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Explanations analyzes dimensions and combinations of dimensions of the data set in a time series to compare to a previous point in time. Explanations will tell you which dimension drove the behavior which can be a combination of several dimensions.

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Note

  • Keep in mind that, depending on your data, the Possible Explanation with the highest score might not always be the most suitable. You will usually know, based on context, which explanations make the most sense in your case

  • You can delete a Possible Explanation, if you'd like to.

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Explanations Data Set Requirements:

  • Explanations only works on column, line, area, and bar charts.

  • Explanations only works on time series with a single date dimension.

  • Only certain measures are supported.

    • Aggregate functions (SUM, COUNT) are supported

    • Measures based on other Formulas (AVERAGE, MEDIAN, COUNT) aren’t supported

    • Some custom formulas are supported provided that the formula used is using aggregate functions that will provide the same results in partitioned and non-partitioned data

  • Explanations doesn’t work properly when the measure is filtered by a dependent filter.

  • Explanations can only run on a widget when the relevant table is limited to 115K rows (cannot run if the dataset is larger than 115K rows). This limitation may be solved by applying a widget or dashboard filter to reduce the amount of data in the widget.

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