Business Intelligence and Analytics

Vrije Universiteit Amsterdam

Course Description

  • Course Name

    Business Intelligence and Analytics

  • Host University

    Vrije Universiteit Amsterdam

  • Location

    Amsterdam, The Netherlands

  • Area of Study

    Business Administration, Business Management, International Business

  • Language Level

    Taught In English

  • Course Level Recommendations

    Upper

    ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.

    Hours & Credits

  • ECTS Credits

    6
  • Recommended U.S. Semester Credits
    3
  • Recommended U.S. Quarter Units
    4
  • Overview

    COURSE OBJECTIVE
    Academic & Research skills
    - Using business intelligence and data mining suites to create insight from data and tackle business problems

    Bridging theory and practice
    - Defining, describing and recalling the basic concepts, constituent components, principles and theories underlying the use and the deployment of business intelligence & analytics solutions

    - Choosing, applying, and evaluating business intelligence & analytics concepts, principles and solutions to solve business problems

    COURSE CONTENT
    Dealing with the overabundance of data and the ability to transform data into insights have become critical success factors for organizations. This course offers the handles that are needed to unleash the potential of data, and business intelligence and analytics solutions in order to create competitive advantage. The course primarily has a managerial focus. The students will acquire hands-on experience with trending BI&A technologies to learn how to use their features and characteristics in practice. Our partners from the industry and the business consulting sector will be closely involved in the course, sharing their insights and experience during several interventions.

    Keywords in this area are ‘big data’, ‘data science’, ‘business intelligence’, ‘data mining’ and ‘data-driven decision making and innovations’

    TEACHING METHODS
    Lectures, tutorials

    TYPE OF ASSESSMENT
    Written exam – Individual assessment

    Interim Assignment(s) / Tests:
    Hands-on analytics quizzes – Individual assessment

    RECOMMENDED BACKGROUND KNOWLEDGE

    Management Information Systems, Business Information Technology, Business Information Systems, Basic knowledge on Statistics and Microsoft Excel.

Course Disclaimer

Courses and course hours of instruction are subject to change.

Some courses may require additional fees.