Big Data Engineering (5 cr)

Evaluation scale

H-5

Content scheduling

-The basic idea of big data engineering methods and pipelines
-different components and processes
-integration of said components (MQ systems)
-data engineering frameworks (Apache family)
-The goal of the course is to be able to build a data pipeline from start to finish and to understand both the process and the different components and their role.

Objective

After completing the course the student can:
- describe basic solutions for data architectures and big data
- select and use suitable data architecture
- apply ETL process and tools for handling of big data

Content

Architecture and Components of Big Data Frameworks
ETL process with Big Data for batch and streaming
Practical work with suitable tools and frameworks

Materials

Teacher provided lecture material
Supporting public online material
All needed material (or at least a link to them) will be available in itslearning.

Teaching methods

Contact learning, practical exercises, independent study

Exam schedules

There's an exam in April, re-exam in May.

International connections

Given examples and exercises support each topic studied during the lectures. Additional material in the form of tutorials and reliable information sources is provided.

Student workload

Contact hours 44 h
Independent studying 91h, including:
- Studying the course material
- Completing exercises
- Exam

Further information

Itslearning and contact classes are the main communication channels used on this course.

The student is required to have a computer capable of running a simple Ubuntu virtual machine and basic skills to work with Ubuntu command line.