With a discrete story type, a user is trying to compare values and understand the distribution of their data. The narrative analysis adds distribution, and groupings/clusters across the data.

 

Contribution analysis for multi-dimensional narratives.

 

Below are examples of how the narrative analysis changes with 1M/1D, 1M/2D and 2M/1D, as well as a breakdown of each analytic type. 

 


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 Narratives for Tableau has support for the following scenarios of discrete analysis:

  • Single dimension with between one and 10 measures
  • Two dimensions and one measure

The example below is a single dimension and single measure bar chart:


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The example below is a single dimension bar chart with two measures:


Screen_Shot_2018-06-08_at_9.23.28_AM.png

The example below is a bar chart with two dimensions and a single measure:


Screen_Shot_2018-06-08_at_9.24.13_AM.png

 

 

Where is the Discrete Story Analysis Useful?

  • Sales Reporting - better understand drivers of your KPIs
  • Data Discovery - quickly identify and understand outliers
  • Audit - identify trends not easily observable in the visual
  • Geographical - instantly uncover complex utilization insights
  • Relationships - identify and call out key relationships between sales & profit

Example of Discrete Story: 


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To learn more about each insight in detail, watch our Discrete Story Type video. 

If you'd like to see all available narrative types, download our Tableau Workbook With All Story Types.