Mar 2, 2016 · High granularity is what defines data to the most precision, so in my scenario Hourly is the highest granularity, then Daily next highest, Monthly next after that and Yearly the lowest granularity. Hence the higher the granularity the more data rows you will have.

Aug 13, 2023 · Dear Team , I am trying to implement section access with different employee hierarchy but i have the aggregated data at least granular level in the transaction table though i create hieirchy table implement bridge connection, not able to understand how too link with transaction table Please find the...

May 7, 2021 · the dataset is big with 3 years more granular data . not sure if 'if' will take long time to perform.

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Nov 7, 2013 · This will filter the data to select only records with Key = 0 and are in the last 12 months, and then sum the Data values by Name. This will work, though normally it is better to keep the data at a granular level in QlikView and do the summing in your charts as this gives you the most flexibility on how to view and analyse the data.

Oct 29, 2015 · Hi Experts, If there are multiple fact tables with different granularity how to fix this? Thanks in Advance.

The Qlik Associative Engine leverages the processor to dynamically create aggregations as needed in real time, which results in a fast, flexible, and intuitive user experience. Note that the data stored in RAM is the unaggregated granular data. Typically, no pre-aggregation is done when the data is reloaded or a script is executed for a document.

Aug 12, 2024 · @Sunilkumar3 If possible try to reduce data in your application. There are many ways to do it. You can filter your data or you can aggregate your data if your data is at lower granular (transaction) level. Once you aggregate your data, you can use ODAG to go to lower level in transaction. Check which field is occupying more memory using App metadata anlyzer app. If that field is just used in ...

Feb 20, 2013 · Hi Amar, Please follow what HIC suggested and that should take care of your requirements. Also, another alternative approach would be implementing Section Access at the most granular level of your data. Which will eventually roll-up based on the Hierarchy.