Pivot - Settings
Here is the different settings available in DataMa Pivot
Single Dimension Clusturing:
Multiple Dimensions Clusturing:
Find here the details of the main settings DataMa Pivot
Single Dimension Clustering
Aggregation in %
The level of aggregation that the model is using – e.g. if Level of aggregation is set at X%, segment within each dimension that represents less than X% of the Primary Numerator (e.g. Revenues) of the main KPI you’re analyzing will be clustered in one « Other » segment. X is set at 2 by default, but you may want to play with this parameter quite a bit because it can change significantly the calculation of mix effects.
Click on the drop-down arrow to display the settings menu Move the cursor to the right to increase the level of aggregation Click on « Pivot » to get results Segments are now aggregated at the requested level
Maximum Depth For Continuous Grouping
For continuous elements, multiple clusters are created aggregating elements having a similar average KPI. The level of aggregation of the clustering is set by this parameter.
Multiple Dimension Clustering
Maximum Depth Of Decision Tree
The Decision Tree is not yet avalaible in the latest version of DataMa Pivot
By increasing the tree depth you increase the detail of the decision tree. It will be more detailed.
DataMa Pivot can be used with a comparison. To enable this mode select a dimension and the element you want to compare. Each graph and the comments will be in a Compare mode reflecting the difference of the elements you are comparing.
In DataMa Pivot, there is only one ratio to be defined to run the module. This ratio will be used to understand the performance of the dimensions.