Hi StavG, maybe this could be helpful:
https://community.qlik.com/t5/Official-Support-Articles/Conditional-reload-based-on-QVD-update-time/...
https://help.qlik.com/en-US/cloud-services/Subsystems/Hub/Content/Sense_Hub/Apps/app-performance-eva...
To create aggregated monthly QVDs without ID level using Group By while storing them in the same space as the earlier ID-level QVDs, you can follow these steps:
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Use a For Each loop to iterate through your existing QVD files.
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Load the data from each QVD file, introducing a dummy field (e.g., 'All Files') to create a single group for all records.
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Apply the Group By clause to aggregate the data on a monthly level, using relevant fields like YearMonth.
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Use the Sum function to aggregate numeric values and Group By to consolidate the data.
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Store the aggregated data in a new QVD file with a naming convention that distinguishes it from the ID-level QVDs (e.g., append "_monthly" to the filename).
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Implement incremental loading to update only the necessary data in subsequent reloads.
This approach allows you to maintain both the detailed ID-level QVDs and the aggregated monthly QVDs in the same storage space. The aggregated QVDs will be smaller in size and faster to load, making them ideal for historical data analysis or when detailed information is not required.
Remember to update your data model to use these new aggregated QVDs where appropriate, which can significantly improve app performance, especially when dealing with large datasets spanning multiple years.
