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Anonymous
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5 years ago
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Code library / snippets to deploy multiple reports

I work on Power BI Desktop and publish reports to Power BI Service.
 

I have a fairly comprehensive report (pbix file) that has the following specificities :

  • 20 pages
  • 20 tables with each of them having 10 calculated columns
  • 60 measures
  • connection to 10 SQL tables from a server
  • that report is made to reflect progress/users/tasks/budget based on data from a specific project ("Project A")

Objective is to have the same report on another project "Project B" (actually, it's about 10 other similar projects). Project B is using a very similar database, and there are 95% of the data structure in common between Project A and Project B. I can't mix users as well, they really need to be separate projects (user access, data confidentiality).

 

Right now, to the best of my knowledge, I would copy/paste the Report A.pbix, to make Report B.pbix and I would then have 2 different reports. Maintenance-wise, it is problematic to have to maintain 10 reports that are similar but not identical.

 

I currently haven't found a way to build a "code library" that I would easily re-use in reports, that could make life easier to update to a specific formula or measure.

 

Am I missing something in Power BI about code library or code sharing ? Any methodology for handling a collection of reports and maintaining them efficiently ?

 

Bonus : Would Tableau or Spotfire provide a feature to help me create "similar dashboards" for 10 similar projects ?

 

Thanks a lot for reading and looking forwards to your answers !

2 Replies

  • The general approach in such a situation is to create a master dataset in a dedicated workspace that has the complete data model and no real report (maybe some DQ reports). Then you can create any number of reports in different  workspaces/apps that connect to that master dataset with their own set of filters and permissions etc.

     

    Power BI has the concept of promoted and certified datasets to steer developers towards using these master/golden datasets rather than to duplicate data models all over the company.