Business Intelligence

SOL17 Business Intelligence

Spring 2024

  • Topics

    Businesses are increasingly able to take large volumes of data into consideration, both from their internal business systems and from external sources. To stay competitive, businesses need to maximize the value of the data available to them today and in the future. Many businesses have acknowledged the need to utilize the increasing volume of various data that are generated at high speed to become more data-driven.

    In your future job, you will have to take the complexity and volume of data into consideration and ensure that you create business value from it. With modern technology, you have the possibility to let your decisions be based on data, rather than gut feeling. Business intelligence (BI) is about precisely this: to search for, collect, integrate, analyze and present data so that it provides a solid foundation for fact-based decision-making.

    BI has traditionally been based on data stored in internal business databases and/or data warehouses. Larger data volumes and more complex and external data have posed challenges to traditional BI such as data acquisition and data integration. As a result, modern data platforms have emerged and are being applied to address these challenges. Also, the need for adapting and responding in timely manner is given more emphasis in the design of modern platforms.

    This course aims to prepare students for a career in which they must use data in decision-making processes. The course provides an introduction to concepts, models and methods that are relevant for business intelligence. Students will also gain experience using modern software for business intelligence and become familiar with data integration process as well as understanding the possible role of artificial intelligence in business intelligence.

    The course will provide essential knowledge and skills to students who want to excel in roles that involve data engineering, business intelligence, analytics, and making informed decisions based on data. Thus, this course is relevant for both future leaders and BI specialists.

    TOPICS

    • Decision support / decision process
    • Data warehouses and modern data platforms
    • Database and dimensional modelling
    • Business intelligence and analytics
    • Business Intelligence and artificial intelligence

  • Learning outcome

    Knowledge

    The candidate:

    • Has thorough knowledge of business intelligence systems’ potential to help decision-makers search for, collect, integrate and analyze data.
    • Has insight into the different components included in a BI solution.
    • Has insight into challenges relating to BI and how modern data platforms address these challenges.
    • Has knowledge of principles, methods, concepts and models relating to business intelligence.
    • Has knowledge of how artificial intelligence may impact business intelligence.

    Skills

    The candidate

    • Can design multidimensional data models with Power BI.
    • Can use Power BI to perform data queries and transformations.
    • Can analyse and visualize data using Power BI.

    General competence 

    The candidate

    • Can apply his/her knowledge and skills to be able to play an active role in the development of BI solutions in a specific business context.
    • Can communicate with ICT consultants about needs relating to specific BI solutions.

  • Teaching

    The course will consist of lectures, videos and practical group work.

  • Recommended prerequisites

    It is recommended that the students have passed MET3.

  • Credit reduction due to overlap

    None.

  • Compulsory Activity

    Mandatory multiple choice (1 hour) Passed/Failed

  • Assessment

    Group-based project assignment (3-4 people) that counts for 100%. The assignment will be handed out 3 weeks before the submission deadline.

    An assessment in SOL17 will not be organised in the the non-teaching semester. As of autumn 2023, only mandatory bachelor courses with an individual assessment will have an assessment in the non-teaching semester. This only applies to students with a valid course approval. The retake options that apply at all times are decided by the dean for the bachelor program and will be published in the course description.

  • Grading Scale

    Grading scale A-F.

  • Computer tools

    MS Power BI.

  • Literature

    Articles / Book Chapters / Online resources.

Overview

ECTS Credits
7.5
Teaching language
English
Semester

Spring. Will be offered spring 2024.

Course responsible

Associate Professor Marilex Rea Llave, Department of Strategy and Management (main course responsible)

Micael S. Ueland, Director and Head of Business Intelligence and Reporting, TheVIT