Data in ProcessMind
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Every analysis in ProcessMind starts with a dataset. This section covers the full lifecycle of a dataset inside the app: upload a file, map its columns to the three required fields, refine attributes and activities, check the quality score, and keep the data fresh as your process changes.
If you have never uploaded a file, the fastest way in is How to Upload Your Dataset — three columns are enough to start (a case ID, an activity, and a timestamp). If you are still deciding where your data should come from, read Process Mining Data first.
The dataset lifecycle
- Upload — import a CSV, Excel, XES, Parquet, or JSONL file: Configuring Your Dataset.
- Configure — map columns to the expected fields, then refine Dataset Attributes and Dataset Activities; preview everything in Dataset Data.
- Validate — read the Data Quality badge and panel before you trust the numbers.
- Keep it fresh — append new rows with Incremental Data Loading instead of re-uploading.
AI helps along the way: AI Data Recommendations flags mapping issues and anomalies automatically, and Dataset Attributes can derive new columns from existing ones as calculated attributes (see the expression language).
Where to go next
- Connect data to a model — the Data Mapping menu explains how datasets attach to process models, including primary and comparison datasets.
- Prepare data before you have a file — Process Mining Data covers sourcing, formats, and cleaning for event logs.
- Analyze what you uploaded — Process Mining turns a configured dataset into a mined process you can explore on the Process Graph.
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