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. 




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

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

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


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


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




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: 



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