WISE OWL EXERCISES
SSAS EXERCISES
SSAS - TABULAR EXERCISES
SSAS - tabular | Calculated columns exercise | Use the SWITCH function to divide transactions into bands
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The answer to the exercise will be included and explained if you attend the course listed below!
Software ==> | SSAS - tabular (29 exercises) |
Version ==> | SSAS 2012 and later |
Topic ==> | Calculated columns (4 exercises) |
Level ==> | Average difficulty |
Course ==> | SSAS - Tabular Model |
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If you haven't already done so, run the SQL script in the above folder in SQL Server Management Studio to generate a database (not for commercial use or copying) called MAM.
The aim of this exercise is to categorise staff by age using the following bands:
Year of birth | Band |
---|---|
Before the 1960s | Has-been |
1960s | Peak age |
1970s onwards | Will-be |
To start this slightly subjective categorisation, create a new project and model containing the transaction, pos and staff tables.
You'll need to create a relationship manually between the Pos and Staff tables at this point.
Create 3 new calculated columns in the staff table:

The staff table in id order, with the 3 new columns giving the name of each member of staff, their birth year and a verdict on their age.
Here are some notes on how to create these columns:
Column | Notes |
---|---|
StaffName | Use the & symbol to join together the first name, a space and the last name. |
YOB | Use the YEAR function to get the year for each member of staff, given their date of birth. |
Verdict | Either use a nested IF function based on the table at the start of this exercise, or (better) use SWITCH. |
Now use these columns to show the number of transactions for each age category:

The pivot table shows that (unsurprisingly) the post 1970 generation have processed most sales.
Save this workbook as But peak agers are still best, then close it down.