the context for existing facts is restated. This effect can give rise to confusion. An example is provided by the change in Sue s date of birth. The before picture in the top half of Figure 3-7 shows an order in the fact table for Sue. It was placed on whatever
Part I
customer_ key
customer_ id
customer_ name
date_of_ birth
state
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PART I Fundamentals
day is represented by day_key 2322. If you were to run a query that grouped orders for that day by the customer s date of birth, Sue s order would be grouped together with other customers born on 3/2/1961. Suppose that someone created a report to do just that and printed out the results. Now, move forward to a point in time after the type 1 change has taken place. The bottom half of Figure 3-7 shows that Sue is now listed with a date of birth of 3/2/1971. You run the same report taking all orders from the day represented by day_key 2322 and grouping them by customers birth dates. Your report will count Sue s past order with people born on 3/2/1971, while the one printed previously will count it among people born on 3/2/1961. The reports have different figures, even though they both describe activity for the same day in the past. TIP Use type 1 changes carefully. They restate the context for associated facts. Confusion can be minimized by educating systems analysts and business users. Steps can be taken to minimize the confusion caused by type 1 changes. Systems analysts responsible for supporting the data warehouse users must be aware of this phenomenon so they are prepared to address confusion. Developers of reports can place the query execution date within the report footer or cover page, signaling to readers the date as of which the report was current. Any reports that are pre-run and stored for users can be automatically updated on a regular basis so users do not unintentionally access stale data. For many organizations, though, the preferred approach is to avoid the type 1 change.
History of Dimension Is Not Maintained
In addition to restating the context of facts, the type 1 change fails to track the history of the dimension itself. No change history of the data element is maintained in the star schema. In a Corporate Information Factory architecture, the data warehouse may maintain this history in the enterprise data warehouse repository.
Type 2 Change
Most operational changes are dealt with in a star schema as type 2 changes. The type 2 change preserves the history of facts. Facts that describe events before the change are associated with the old value; facts that describe events after the change are associated with the new value.
Inserting a New Dimension Row
The second method for responding to a change in source data is to insert a new record into the dimension table. Any previously existing records are unchanged. This type 2 response preserves context for facts that were associated with the old value, while allowing new facts to be associated with the new value. Sue Johnson s change of address provides an example where a type 2 change can be useful. Recall from Figure 3-6 that over the years, Sue has lived in Arizona, and later in California. She may have placed some orders while living in Arizona and other orders while living in California. A type 1 response to Sue s change in address would have the undesirable side effect of restating the context for orders that Sue placed before she moved. They would become associated with California, even though Sue lived in Arizona at the time.
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