DataMa Compare is a relatively complex models and include a series of other parameters in the left menu, that you may have to use to refine or better visualise your analysis.

Most of them are editable through Shiny Web App, but you can also edit them through R code with references below (by those who have a « develop » license)

**Start & End definition:**This includes both definition of the dimension you want to compare on and the segments within that dimension that defines your starting point and end point- Start End Dimension (
`StartEndDimension`

): This can be whatever dimension is in your source, depending on your use case. Typically Period or Date, but also business unit, AB test variant… - Start definition (
`Start`

): This is really you’re starting point for the KPI you want to understand, i.e. what you want to compare to. It can be one or multiple possible values of the selected dimension. - End definition(
`End`

): This is the end point of your waterfall, i.e. the observation of your KPI that you want to explain.

- Start End Dimension (

**Filters**:- Excuded dimension (
`Excluded_Dimension`

): Dimension you want to exclude from the analysis - Filter segment (
`Dimension_filter`

and`Filter`

): Segment within a given dimension that you want to filter on - Dimension excluded from Summary View (
`Dimension_filter_SimplifiedView`

) : A dimension you don’t want to consider within summary view, for some reason.

- Excuded dimension (
**Settings**:- Level of aggregation (
`NumLimit`

): 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. - Skipped steps (
`selected`

): the steps that are kept within your overall Metric Relation definition. This allows you to change your overall « Market Equation » and the KPI you’re following, as well as grouping/ expanding the steps you’ve defined - Safe Mode (
`SafeMode`

): Activates two important checks:- The volume of events you’re considering in your analysis (
`DimensionForFlag`

,`MinValueForFlag`

): Is the total sum of selected Dimension above a certain threshold both within Start and End ? The idea is to check that your analysis is « significant » and everything you’re saying makes some sense. If not, a flag will be raised. Of course, this is far from a proper statistical significance test. DataMa Impact might help you in doing that properly, with the appropriate statistical tests - The correlation between your dimension is not too high (
`DimensionsAreNotIndependent`

). We’re using Chi-Square test here to evaluate the correlations within dimensions. This is important because when you compute a mix effect on two dimensions, it could very well appear that those two mix are actually the same effects. DataMa Pivot might help you in understanding this better.

- The volume of events you’re considering in your analysis (
- Display options (for Shiny app)
- Contextual help: Display executive summary and contextual worded sentences in help tooltips of charts. Swith off to avoid contextual help in the interface
- Print version: allow to read Shiny chart of segment performance without hovering on it
- Output unit (
`output_unit`

): the unit of the overall KPI you’re following. By default it is set to « € » for « Revenue » - Dimension excluded from Summary View (Dimension_filter_SimplifiedView) : A dimension you don’t want to consider within summary view, for some reason. The dimension is kept in the calculation but just don’t appear in graphs
- Label Bridges: Choose whether you want to display numbers on watefall or not

- Level of aggregation (