What is a Slowly Changing Dimension, and the Logic in Implementation

In business, one of the most important resources you need to manage is time; you have only X number of hours in a day in which you have to complete your tasks. This is especially true when you are working in a service industry where you have to complete all your routine tasks plus any additional chores that may arise from some customers requiring impromptu services. But time is not just something that affects you, it also affects your data. What is a slowly changing dimensions, and the logic in implementation.

When working with your data in a data warehouse, you might assume that most dimensions of your database stay the same. Sometimes, what appears to be a static dimension is actually a slowly changing dimension or SCD. An SCD is marked by the fact that, unlike sales-related events that might accumulate new entries over time, there can theoretically only be a single value for this dimension. For example, there can only be one customer address, right? But what happens when he/she moves? How do you track it, now that the value in the ‘Address’ dimension has changed? How do you keep the new address linked to all the activities linked to the previous address? The answer is to use one of the three types of SCD update actions.

In a data warehouse environment, users perform either Online Transaction Processing (OLTP: insertion, update, deletion) or Online Analytical Processing (OLAP: data retrieval for decision support). Update performance, query performance, and schema simplicity are essential for the efficient use and maintenance of a data warehouse. To achieve this, data is organized in a dimensional model called a star schema. In the star schema, the fact table is at the center surrounded by dimension tables.

A typical star schema diagram is as shown below:

slowly changing dimensions

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