Predictive Analytics World, the leading vendor-independent expert conference, launches the first European edition of PAW Manufacturing in Dusseldorf, Germany. Read a preview of Process Mining for the Internet of Events. Register by Jan 13 and save with code KDN15.
PAW Manufacturing is coming to Dusseldorf!
Predictive Analytics World for Manufacturing is the leading vendor-independent expert conference for application-oriented Predictive Analytics in Industry 4.0. We are pleased to announce the launch of the first European edition of PAW Manufacturing in Dusseldorf, Germany on February 2nd-3rd, 2017!
With a full conference programme in English and many international experts attending, PAW Manufacturing is a guaranteed opportunity to hear how some of the world's largest and most forward-thinking manufacturers are tapping the power of predictive modeling to improve business outcomes.
All presentations are projected from experts for experts with a strong focus on real-world examples of deployed predictive analytics techniques, presenting concrete application cases and business scenarios of Predictive Analytics in the context of industrial production.
The conference programme is already live. Have a look at it here.
We interviewed our keynote speaker Prof Dr. Wil van der Aalst from the Eindhoven University of Technology about his lecture Process Mining based on the Internet of Events and here is an extract from the full interview:
Prof. Dr. Wil van der Aalst, it is a great pleasure and honour that you will speak at the Predictive Analytics World Manufacturing in February in Dusseldorf. The title of your keynote will be Process Mining based on the Internet of Events. All data scientists know data mining and most know text mining, but what is process mining?
Process mining bridges the gap between traditional model-based process analysis (e.g., simulation and other business process management techniques) and data-centric analysis techniques such as machine learning and data mining. Process mining seeks the confrontation between event data (i.e., observed behavior) and process models (hand-made or discovered automatically). This technology has become available only recently, but it can be applied to any type of operational processes (organizations and systems). Like process mining, data mining is data-driven. However, unlike process mining, mainstream data mining techniques are typically not process-centric. Process models expressed in terms of Petri nets or BPMN diagrams cannot be discovered or analyzed in any way by the main data mining tools.
Can you give examples of how process mining is already used in business and industry? And what are the benefits for companies?
The two primary reasons for applying process mining are: (1) performance and (2) compliance. Process mining is used to discovery the real process thereby uncovering bottlenecks, delays, waste, errors, and inefficiencies. These performance problems are uncovered in an evidence-based manner, taking only a fraction of the time this would normally take. Whenever there is a normative process model (guidelines, regulations, best practices, etc.), process mining can be used to diagnose deviations. What is causing these deviations and how harmful are they?
We invite you to take part in this extraordinary event to be informed and inspired, to learn about the latest research and advances and exchange ideas both professionally and personally.
You also have the chance to save up to 300€ on the full price if you book your ticket in advance. The Early Bird rate is available until January 13th!
Early Bird + KDnuggets Discount
Save when you register before January 13 with early bird passes, and save an extra 15% on conference passes when you register with code KDN15.