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We've enhanced the Celonis Platform with new usability improvements for a more seamless experience. Analysts will find it easier to explore their data with powerful new visualizations like the boxplot chart, while also benefiting from new data management and usability features. These updates are designed to help you work more efficiently and effectively.

All changes listed below are in General Availability. To take part in early previews, check out the list of opportunities here

Planned releases:

DATA INTEGRATION

Inactive Data Model Suspension

To prevent unnecessary load on the Celonis Platform, data models that haven't been referenced in PQL for 40 days or more will now be suspended. When a data model is suspended, its data is still accessible but won't be up-to-date. You can manually reactivate a suspended data model, but it can take up to an hour for the load to restart after a PQL query is triggered. To keep you informed, email notifications are sent seven days, two days, and shortly before a data model is suspended.

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PI GRAPH

Delete Object/Event Types & Dependencies

When you delete a custom object or event type, the system now automatically removes many of its dependencies. This saves you time by automatically deleting:

  • Object and event relationships
  • Transformations
  • Occurrences in perspectives 

You will still need to manually delete transformation code for certain relationships and any PQL statements you created using the deleted object or event type.

 

PROCESS DESIGNER

Improved Modeling & BPMN 2.0 Conformance

A new editor for Process Designer is now available, offering an improved modeling experience and full BPMN 2.0 conformance. The new editor supports features like pools, lanes, and message flows, and allows for inline editing. This is an opt-in change, so you can choose which editor to use without needing to migrate existing processes. Additionally, Celonis Process Management (CPM) has a refreshed look to be more visually aligned with the rest of the platform. Please note that customers with existing customization set up for their CPM workspace will remain untouched.

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PROCESS NAVIGATOR

Approver role in Process Journal

The Approver for a specific process is now visible when viewing it in the Process Journal.

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STUDIO VIEWS

Object count in Views

When using object-centric data models, you can enable and configure an object count for your Studio Views. The indicator shows the percentage and total number of objects available in the current view and updates based on applied filters.

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Predefined filters for containers

Predefined filters can now be configured for containers and tabbed containers in your Studio Views. This allows you to set filters on a Knowledge Model, View, or tab level, ensuring the published version of a View already shows filtered data.

Y-axis autoscale for charts

Y-axis autoscaling can now be enabled for Studio charts to dynamically adjust the Y-axis based on the visible data range. Disabling this feature keeps the Y-axis fixed for a consistent view of the entire dataset, which can help with data comparison.

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Knowledge sidebar & quick metadata updates

Studio now includes a new Knowledge sidebar to help you configure View components more quickly. You can drag and drop dimensions, metrics, and saved filters directly from the sidebar. Additionally, it's easier to change a data chip’s display name, format, and units from its context menu without needing to open the PQL editor.

Show & hide Knowledge Model entities

You have the ability to show and hide Knowledge Model entities from the user interface using the View Options panel. This makes it easier to manage the data and variables you need, as hidden entities are only removed from the Knowledge Model interface but are still available for use in Studio assets that reference the model.

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Boxplot Chart Component

 A new boxplot chart component has been added to Studio Views, offering both horizontal and vertical options. This chart is a great tool for visualizing the distribution of numerical data and comparing different groups, as it provides a quick, high-level view of a dataset's symmetry, spread, and outliers.

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