Data analyticsLaajuus (5 cr)
Code: LI00BS44
Credits
5 op
Objective
Learning outcomes
The student is able to
- Produce exact and predictive information for varied business purposes
describe the integration of data analytics into business processes
- Develop an analytics plan and describe the integration of data analytics into business processes
- Prepare a data analytics development plan for the company
Enrollment
19.11.2021 - 09.01.2022
Timing
10.01.2022 - 31.05.2022
Number of ECTS credits allocated
5 op
Virtual portion
5 op
Mode of delivery
Distance learning
Unit
Faculty of Business and Hospitality Management (LAB)
Campus
E-campus
Teaching languages
- Finnish
Seats
20 - 40
Degree programmes
- Complementary competence and optional courses, Bachelor's
Teachers
- Tarja Keski-Mattinen
Scheduling groups
- Verkkoluennot (Size: 0. Open UAS: 0.)
- Harjoitukset, ohjaus ja esitykset (Size: 0. Open UAS: 0.)
Groups
-
LLABTO22H
Small groups
- Online lectures
- Harjoitukset
Learning outcomes
Learning outcomes
The student is able to
- Produce exact and predictive information for varied business purposes
describe the integration of data analytics into business processes
- Develop an analytics plan and describe the integration of data analytics into business processes
- Prepare a data analytics development plan for the company
Timing and attendance
Active participation is required, but no attendance obligation.
Learning material and recommended literature
Material announced by the lecturer
Working life cooperation
work-oriented assignment
Learning environment
Lectures, teamwork and work-based final assignment
Student time use and work load
27 h of student work is equal to 1 cr
Contents
* Integration of data analytics into business processes
* Needs of Business Information and Data Sources
* Data processing and visualization
Additional information for students: previous knowledge etc.
Basics of Business
Assessment criteria
Excercises and assignment
Assessment scale
1-5
Failed (0)
Student has not achieved the objectives of the course sufficiently.
Assessment criteria: level 1 (assessment scale 1–5)
Student has achieved the objectives of the course sufficiently. Student understands the meaning of data analytics in business processes, and is able to form a visualization of data sources and data transferring in business processes.
Assessment criteria: level 3 (assessment scale 1–5)
Student has achieved the objectives of the course in a good manner.
Student understands the meaning of data analytics in business processes, and is able to form a visualization of data sources and data transferring in business processes. Student is able to participate to designing the data-analytics process plan.
Assessment criteria: level 5 (assessment scale 1–5)
Student has achieved the objectives of the course in an excellent manner. Student understands the meaning of data analytics in business processes and value of it. Student is able to form a visualization of data sources and data transferring in business processes. Student is able to choose valuable methods, and can design a data-analytics process plan.