Big data processing and applications

Max amounts of FITech students: 30

Persons without a valid study right at a Finnish university or university of applied sciences have preference to this course.

During this course, the student gets familiar with the concept of “Big data” and different phenomena related to it, including requirements and principles for data intensive systems and their implementation as well as benefits, risks and restrictions of available big data solutions.

Course topics include general introduction into big data, namely: big data fundamentals, data storage, batch and stream data processing, data analysis, privacy and security, big data use cases.

Learning outcomes

Upon completion of the course, the student

1. can identify real life cases where big data solutions are needed and design basic solutions to big data problems.
2. is able to explain the big data phenomenon, its challenges and opportunities
3. is able to explain the requirements and common principles for data intensive systems design and implementation, and evaluate the benefits, risks and restrictions of available solutions
4. can explain the principles of big data management and processing technologies and utilize them on a basic level.

Teaching methods

The course includes lectures, exercises, seminars as well as independent and group work. The course is fully online. All the material will be available in course Moodle pages, no lecture recordings will be made. There are deadlines, which would be communicated when the course starts.

Completion methods

This course assesses students continuously by the completion of a small project work or literature review report, mandatory exercises, and seminar presentations (mandatory participation on scheduled time). To pass the course, it is enough to get 50 % of the available points. The course doesn’t have an exam.

More information in the University of Oulu study guide.

You can get a digital badge after completing this course.

data-analytiikka data-analyysi massadata datan käsittely data science data processing, Distributed systems, Data management