Introduction to Data Economy (1 cr)
28.11.2022 - 21.05.2023
01.12.2022 - 30.06.2023
Number of ECTS credits allocated
Mode of delivery
Korkeakouluyksikkö D, Verkkokampus, tiko
Laurea Virtual Campus
0 - 500
- Complementary competence, master’s studies in English (CYJ2), Generic studies
- Heli Kulomaa
- Suvi Valsta
Teacher in charge
- Avoin AMK (Size: 200. Open UAS: 200.)
CYJ23KJComplementary competence (master’s studies in English), K23, Generic studies
- Avoin AMK
Student is able to
- Explain why organizations need to apply data in decision making
- Explain where the data comes from and how it can be used (buying, selling, collecting data, big data from IoT, digital platforms and APIs, machine learning and AI vs. statistical methods)
- Identify the role of information in a value creation process
- Identify key business models enabled by digital data
- List a few “no-code” ways of experimenting with data products to validate the business model
- Summarize how intellectual privacy regulations shape the data economy
Online course available for independent study at the student's own pace.
Learning materials and recommended literature
All necessary materials are provided on the course platform.
Alternative completion methods of implementation
Co-operation with working life and/or RDI
Course has been produced in corporation with Osaango Oy. Lecturers on the videos are experts in data economy.
1 ECTS credits = 27 hours of work
Content and scheduling
Videos, quizzes and articles in four different modules.
Module 1: Data economy in brief
Module 2: Data sources and business models
Module 3: Role of information in value creation
Module 4: Next steps in data economy
After this course, you will be able to:
Explain why organizations need to apply data in decision making
Explain where the data comes from and how it can be used (buying, selling, collecting data, big data from IoT, digital platforms and APIs, machine learning and AI vs. statistical methods)
Identify the role of information in a value creation process
Identify key business models enabled by digital data.
List a few “no-code” ways of experimenting with data products to validate the business model
Summarize how privacy regulations shape the data economy
Further information for students
Inquiries for the course can be directed to firstname.lastname@example.org.
Evaluation methods and criteria
For a passing grade, student has to complete all the required tests with a minimum score of 50%, all the required assignments and familiarise themselves with the course materials.