Expert of the future – Knowledge management in decision-making (3cr)
Code: MS00CZ52-3002
General information
- Enrollment
- 01.09.2025 - 15.09.2025
- Registration for the implementation has begun.
- Timing
- 01.10.2025 - 31.10.2025
- The implementation has not yet started.
- Number of ECTS credits allocated
- 3 cr
- Local portion
- 0 cr
- Virtual portion
- 3 cr
- Mode of delivery
- Distance learning
- Unit
- Yhteiset palvelut
- Campus
- Location-independent
- Teaching languages
- Finnish
- Seats
- 5 - 200
- Degree programmes
- Master of Management and Leadership in Health Care
- Teachers
- Anu Vaihekoski
- Minna Salakari
- Anne Rouhelo
- Scheduling groups
- Avoimen AMK:n kiintiöpaikat. Ilmoittaudu ilman tätä pienryhmää. (Size: 2000 . Open UAS : 2000.)
- Small groups
- Open UAS quota. Please enroll without selecting this group.
- Course
- MS00CZ52
Unfortunately, no reservations were found for the realization Expert of the future – Knowledge management in decision-making MS00CZ52-3002. It's possible that the reservations have not yet been published or that the realization is intended to be completed independently.
Evaluation scale
H-5
Content scheduling
The course focuses on the role of data-driven management in supporting decision-making, particularly from the perspectives of practical data collection, analysis, and decision support.
Course Objectives
The student will:
- Understand the importance of data-driven management in decision-making and organizational development.
- Be able to identify and define the information and sources needed to support decision-making.
- Master the basics of data collection and analysis, as well as the use of data-based decision-making models.
- Develop skills in utilizing analytics and data-driven management tools in decision-making.
Core Topics
Fundamentals of Data-Driven Management
Definition and role of data-driven management
Organizational data management: How do organizations collect, store, and share information? What are the roles of data repositories and structures?
Data Collection for Decision Support
Data analysis and data collection techniques
Databases and information sources
Principles of data protection and security: Ethical use of data and privacy protection
Data Analysis in Decision-Making
Analysis tools and methods
Data-driven decision-making
Tools for Data-Driven Decision-Making
Strategic decision-making through data
Using data in strategic planning and operational decision-making
Objective
After completing the course, the student the student will:
- Understand the importance of data-driven management in decision-making and organizational development.
- Be able to identify and define the information and sources needed to support decision-making.
- Master the basics of data collection and analysis, as well as the use of data-based decision-making models.
- Develop skills in utilizing analytics and data-driven management tools in decision-making.
Content
- Fundamentals of Data-Driven Management
- Data Collection for Decision Support
- Data Analysis in Decision-Making
- Tools for Data-Driven Decision-Making
Materials
Oppimateriaali on koottu ItsLearning-verkkoympäristöön.
Teaching methods
The course is delivered as an independent online course in the itsLearning learning environment.
Learning methods and assignments
Recorded online lectures on the topics of the course.
Theory and practical examples of data-driven management, the basics of data analysis, and methods used to support decision-making.
Discussion assignments where students apply the learned theory in practice.
Online exams and tests.
Pedagogic approaches and sustainable development
The course employs diverse pedagogical methods that combine lecture-based teaching, practical application, interactivity, and digital assessment.
Completion alternatives
Ei valinnaisia toteutustapoja.
Student workload
The course module is worth 3 ECTS credits, equivalent to 81 hours of student work, and can be allocated as follows:
Recorded online lectures on course topics: 5 hours
Independent study and familiarization with materials: 25 hours
Discussion assignments: 10 hours
Online exams and tests: 31 hours
Written assignment: 10 hours
Evaluation methods and criteria
The student must obtain an approved result of all the sections of the course in order for the whole to be accepted and assessable.
A maximum of 100 points can be earned for the course. Assessment of the course by score:
Excellent (5): 91100 points
Good (4): 7890 points
Good (3): 6377 points
Satisfactory (2): 5062 points
Satisfactory (1): 4049 points
Rejected: 039 points