Data Model
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      Data Filter vs. Table vs. P# Script

      Data Filters

      • Data Filters are quick easy way to pull data, save data back to the platform and convert to a P# Script.  
      • Data Filters have the capability to save any modifications made to the data directly to the Workspace.
      • Data Filters can use copy & paste directly for a spreadsheet into the Workspace.
      • Data Filters can also be saved as a P# Script.

      Pivot Tables

      • Pivot Tables are most suitable for data that is time dependent.
      • For use in Power BI:  A Pivot Table is an excellent tool for storing time-series information. It can be thought of as the Power BI equivalent of a flat-file format that contains data with a one-to-many relationship. This means that for each entity, there are multiple rows of information, each linked to a series of dates. When you load a pivot table like this into Power BI, it functions like a database table, allowing you to work with this type of data effectively.

      P# Scripts

      • For P# Script, it's best when you want to save data back into the platform.
      • P# Scripts have the capability to save any modifications made to the data directly to the Workspace.
      • For use in Power BI: Utilize a P# script for static data or "one-to-one" data, meaning each entity has only one row of information. This applies regardless of how the single-row data is obtained. The advantage of using P# scripts is that they allow you to process data using time and/or depth scopes, resulting in a collapse of the results into a single row of information per entity.

      However, there is one important consideration to keep in mind regarding the use of P# scripts. If a P# script is highly complex and requires a significant amount of processing time, it may be more beneficial to convert it into a Pivot Table. As a general guideline, if a P# script executes within seconds, it is perfectly suitable to leave it as is. However, if the execution time exceeds 10 minutes or more, it may be worth considering the conversion to a Pivot Table. This decision ultimately depends on the specific requirements and performance needs of your Power BI dashboard.