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How Process Mining compares to Standard Query Tools

If you have data and questions about your process, there are many powerful tools around that you can use to manipulate, query, and analyze the data to answer these questions. For example, SAS is often used by auditors to combine and filter data. Routines can be programmed and automated to a large extent.

So, how are these tools different from process mining?

The main difference is that you need to know what you are looking for if you use a query-based tool.

Process mining allows for a much more explorative analysis of your process, without the need to have all the questions in advance. Here are 2 examples.


Process discovery works by taking the real execution logs of your process as input and then generates a graphical model of what has been happening.

Even if you are not sure what exactly you are looking for, process mining can provide you with an accurate picture about how your business process looks like in practice. This again may trigger questions that you would have never thought of in advance.

For example, in one of our customer projects we found out that advances that were made for some clients sometimes lead to a double payment in the regular process. The advance payment process was manually managed and thought to be under control. But just from looking at the discovered process model it became clear that much more cases slipped through the manual control than people thought.


Often, there already exists a description or a model of the process as it should be. By comparing the actual log data from the IT system with the ideal process, one can find out where deviations have occurred and how many.

Checking data against a complete process description is almost impossible to do in a standard query tool, because it is hard to capture the complete target process in a query.

Query tools are very powerful and can be best combined with process mining. Do you have any experience of using both? What are your observations?

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