Slowly altering dimension (SCD) is an information warehousing idea coined by the superb Ralph Kimball. The SCD idea offers with shifting a selected set of knowledge from one state to a different. Think about a human sources (HR) system having an Worker desk. As the next picture exhibits, Stephen Jiang is a Gross sales Supervisor having ten gross sales representatives in his group:

At the moment, Stephen Jiang received his promotion to the Vice President of Gross sales function, so his group has grown in measurement from 10 to 17. Stephen is similar individual, however his function is now modified, as proven within the following picture:

One other instance is when a buyer’s handle modifications in a gross sales system. Once more, the client is similar, however their handle is now completely different. From an information warehousing standpoint, now we have completely different choices to take care of the info relying on the enterprise necessities, main us to several types of SDCs. It’s essential to notice that the info modifications within the transactional supply techniques (in our examples, the HR system or a gross sales system). We transfer and remodel the info from the transactional techniques by way of ETL (Extract, Transform, and Load) processes and land it in an information warehouse, the place the SCD idea kicks in. SCD is about how modifications within the supply techniques replicate the info within the information warehouse. These sorts of modifications within the supply system don’t occur fairly often therefore the time period slowly altering. Many SCD sorts have been developed over time, which is out of the scope of this publish, however to your reference, we cowl the primary three sorts as follows.

SCD sort zero (SCD 0)

With any such SCD, we ignore all modifications in a dimension. So, when an individual’s residential handle modifications within the supply system (an HR system, in our instance), we don’t change the touchdown dimension in our information warehouse. In different phrases, we ignore the modifications inside the information supply. SCD 0 is additionally known as mounted dimensions.

SCD sort 1 (SCD 1)

With an SCD 1 sort, we overwrite the outdated information with the brand new. A superb instance of an SCD 1 sort is when the enterprise doesn’t want the client’s outdated handle and solely must preserve the client’s present handle.

SCD sort 2 (SCD 2)

With any such SCD, we preserve the historical past of knowledge modifications within the information warehouse when the enterprise must preserve the outdated and present information. In an SCD 2 state of affairs, we have to keep the historic information, so we insert a brand new row of knowledge into the info warehouse at any time when a transactional system modifications. A change within the transactional system is likely one of the following:

• Insertion: When a brand new row inserted into the desk
• Updating: When an present row of knowledge is up to date with new information
• Deletion: When a row of knowledge is faraway from the desk

Let’s proceed with our earlier instance of a Human Useful resource system and the Worker desk. Inserting a brand new row of knowledge into the Worker dimension within the information warehouse for each change inside the supply system causes information duplications within the Worker dimensions within the information warehouse. Subsequently we can not use the EmployeeKey column as the first key of the dimension. Therefore, we have to introduce a brand new set of columns to ensure the distinctiveness of each row of the info, as follows:

• A brand new key column that ensures rows’ uniqueness within the Worker dimension. This new key column is solely an index representing every row of knowledge saved in an information warehouse dimension. The brand new secret is a so-called surrogate key. Whereas the Surrogate Key ensures every row within the dimension is exclusive, we nonetheless want to take care of the supply system’s major key. By definition, the supply system’s major keys are actually referred to as enterprise keys or alternate keys within the information warehousing world.
• A Begin Date and an Finish Date column characterize the timeframe throughout which a row of knowledge is in its present state.
• One other column exhibits the standing of every row of knowledge.

SCD 2 is essentially the most widespread sort of SCD. After we create the required columns

Let’s revisit our state of affairs when Stephen Jiang was promoted from Gross sales Supervisor to Vice President of Gross sales. The next screenshot exhibits the info within the Worker dimensions within the information warehouse earlier than Stephen received the promotion:

The EmployeeKey column is the Surrogate Key of the dimension, and the EmployeeBusinessKey column is the Enterprise Key (the first key of the client within the supply system); the Begin Date column exhibits the date Stephen Jiang began his job as North American Gross sales Supervisor, the Finish Date column has been left clean (null), and the Standing column exhibits Present. Now, let’s take a look on the information after Stephen will get the promotion, which is illustrated within the following screenshot:

Because the above picture exhibits, Stephan Jiang began his new function as Vice President of Gross sales on 13/10/2012 and completed his job as North American Gross sales Supervisor on 12/10/2012. So, the info is reworked whereas shifting from the supply system into the info warehouse. As you see, dealing with SCDs is likely one of the most vital duties within the ETL processes.

Let’s see what SCD 2 means in terms of information modeling in Energy BI. The primary query is: Can we implement SCD 2 straight in Energy BI Desktop with out having an information warehouse? To reply this query, we should do not forget that we at all times put together the info earlier than loading it into the mannequin. Then again, we create a semantic layer when constructing an information mannequin in Energy BI. In a earlier publish, I defined the completely different elements of a BI resolution, together with the ETL and the semantic layer. However I repeat it right here. In a Energy BI resolution, we handle the ETL processes utilizing Energy Question, and the info mannequin is the semantic layer. The semantic layer, by definition, is a view of the supply information (normally an information warehouse), optimised for reporting and analytical functions. The semantic layer is to not change the info warehouse and isn’t one other model of the info warehouse both. So the reply is that we can not implement the SCD 2 performance purely in Energy BI. We have to both have an information warehouse holding the historic information, or the transactional system has a mechanism to help sustaining the historic information, corresponding to a temporal mechanism. A temporal mechanism is a function that some relational database administration techniques corresponding to SQL Server provide to offer details about the info saved in a desk at any time as a substitute of holding the present information solely. To study extra about temporal tables in SQL Server, test this out.

After we load the info into the info mannequin in Energy BI Desktop, now we have all present and historic information within the dimension tables. Subsequently, now we have to watch out when coping with SCDs. As an illustration, the next screenshot exhibits reseller gross sales for workers:

At a primary look, the numbers appear to be appropriate. Properly, they could be proper; they could be fallacious. It relies on what the enterprise expects to see on a report. Take a look at Picture 4, which exhibits Stephen’s modifications. Stephen had some gross sales values when he was a North American Gross sales Supervisor (EmployeeKey 272). However after his promotion (EmployeeKey 277), he isn’t promoting anymore. We didn’t contemplate SCD after we created the previous desk, which implies we contemplate Stephen’s gross sales values (EmployeeKey 272). However is that this what the enterprise requires? Does the enterprise anticipate to see all staff’ gross sales with out contemplating their standing? For extra readability, let’s add the Standing column to the desk.

What if the enterprise must solely present gross sales values just for staff when their standing is Present? In that case, we must issue the SCD into the equation and filter out Stephen’s gross sales values. Relying on the enterprise necessities, we would want so as to add the Standing column as a filter within the visualizations, whereas in different instances, we would want to switch the measures by including the Begin Date, Finish Date, and Standing columns to filter the outcomes. The next screenshot exhibits the outcomes after we use visible filters to take out Stephen’s gross sales:

Coping with SCDs isn’t at all times so simple as this. Typically, we have to make some modifications to our information mannequin.

So, do all of the above imply we can not implement any varieties of SCDs in Energy BI? The reply, as at all times, is “it relies upon.” In some situations, we will implement an answer much like the SCD 1 performance, which I clarify in one other weblog publish. However we’re out of luck in implementing the SCD 2 performance purely in Energy BI.

Have you ever used SCDs in Energy BI, I’m curious to know concerning the challenges you confronted. So please share you ideas within the feedback part beneath.