Material presented in the lectures plus additional material handed out by the lecturers.
Combination of lectures and exercises. The students need to install additional software on their computers. Exercises include oral and visual presentation.
Quantitative (exam), quantitative (exercises)
10.01.2022 - 18.03.2022
19.11.2021 - 09.01.2022
Enrolment in Peppi http://peppi.lab.fi. If you need assistance, please contact the student office.
Faculty of Business and Hospitality Management (LAB)
Jaani Väisänen, Jaana Tanhuanpää
Bachelor's Degree Programme in Business Information Technology
Week11 (exam) Week13 (re-exam) Week15 (re-exam)
Week2-6: Lectires Week7-9: Independent group work with the exercise Week10: Presentation of exercises Week11: Exam Week13: Re-exam Week15: Re-exam
Mainly contact lessons on campus. Exercises are made in groups individually. Presentation of exercises will be done physically on campus. Virtual exam.
Lectures 20h Exercise 60h Exercise presentation 2h Prepping for exam 50h Exam 2h
Basics of Business Intelligence and Knowledge Management: the philosophy, the systems, the implementation Basics of data analytics: descriptive, classification, prediction Digitalization of business: customers, operations, revenue models The student -understands the value of business information -can name and use BI/KM applications, understands their features -understands the basics of data mining, data warehousing and analyzing -understands how digitalization and globalization drives the business landscape -understands digitized revenue models and their properties -understands changing consumer behavior
Cannot name the functionalities of BI/KM-systems Cannot name data mining methods Does not understand the importance of digitalization in business
Can name the functionalities of BI/KM-systems Can name data mining methods Understands the importance of digitalization in business
Can use BI/KM-systems Can name the properties and use cases of data mining methods Can name practical issues of digitalized business cases
Can apply BI/KM-systems to different scenarios Can apply cases of data mining methods Can name development issues of digitalized business cases