Celonis Product Documentation

Create focused packages and knowledge models: Rather than creating all views and knowledge models in one package, try to focus your packages around your use cases. By having use case specific packages, you require less data to be loaded when opening your views. We also recommend that a package contains no more than four knowledge models.

Limit your use of embedded views: While embedded views allow you to display a greater volume of content, that data also needs to be loaded into your view each time. The loading time is also increased when embedded views are then nested into other embedded views. To optimize your view, we recommend that you limit the number of times you embed views and configure no more than three layers of nesting.

For more information about embedded views, see Embedded views.

Use buttons and links: Rather than using multiple tabs within your view, consider using buttons and links to direct your users to related views instead. This approach reduces the load on individual views, spreading out the data across more manageable views.

For more information about buttons and links, see: Buttons.

Optimize your view layout: Complex views, such as those with nested layers and a high volume of columns and rows, take longer to load. To avoid this, we recommend nesting no more than three layers into each view. To review this, focus on the Inner Section in your view’s visual editor and pay attention to the layout property on your columns in your YAML editor.

For more information about creating views, see: Create a new View.

Use available view components: When configuring a view there are a number of customizable view components available, such as KPI cards, charts, and filters. We recommend using these view components rather than embedding information from other views. As with other recommendations, we also suggest limiting the number of components you add to an individual view.

For a full list of available view components, see: View components.

Consider the volume of data needed: In general, the more data points used and the wider the timescale, the longer this data will take to load. As such, you should consider creating views or setting your filters based on more defined time periods and use cases. As an example, rather than filtering a chart based on all data from the last year, use smaller time periods.

Optimize your charts: To ensure your charts display efficiently, we recommend limiting the number of data points to two thousand, taking advantage of Process Query Language (PQL) calculations (such as PU_Count), and defining both your x and y axis for each chart.

For more information, see: Charts.

Simplify your PQL and variable statements: When writing PQL queries and variable statements, we recommend keeping them targeted and using functions and short hands whenever possible. This will reduce the volume of information sent, improving the performance of your views.

We also recommend the following PQL focused best practice:

Related links

Performance Optimization in PQL Academy course