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Historical data into Qlik Sense


I would like to include historical data into my Qlik Sense application.  As an example there is my FCT_Contract table, containing every data about a contract and my HIST_Contract table containing the data by month.


How can I manage the two sets of data to work within one Qlik Sense application ? I would want to make some comparation vizualisation (between periods) and to have my "classic" vizualisation about my current period also.  I could make a link table to avoid the duplication of every dimensions like this :


Do I have to duplicate every measure I have in my application ? Lets say I would like to have the count of contract by category.  If I have only one measure "Contract count" (which is filtered by period), I could have this count right only if I have selected one period (current or only one month).  If after I select multiple period to be able to make comparaison between multiple periods, my other vizualisation which work on one period would be false.  I want to avoid this kind of confusion.

Do you have a "best practice" to work with historical data with snapshot date ?


3 Replies

See this document (which applies to Qlik Sense too): IntervalMatch and Slowly Changing Dimensions

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Thanks for the fast answer.

I read the document but I don't see how this is applicable to my problem.  I don't want to select data for its validity within an interval (as the department for a sale person as in the document) but I want to compare data between different snapshot dates and keep the same measures & dimensions but only add some filters or something to help me clarify the situation for my users.  I want to be able to work with the "current version" of my data and the "old versions" in the same application/sheet.


If your two fact tables contain basically the same information, but at different granularity (i.e today versus historical months) then perhaps this blog post is more to the point: Fact Table with Mixed Granularity‌. The result will be one fact table and you can compare snapshots easily using a combination of set analysis, alternate states and/or bookmarks.

talk is cheap, supply exceeds demand