
Demystifying Process Mining: A Beginner’s Guide
A plain language introduction to process mining, starting from examples everyone recognises rather than from theory.
Our business process modeling blog shares the ideas, examples, and advice enterprise teams need to understand how work really runs and where it can improve.

A plain language introduction to process mining, starting from examples everyone recognises rather than from theory.

mindzie partners with Silico to pair process mining with business process simulation, so a proposed change can be tested before it is made.

CSV, XES, MXML and OCEL each carry different amounts of structure. Which one you need depends on what you are trying to analyse.

mindzie integrates generative AI into the platform so users can ask for process insights in plain language rather than building a query.

mindzie launches a MuleSoft Certified Connector, making it easier to feed process data from integrated systems into mindzie studio.

Skan and mindzie announce an integration bringing process mining and task mining together in one view.

Internal audit has always been limited by sampling. Process mining removes that limit by testing the full population.

Alpha, Heuristic, Fuzzy, Inductive and Genetic miner each trade accuracy against readability differently. A plain explanation of how each works.

Predictive process monitoring estimates where a running case is heading, so intervention happens while it still matters.

Adoption patterns differ by country and sector, but the underlying problem is the same everywhere: nobody can see how the process really runs.
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The mindzie team can show you how the ideas from our process improvement blogs translate into real-world results, bringing together process intelligence, BPMN modeling, and AI-ready operational insight in your business environment.