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Archived Curricula Guide 2017–2019
Curricula Guide is archieved. Please refer to current Curricula Guides
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
Intermediate Studies in Computer Science
Faculty of Natural Sciences
Compulsory Introductory Studies
2018–2019
Teaching
Archived Teaching Schedule. Please refer to current Teaching Shedule.
Period I Period II Period III Period IV
TIETA17 Introduction to Big Data Processing
Faculty of Natural Sciences
Degree Programmes