Create / Generate Fiscal Calendar - Best Practice

[joshua1990]

In the past I have generated our fiscal calendar in Dataflow Gen 1 using PQ.

This calendar table was shared accross different workspaces and reports.

Considering to upgrade the workspace to fabric what would be the best approach to generate a calendar and to make it available for different reports?

• Dataflow Gen 1 / 2?
• Something using SQL or Phython etc?

What are your thoughts?

[V-yubandi-msft · Accepted solution]

Hi @joshua1990 ,

Select the method that best suits your expertise (Power Query, SQL, Python) and the complexity of your time intelligence calculations. Each option guarantees that the enriched fiscal calendar is centralized and accessible across Fabric workspaces and reports.

Thank you, @lbendlin &  @suparnababu8 , for your prompt and helpful responses.

If there is any post helps, then please consider Accept it as the solution  to help the other members find it more quickly.

[lbendlin]

Fiscal calendars are immutable.  There is no need to calculate them over and over again.  Use an external, precomputed, reference table

[joshua1990]

Yes and now. The skeleton should be sourced from an ERP etc, but I need to add some additional time intelligence columns.

[suparnababu8]

Hello @joshua1990 

Thanks for reaching coomunity.

As per your requirement, I can choose Dataflow Gen2 as 1st choice of bext practise. here is why?

• DataFlow Gen2  has advanced capacbilites as compared to Gen1. You can create a fisical calender table by uisng gen2 anshare it across all reports - It's a centralized location and you can publish this in any of supported DB's such as Lakhehouse, Warehouse etc..(It's not possible by using Gen1)
• You can use SQL for handling large datasets, suppose if you have any complext logic need to be creatd for fiscal calender year, SQL with datawarehouse will be  best option.
• Python is also abest option but it's depends on your data volume.

Finally I would like to tell you, if you are going to use low-code-no-code then go with Dataflowgen2, if you want to perform large data processing then you can opt SQL & if you are familir with Python you can go with this.

according to your requirement, you can select one best option from this.

Thank you once again!!

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