Data Mapping Overview
Learn how to upload datasets, map them to processes, and interact with data using ProcessMind's Data Mapping feature.
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Mapping / Unmapping activities
Mapped Activities
Mapped activities are activities in your dataset that have been successfully linked to attributes within your process model. These activities are fully integrated into the canvas and contribute to building a comprehensive and actionable process design.
How Mapped Activities are Represented
- Mapped activities are displayed as solid lines in your process model, visually distinguishing them from unmapped activities.
- They are color-coded based on the datasets’ assigned color, making it easier to identify their origin.
Linking Unmapped Activities
If you have unmapped activities, you can link them to modeled activities in three ways:
Drag and Drop:
Drag the activity from the dataset (referred to as a Mind activity) and drop it directly onto the corresponding modeled activity on the canvas. This creates a link, indicating that the designed activity represents the same as the Mind activity.Select from the Dataset:
Select the designed activity on the canvas, and then, from the right-hand side panel, choose an activity from the dataset to map it. This establishes the connection seamlessly.Use the mapping menu
Click on the options menu above the selected task. then in the menu you can add new activities to the task by hitting the plus icon. This will open a menu where you can select the activities you want to add to the task. You can also remove activities from the task by clicking on the trashcan icon next to the activity name.
Add multiple activities to a task
ProcessMind allows you to add multiple activities to a single task. This is useful when a task represents multiple actions or events in your process if you want to link multiple activities from your dataset to a single modeled activity. It is also possible to link activities to subprocesses and implode the subprocess so certain parts of the process flow can be hidden while still being linked to the dataset.
Data Flow Through
In cases where an activity is designed but not represented in the dataset (e.g., a non-digital step), you can set the activity as a Data Flow Through activity.
- Purpose: This allows the activity to remain part of the mapped activities without being included in calculations or statistical analyses.
- Usage: Ideal for steps that are critical to the process but do not have digital footprints.
Benefits of Mapped Activities
- Provide a structured view of your process, showing how datasets align with real-world operations.
- Enable deeper analysis, allowing you to generate statistics, identify inefficiencies, and refine workflows.
- Include non-digital steps without affecting the integrity of the data calculations.
Below is a short video that demonstrates these features, including how to map activities, set Data Flow Through activities, and visualize the results.