What data do I need to run process mining?

Three columns are enough to start: a case ID, an activity, and a timestamp. Optional columns such as resource, cost, or department add extra context to the analysis.

Which file formats can I upload?

CSV, TSV, TXT, XES, Excel (XLS, XLSX, XLSB), Parquet, ORC, and JSONL/NDJSON files, optionally gzip-compressed. You can upload through the app or the API, and Parquet is the fastest option for large datasets.

Can I add new data to an existing dataset?

Yes. Incremental (delta) uploads append new rows to an existing dataset without replacing it. The delta file must match the format and column structure of the original upload, and Excel and XES files have to be converted first.

Do I need to clean my data before uploading?

No. You can start with the data you have and clean it as you go. Every dataset gets a quality score, and AI Data Recommendations can point out mapping and data issues automatically.

What if my column names do not match the expected fields?

You map your columns to the expected fields during dataset configuration. Data mapping and AI Data Recommendations suggest matches, and a quality score flags columns that still need attention.

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Process Mining Data in ProcessMind

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Welcome to Our Documentation Center

Guides, resources, and references to help you become an expert. ProcessMind helps you turn complex workflows into clear, efficient operations. From your first model to organization-wide process intelligence, this documentation gives you the steps, tips, and answers you need.

New here? Pick your track: Process Foundation to document and standardize, Process Architecture to connect and govern, or Process Intelligence to analyze and optimize with data. You can follow any track right away with a free trial.

Event data is the fuel of process mining: every chart, graph, and score is only as good as the log behind it. This section covers the data side of mining, before a file ever reaches a dataset — where event data comes from, which file formats carry it, what typically goes wrong, and how to clean and prepare it. When you are ready to load a file into the app, continue with the Data menu.

These guides are written for process mining analysts, data analysts, and anyone who extracts event logs from business systems. Preparing and uploading data requires a Process Intelligence seat, as do AI-driven checks such as AI Data Recommendations.

What You’ll Learn

Where to Get Data: extract event data from systems such as SAP, Oracle, and ServiceNow, and structure it as an event log.
Supported Data Formats: CSV, TSV, TXT, XES, Excel, Parquet, ORC, and JSONL files, with gzip compression.
Data Cleaning and Preparation: the recurring problems in event data — duplicates, missing events, inconsistent IDs, silos, large datasets, and privacy — and how to fix them before your analysis inherits them.

Where to Start

New to process mining data: the three columns every log needs are covered in What data you need for process mining; the Intelligence Path takes you from there to a mined process.
You have a file ready: head to Configuring Your Dataset to upload it and map its columns.
Your data has issues: Data Cleaning and Preparation names the usual problems and walks through the fixes.

When your data is ready, mine your first process with Process Mining.

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