Especially in projects with a very large amount of data, for example tracking studies, it can happen that the performance, e.g. the loading speed of charts, slows down. There are a number of ways to keep performance high over the long term.
Data that has already been retrieved or calculated can be efficiently reused through caching. Caching can be activated in the backend under "Data" in the "Cache Settings":
You can also set the duration of the cache.
(2) Reduce number of charts per dashboard
The more charts there are on a dashboard, the longer are the loading times when using drop-down filters, since these are then applied to all charts in a dashboard. Here it can be helpful to use fewer charts on a dashboard and to divide the widgets thematically into different dashboards, for example.
(3) Do not show all values
Especially in the case of open entries or labels, there are often a large number of possible values. In most cases, however, only the TOPXX values are relevant for the analysis. You can define various TOP values via the backend (General >> Chart settings):
In the front-end you can then select the corresponding TOP values via the chart settings:
(4) Form index columns
Indices can also be created using variables that are often used as filters. Indices speed up searches in large databases.
Indices can be activated via the backend under Data:
(5) If possible use simple queries on precalculated columns in your dataset instead of SQL formulas
(6) Remove unneeded columns from your dataset
(7) Transfer to a column-oriented, relational database management system
Another way to increase performance - if points 1 to 3 do not improve performance - is to transfer the data to another database management system (e.g. Exasol). Please do not hesitate to contact us regarding this matter.