(Last updated: 18:00 1. Apr. 2020)
Process mining has been provided effective tools to improve inefficiencies residing in organizational processes. In process mining, data-driven approaches are used to improve the organizational processes with process-centric viewpoint.
Process discovery is at the heart of process mining. Process discovery techniques enable practitioners to find process models using event logs that are recorded at process-aware information systems. The resulting process model shows a comprehensive view of the processes that organizations have.
(This post is also uploaded at PADS blog).
Process mining has provided effective techniques to extract in-depth insights into business processes such as process discovery, conformance checking, and enhancement. Nowadays, with the increasing availability of real-time data and sufficient computing power, practitioners are more interested in forward looking techniques whose insights can be used to improve performances and mitigate risks of running process instances.
Research on these forward looking techniques has been actively done in the field of process mining.
Hadoop Hands-on (Last updated: 31. January. 2020)
This blog post is a supplement for Hadoop instruction at Introduction to Data Science, RWTH-Aachen. This post covers:
What is Hadoop Distributed File System (HDFS)? How can we use it? What is Hadoop MapReduce? How can we use it? How can we apply process mining techniques to an event log with billions of events with Hadoop? We are living in the world of big data.