Aggregation Matrices can include multiple Facts. The Fact utilises content from the Source Query and each visible level. Adding a Fact adds a column of results to the Aggregation Matrix. These results are not held in a field, but instead calculated for each row when required.
A total can be produced for each dimension. The totals are calculated using the results in the column for each dimension. The type of total depends on the Fact used. For example, if the Fact was MAX, the total row would display the largest value from all of the results. Similarly, if a SUM Fact was used, the total row would calculate and display the sum of all the results.
The centre of the visualization is the Aggregation Matrix's Facts. The Facts are evaluated for each visible level or dimension Source Query. Within the Fact area you can format how the Fact's results are displayed, change the order, add, edit or remove them.
The Fact Builder is used to build the calculation (Fact) that is outputted for each Element. This is accessed from the add/edit link in the middle of the Designer tab's visualization of the Smart Column.
There are five different types of fact: Simple, Embedded, Threshold, Free Form Threshold, and Aggregated Pick State.
For a quick overview on what each of these types do refer to the appendix. For a more detailed explanation on Facts and the Fact Builder see Aggregation - A Closer Look at Fact Builder.
How to Add a Fact
- In the Designer tab, click “Add…” to open the Fact Builder
- If the Fact already exists, click “Edit…” to alter it
- Choose the type of Fact you want to add
- Start building the Expression in the dedicated box
- For more information on what the Fact components use the Aggregation - A Closer Look at Fact Builder guide.
- Check the Summary at the bottom of the Fact Builder to ensure the Fact is correct
- Click OK
- Execute the Aggregation Matrix to test the fact
- Depending on your desired output you may need to add levels to aggregate the content.
Adding a fact is demonstrated in the short video clip below: