In Type 1 Slowly Changing Dimension, the new information simply overwrites the original information. In other words, no history is kept.
In our example, recall we originally have the following table:
| Customer Key | Name | State |
| 1001 | Christina | Illinois |
After Christina moved from Illinois to California, the new information replaces the new record, and we have the following table:
| Customer Key | Name | State |
| 1001 | Christina | California |
Advantages:
- This is the easiest way to handle the Slowly Changing Dimension problem, since there is no need to keep track of the old information.
Disadvantages:
- All history is lost. By applying this methodology, it is not possible to trace back in history. For example, in this case, the company would not be able to know that Christina lived in Illinois before.
- Usage:
About 50% of the time.
When to use Type 1:
Type 1 slowly changing dimension should be used when it is not necessary for the data warehouse to keep track of historical changes.
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