process-mining
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- Release notes
- Before you begin
- Managing access
- Getting started
- Integrations
- Working with process apps
- Working with dashboards and charts
- Working with process graphs
- Working with Discover process models and Import BPMN models
- Showing or hiding the menu
- Context information
- Export
- Filters
- Sending automation ideas to UiPath® Automation Hub
- Tags
- Due dates
- Compare
- Conformance checking
- Process simulation
- Root cause analysis
- Simulating automation potential
- Starting a Task Mining project from Process Mining
- Triggering an automation from a process app
- Viewing Process data
- Creating apps
- Loading data
- Transforming data
- Structure of transformations
- Tips for writing SQL
- Exporting and importing transformations
- Viewing the data run logs
- Merging event logs
- Configuring Tags
- Configuring Due dates
- Configuring fields for Automation potential
- Activity Configuration: Defining activity order
- Making the transformations available in dashboards
- Data models
- Adding and editing processes
- Customizing dashboards
- Publishing process apps
- App templates
- Notifications
- Additional resources
Process Mining
Last updated Oct 29, 2025
With Data Manager you can add and edit fields and metrics displayed in your process app. You can also create new fields that derive their values from an expression or calculation based on values from other fields.
- A Field is raw data—individual pieces of information tied to each row in your dataset. For example, a field might represent
PriceorQuantityfor each transaction in a table. Fields describe specific details of each row.
- A Calculated Field is a transformation or computation applied to your raw data at the row level. It combines or modifies existing fields using
formulas or expressions, creating new values for each row without aggregating data. For example,
Profitmight be a calculated field created by subtractingCostfromRevenuefor each row.
- A Metric is a summary or an aggregation of data across multiple rows. Metrics combine data using methods like summing, averaging,
or counting to create a high-level indicator of performance. For example,
Total Profit(sum of all profit) orAverage Quantity Sold(average of all quantities) are metrics that help provide insights into trends or overall performance. Once created, metrics can be reused across multiple charts and dashboards. Metrics can be used to calculate other metrics.
To summarize: (Calculated) fields provide detailed information row by row, while metrics summarize and aggregate data across multiple rows to help you see the bigger picture.
| Concept | Definition | Example | Data Level | Purpose |
|---|---|---|---|---|
| Field | Raw data tied to each row in the dataset. | Price, Quantity, Date | Row-level | Describe specific details of each row. |
| Calculated field | A field created from a computation applied to raw data. | Profit = Revenue - Cost | Row-level | Combine the values of existing fields. |
| Metric | A summary or aggregation of data across multiple rows. | Total Profit, Average Quantity Sold | Aggregated (multi-row) | Combine data using methods like sum, average, or count. |
