Data Management under Uncertain Conditions

DS08
Semester: 2nd,
ECTS Credits: 7.5

Vasiliki Kazantzi

(Course Coordinator)

Syllabus

  • Introduction to data management in decision-making problems under conditions of uncertainty – General characteristics of such problems – Stochastic systems
  • Modeling of stochastic systems
  • The role of data quality in solving problems under conditions of risk and uncertainty
  • Techniques and methods of data management for solving problems under uncertainty
  • Concepts of expected outcome, opportunity cost, and perfect information in real-world problems
  • Sensitivity analysis to changes in problem parameters – use of software tools (Excel, @Risk, XLSim, etc.)
  • Introduction to basic Monte Carlo (MC) simulation techniques
  • Design and development of simulation models – related frameworks
  • Use of software tools in solving complex problems using MC simulation techniques
  • Sensitivity analysis and interpretation of simulation results
  • Utilization of generated probability distribution charts for quantifying risk, performance, and opportunities in systems characterized by a high degree of uncertainty

Recommended Bibliography

  • Velten, K., Schmidt, D.M., Kahlen, K. Mathematical Modeling and Simulation: Introduction for Scientists and Engineers, 2024
  • Savage, L.S. Chancification: How to Fix the Flaw of Averages, 2022
  • Savage, L.S. Decision Making with Insight. Brooks/Cole, Belmont, CA, 2003
  • Savage, L.S. The Flaw of Averages: Why We Underestimate Risk in the Face of Uncertainty, John Wiley & Sons, 2012
  • de Neufville, R., Scholtes, S. Flexibility in Engineering Design. MIT Press, Cambridge, MA, 2011
  • Rossetti, MD. Simulation Modeling and Arena, John Wiley & Sons, 2015
  • Jaggia, S., Kelly, A., Lertwachara, K. and Chen, L. Business Analytics, McGraw Hill, 2023
  • Seila, A.F., Ceric, V., Tadikamalla, P.R. Applied Simulation Modeling. Brooks/Cole, 2003.
  • Hubbard, D.W. How to Measure Anything: Finding the Value of Intangibles in Business, John Wiley & Sons, 2014
  • Law, A.M., Kelton, W.D. Simulation Modeling and Analysis. McGraw-Hill, New York, 2007.
  • Υψηλάντης, Π. Επιχειρησιακή Έρευνα, Εκδόσεις Προπομπός, 2015