donderdag 4 december 2014

Process mining


Currently following the course processmining on Coursera and this course is combination of data mining and processmodels. Like the same as with Business intelligence (sort of), processmining analyzes data about processes in an organisation. I'm quite enthusiastic about this approach because it analyzes processes on a scientific manner with data mining. Datamining analyzes data but not with the (direct) aim of looking at processes in an organisation. Processmining does. There is also a relation between BPM (Business Process modelling). In the course sometimes BPM models are used aside petrinets.

Although I've just started with the course, I want to share some interesting things, I've come along during the course. In this blog post I'll describe this.

Defining process mining

The definition of Processmining according to Wikipedia :

"Process mining is a process management technique that allows for the analysis of business processes based on event logs.".

But in my opinion event logs is a bit of a narrow keyword. A more broader definition could be applicable. Think about facts in a star schema or satellite information in a Datavault model that are very often used in business intelligence and data warehousing. These are transactions that happens in the operations of an organisation These are also events. Events that happened. Think about an order entry system with statuses. Sometimes, customers told me how the order entry process worked and when I studied the different statuses an order should have, I sometimes found out that different sequences of the order process were possible. With process mining you can identify undiscovered routes of your business process in automated way. This is truly an addition in the  field of Business intelligence, Lean Six Sigma,  datamining and BPM.

Just a simple example, suppose from the customer you hear that the model is this (orders with order statusses):

But when we study the transactions of the order entry system the following is noticed (records are identified by a case ID (the grouping of the records) and the activity at a certain moment):

Here we see that order 4568 is reopened and this should not have supposed to happen according to the designed model. After analyzing the events in a log or perhaps a transactional modelled star schema the model appears like this (corrected):

It could mean that in the operational process order entry personnel has reopened the order for some reason. If you want optimize the process in order to reduce the wastes (Lean Six sigma) than this is very interesting information. Process mining can do this for you.


Although I've just started with studying process mining, this seems a very interesting approach for analyzing processes with datamining. And, this is also applicable on huge log files and analyzing log files is one of the applications of Big data analytics. 

Hope you have read this blogpost with pleasure..



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