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Regular version of the site

Data Driven Process Control

Prerequisites:

  • Basic computer science principles and skills
  • Basics in business process modeling

Courses:

  • Enterprise Architecture Modeling
  • Advanced Data Analysis&Big Data for Business Intelligence
  • Predictive Modeling
  • Cloud Computing

This course combines the disciplines of business process improvement (BPR) and service-oriented computing (SOC) to achieve automation with the help of technologies. The course is focused on process control, using computer-aided process surveillance and monitoring.

The capabilities of modern equipment and Big Data technologies enable to collect a lot of data about the process, conduct its analysis, including real-time analysis.

This can be used to optimize processes, enables to use predictive analytics in process control.

Also the course presents a fundamentals of optimizing the control of technical processes, focusing on collecting and using data for efficient control. The course content includes the discussion of the similarities and differences in the use of information for automation of business processes and production processes.

Students will gain the knowledge and skills to apply state-of-the-art process thinking and techniques to critical business processes for organizational efficiency, effectiveness and adaptability.


Topics include:

  • Process-Centric Organization
  • Process Modeling
  • Analysis & Design
  • Deployment & Change Management
  • Business Process Improvement (Lean & Six Sigma)
  • Business Process Automation (IT)
  • Business Rules (BR)
  • Modeling Tools
  • Business Performance Monitoring Systems (BAM)
  • Simulating business processes
  • Optimising process performance
  • Monitoring process performance
  • Process measurement instrumentation
  • Managing automated business processes
  • Technical process dynamics, control and tuning fundamentals
  • Technical process analysis and minimizing variability
  • Manufacturing Intelligence Architecture
  • Real-time process control
  • Predictive process control
  1. Michael Minelli,  Michele Chambers, Ambiga Dhiraj . Big Data, Big Analytics: Emerging Business Intelligence and Analytic Trends for Today's Businesses. Wiley, 1 edition, 2013

  2. Eric Siegel, Thomas H. Davenport. Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die. Wiley; 1 edition, 2013

  3. Chuck Hemann and Ken Burbary. Digital Marketing Analytics: Making Sense of Consumer Data in a Digital World. Que, 2013