TIETA17 Introduction to Big Data Processing 5 ECTS
Organised by
Degree Programme in Computer Sciences
Person in charge
University Lecturer Heikki Hyyrö
Preceding studies
Recommended:
Corresponding course units in the curriculum
School of Information Sciences
Curricula 2015 – 2017

Learning outcomes

After completing the course the student is expected to
- know typical characteristics and common applications of big data
- know the basics of distributed file systems, databases and computing
- have gained practical data processing skills with the MapReduce framework / Apache Hadoop.

Contents

Characteristics and applications of big data. Structured and unstructured data. Distributed file systems. Distributed and relational/non-relational databases. Distributed computing. MapReduce framework. Apache Hadoop.

Teaching language

English

Modes of study

Option 1
Available for:
  • Degree Programme Students
  • Other Students
  • Open University Students
  • Doctoral Students
  • Exchange Students
Participation in course work 
In English

Evaluation

Numeric 1-5.

Study materials

Will be announced in class

Belongs to following study modules

Faculty of Natural Sciences
Faculty of Natural Sciences
2017–2018
Teaching
Faculty of Natural Sciences