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2017/2018  BA-BINTV1051U  Big Data Analytics for Managers

English Title
Big Data Analytics for Managers

Course information
Language English
Course ECTS 7.5 ECTS
Type Elective
Level Bachelor
Duration One Semester
Start time of the course Autumn
Timetable Course schedule will be posted at calendar.cbs.dk
Min. participants 25
Study board
Study Board for BSc/MSc in Business Administration and Information Systems, BSc
Course coordinator
  • Ravi Vatrapu - DIGI
Niels Buus Lassen and Nadiya Straton will teach the course
Main academic disciplines
  • Managerial economics
  • Information technology
  • Statistics and quantitative methods
Last updated on 13-02-2017

Relevant links
Learning objectives
To achieve the grade 12, students should meet the following learning objectives with no or only minor mistakes or errors:
  • Characterize the phenomena of Big Data and Big Data Analytics from a managerial perspective
  • Analyze and apply different visual analytics concepts and tools for big data sets
  • Familiarity with the different concepts, methods, and tools for analyzing big data in an organizational context
  • Understand the linkages between business intelligence and business analytics and the potential costs and benefits of integrating big data analytics in business processes.
  • Critically assess the ethical and legal issues in Big Data Analytics
Course prerequisites
None
Examination
Big Data Analytics for Managers:
Exam ECTS 7,5
Examination form Home assignment - written product
Individual or group exam Individual exam
Size of written product Max. 15 pages
Assignment type Project
Duration Written product to be submitted on specified date and time.
Grading scale 7-step scale
Examiner(s) One internal examiner
Exam period Winter
Make-up exam/re-exam
Same examination form as the ordinary exam
Description of the exam procedure

Project reports must be in the Project Report Template to be provided on the first day of classes and uploaded to LEARN:
Course content and structure

This course is designed to provide knowledge of key concepts, methods, techniques, and tools of big data analytics from a managerial perspective.  Course contents will cover issues in and aspects of collecting, storing, manipulating, transforming, processing, analysing, visualizing, and reporting big data in organisational settings to create business value. 

 

Course topics are listed below:

  • Foundations: Concepts, Lifecycle and Exemplary Cases
  • Data: Types, Structures & Tokens
  • Data Mining & Machine Learning: Algorithms & Tools
  • Visual Analytics: Dashboards
  • Text Analytics: Classification & Clustering
  • Predictive Analytics: Time-Series Econometrics
  • Computational Social Science: Social Set Analytics
  • Applications: Private and Public Sectors
  • Datafication: Security, Governanace, Regulation, Privacy & Ethics
Teaching methods
Lectures
Voluntary Assignments
Tool Tutorials and Workshops
Project
Feedback during the teaching period
The teacher will give continous feedback during the course.
Student workload
Lectures 30 hours
Hands-on Exercises 30 hours
Tool Workshops: Preparation and Participation 30 hours
Individual Project: Work and Report 116 hours
Total 206 hours
Expected literature

F. Provost and T. Fawcett (2013), Data Science for Business: What You Need to Know About Data Mining and Data-Analytic Thinking. O’Reilly. 

 
Last updated on 13-02-2017