Interface performance in Qlik Sense refers to how fast a dashboard responds when users interact with charts, filters, and selections. If the interface is slow, it can frustrate users and make data analysis inefficient. To improve performance, follow these three best practices.
1. Minimize Complicated Calculations and Functions
Using too many complex calculations in the expression editor can slow down chart rendering. When Qlik Sense recalculates these expressions every time a user interacts with the dashboard, it increases processing time and reduces responsiveness.
The best approach is to calculate values beforehand in the Data Load Editor, ensuring Qlik Sense only needs to display results instead of performing real-time calculations.
2. Minimize String Comparisons
Comparing text values is slower than working with numbers because text processing requires more memory and computing power. If a dashboard frequently checks whether a field contains a specific word, it can impact performance.
For example, if a dashboard filters records by checking whether the “Status” field contains the string “True” or “False”, Qlik Sense has to scan every row and compare text values, which slows down performance.
A better approach is to replace these text-based conditions with numeric values during data loading. Instead of using “True” and “False”, assign them values such as 1 for “True” and 0 for “False”. Using numeric flags instead of text makes comparisons much faster and improves performance.
3. Minimize Set Analysis Against Large Fact Tables
Set analysis is useful for filtering data dynamically, but applying it excessively in a Table chart with many columns can slow down performance. If each column in a Table chart contains a measure with complex set analysis, Qlik Sense has to calculate each column’s condition separately for every row, which increases processing time.
For example, if a Table chart includes many columns with different conditions applied, it will take longer to load because Qlik Sense must evaluate each condition row by row.
To improve performance, try reducing the number of columns that use set analysis or pre-aggregate key measures in the Data Load Editor so that calculations do not need to be done dynamically for each row.
By following these best practices, you can create a faster, more efficient, and user-friendly Qlik Sense dashboard.
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