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Author's profile photo Ingo Hilgefort

How to model time-dependent dimensions and attributes in SAP Datasphere ?

I am sure most of you are aware that in SAP Datasphere you have the ability to create a time-dependent dimension now by configuring the “From” and “To” or the “at” date values.

You can find more details here: SAP Help.

But… what if we don’t just have a time dependent dimension or a time dependent text, but instead we have a time dependent dimension and a time dependent text and a time dependent attribute.

Some of you now might say.. “well – that’s unrealistic” – so – welcome to the complexity of HR data.

So lets take an example:

  • First we have a time dependent dimension “Employee” and our “Employee” has a start and end date.
  • Second we have a time dependent text. Let’s take a simple example and our employee gets married and changes the Last Name.
  • Third – we use the example from above – the Marital Status changes as an Attribute to our Employee and there are many more examples for the time dependent Attribute, such as Pay Grade, Pay Level, Job Level, ….

So lets assume we have data that looks similar like this:

Our Employees:

100 EMPLOYEE 100 A 01-Jan-23 30-Jun-23
100 EMPLOYEE 100 B 01-Jul-23 31-Dec-99
200 EMPLOYEE 200 A 01-Jan-23 30-Jun-23
200 EMPLOYEE 200 B 01-Jul-23 31-Dec-99
300 EMPLOYEE 300 A 01-Jan-23 30-Apr-23
300 EMPLOYEE 300 B 01-May-23 31-Dec-99
400 EMPLOYEE 400 A 01-Jan-22 30-Jun-23
400 EMPLOYEE 400 B 01-Jul-23 01-Aug-23
500 EMPLOYEE 500 A 01-Jan-22 30-Jun-23
500 EMPLOYEE 500 B 01-Jul-23 01-Aug-23

Our Values for Attribute 01

100 ATTRIBUTE01 100 A 01-Jan-22 30-Jun-23
100 ATTRIBUTE01 100 B 01-Jul-23 01-Aug-23
200 ATTRIBUTE01 200 A 01-Jan-23 30-Apr-23
200 ATTRIBUTE01 200 B 01-May-23 31-Dec-99
300 ATTRIBUTE01 300 A 01-Jan-22 31-Dec-22
300 ATTRIBUTE01 300 B 01-Jan-23 30-Apr-23
400 ATTRIBUTE01 400 A 01-Jan-22 30-Jun-23
400 ATTRIBUTE01 400 B 01-Jul-23 01-Aug-23
500 ATTRIBUTE01 500 A 01-Jan-23 30-Apr-23
500 ATTRIBUTE01 500 B 01-May-23 31-Dec-99

Our Values for Attribute 02

100 ATTRIBUTE02 100 A 01-Jan-22 31-Dec-22
100 ATTRIBUTE02 100 B 01-Jan-23 30-Apr-23
200 ATTRIBUTE02 200 A 01-Jan-22 31-Dec-22
200 ATTRIBUTE02 200 B 01-Jan-23 30-Apr-23
300 ATTRIBUTE02 300 A 01-Jan-23 31-Mar-23
300 ATTRIBUTE02 300 B 01-Apr-23 31-Dec-23
400 ATTRIBUTE02 400 A 01-Jan-23 31-Mar-23
400 ATTRIBUTE02 400 B 01-Apr-23 31-Dec-23
500 ATTRIBUTE02 500 A 01-Jan-23 31-Mar-23
500 ATTRIBUTE02 500 B 01-Apr-23 31-Dec-23

Before we now go into SAP Datasphere and model this, lets clarify a few items upfront:

  • In SAP Datasphere the only object types that allow you to setup the time dependency are the Semantic Type “Text” and the Semantic Type “Dimension”.
  • We need in this example 3 (three) independent time dependencies, which means that a single dimension object won’t work as that would provide us only with one set of time dependencies.


In this approach what we will do is :

  • Create a Dimension which will leverage the source table for the Employees, which will take care of the name changes.
  • We create a second Dimension for Attribute 01.
  • We create a third Dimension for Attribute 02.

… and then we bring all these together and here is another important rule to keep in mind.

When setting up Associations in SAP Datasphere the most you can point to your Attribute is 1 (one) Text Association and 1 (one) other Association, so in other case with 2 dimensions for the Attributes we basically need to set it up like a snowflake.

First we define 3 Dimensions with the individual time dependency.


Attribute 01

Attribute 02

These are all modeled as Dimension objects so that we can configure the Semantic Type.

Now we have 3 Dimensions, so all that is left to do is to now “chain them” in form of a snowflake using the Associations.

So we add the Dimension for Attribute 01 as an Association to the Employee dimension

…and we add the dimension for Attribute 02 as an Association to the Dimension object from Attribute 01.


Now all we need to do is to use our FACT and add the Association to the Employee Dimension and then create the Analytical Model.

In the Analytical Model we can then see our 3 set of Dimensions.


Because we created this using three separate dimension objects, the individual items are not grouped under on “header” in the list of dimensions, but instead – for those with BW background – its more like the good old Navigational Attributes.

and – showing data for August 02, 2023 – we have 1 dimension with 2 Attributes and each with its own time dependency.

and each time dependency is resolved correctly.


Hope this helps a few folks out. I will show next week how this also can be used to create time dependent hierarchies.


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      Author's profile photo Sascha Claus
      Sascha Claus

      Hi Ingo,

      were you already able to create temporal hierarchy joins? In SAP BW it is possible to display different hierarchy states while analyzing the data over time. Meaning the values are mapped to the valid hierachy states for each individual period.

      As of now I could not recreate this in datasphere. It seems only possible to select one specific date for the hierarchy state.

      Kind regards,


      Author's profile photo Ingo Hilgefort
      Ingo Hilgefort
      Blog Post Author

      Hello Sascha,

      those are not possible yet in a Graphical View but you can create them using the SQL View option and specify them as part of the SQL Statement.



      Author's profile photo Sascha Claus
      Sascha Claus

      Hi Ingo,

      do you have any example of how this works?


      Kind regards


      Author's profile photo Ingo Hilgefort
      Ingo Hilgefort
      Blog Post Author

      Hi Sascha,

      ok - I just noticed you were also talking about "hierarchy". read to quick.

      so temp joins are possible in the SQL View - like this:
      FROM <>
      JOIN A on <column> BETWEEN <date1> AND <date2>

      haven't tried that with a hierarchy, but... (not tested) if you join on the raw data you should be able to then use the hierarchy on top for display



      Author's profile photo Sebastian Gesiarz
      Sebastian Gesiarz

      Thanks, Ingo, you make it look quick and easy as usual 🙂