Managing data, decisions and processes (5081)
  
Coordinating lecturer :Prof. dr. Mieke JANS 
  
Co-lecturer :Prof. dr. Benoit DEPAIRE 
  
Member of the teaching team :De heer Haroon THARWAT 
 Mevrouw Manal LAGHMOUCH 
 Mevrouw Yunyun WANG 

Language of instruction : English
Credits: 12,0
  
Period: semester 1 (12sp)
  
2nd Chance Exam1: Yes
  
Final grade2: Numerical
 
Exam contract: not possible
 
Sequentiality
 
   No sequentiality

Content

Managing Data, Decisions, and Processes starts with a focus on data and provides the necessary concepts and skills to handle data as it exists in a business context. You start with the necessary data modeling concepts, which act as a common foundation for all other future data skills. Additionally, you will focus on the necessary skills to extract data from realistic data environments and how to prepare these data for future data analyses. Once you are comfortable with extracting and preparing data, the course will focus on the two aspects where data science shines within organizations, i.e., improving the quality of business decisions and business processes. For both aspects, you will learn a broad range of AI techniques to extract actionable insights from data.

 


Organisational and teaching methods
Organisational methods  
Lecture ✔  
Small group session ✔  
Teaching methods  
Exercises ✔  
Homework ✔  


Evaluation

Semester 1 (12,00sp)

Evaluation method
Written exam100 %
Closed-book ✔
Open questions✔

Second examination period

Evaluation second examination opportunity different from first examination opprt
No
 

Compulsory textbooks (bookshop)
 

Textbook 1:

  • Kroenke, David, M. and David J. Auer. Database Processing: Fundamentals, Design, and Implementation, Global Edition. (Available from: VitalSource Bookshelf, (14th Edition). Pearson International Content, 2016.)

    • Isbn eText: 9781292107646

    • Isbn fysiek boek: 9781292107639

Textbook 2

  • Silver, Bruce. BPMN Method and Style, 2nd Edition, with BPMN Implementer's Guide
    • isbn 9780982368114

Textbook 3

Data Science for Business: What you need to know about data mining and data-analytic thinking, Provost, Foster, and Tom Fawcett, 2013, O'Reilly Media, Inc. 

1449361323 (ISBN10), 978-1449361327 (ISBN13)

 

Compulsory course material
 

Study material will be provided over Blackboard (apart from the text books)
 

Mandatory software
 

Microsoft Access


Learning outcomes
Master of Business Administration
  •  EC 

    • EC 14: The holder of the degree is able to apply in-depth academic insights from organisational and management sciences and relevant supporting and/or related disciplines in the analysis of such concrete questions of business management and formulate recommendations. (Problem-solving capacity)

 
Master of Business Economics
  •  EC 

    • EC 15: The holder of the degree is able to apply in-depth insights and argumentation methods from business science and relevant supporting and/or related disciplines in solving strategic policy issues. (Problem-solving capacity)

 
Master of Management
  •  EC 

    • EC 13: The holder of the degree is able to formulate, analyze, and answer complex management issues within a VUCA world from a systems perspective, providing innovative and scientifically grounded recommendations using strategic and conceptual perspectives.

     

 
  EC = learning outcomes      DC = partial outcomes      BC = evaluation criteria  
Offered inTolerance3
Exchange Programme Business Economics J
Specialisatie Data Science for Business verplicht J



1   Education, Examination and Legal Position Regulations art.12.2, section 2.
2   Education, Examination and Legal Position Regulations art.15.1, section 3.
3   Education, Examination and Legal Position Regulations art.16.9, section 2.