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Preset Feature Feedback

Extract data from the database to allow advanced analytics computation and save DB resources

What is the problem or goal the end user is trying to solve or accomplish?

Customers want to isolate a single value from a calculation and compare that to different items, timeframes, etc with ease. Another use-case would be when there are multiple Charts using the same Dataset - customers would like that Preset execute a single query for the Dataset on the DB, and then filter it according to each Chart.

How are they solving it currently?

This can be solved by creating joins with the same table to create these comparisons. It is not possible to avoid multiple queries to the same Dataset.

What is the recommended solution by the Customer?

Implement data extraction so that Preset can perform these additional queries to compare the data.

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    • David Rivera
      Reply
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      Feb 5, 2025

      This would be a really useful and powerful feature.
      The typical example would be, a Dashboard with some KPIs (displayed with Big Number charts) based on a date period. Only one dataset is needed to calculate all the KPIs numbers, but instead of running the same query N times, only 1 is needed.


      It would mean, less requests to the DB, reducing the load in the DB and speeding up a LOT the dashboards

      +1

    • Guest
      Reply
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      Feb 8, 2024

      Undoubtedly, this would be an exceedingly convenient feature

    • Marko Stefanovic
      Reply
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      Apr 6, 2022

      Sending a spearate query to the database for each chart is ineffective when each query is filtering through millions of rows. If Preset were to upgrade their product in such a way that it can connect data sources to dashboards instead of connecting them to specific charts - and then allowing all charts on the dashboard to use the results of the query, this would be a huge improvement that would increase the usability of the product multiple times.

    • Igal Liberman
      Reply
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      Apr 3, 2022

      The use-case of multiple Charts using the same Dataset is very common at least for our organization where we have the same DB result displayed in different visualizations and aggregation forms in different charts on the same dashboard.

    • +3