Big Data Engineering (5 op)

Arviointiasteikko

H-5

Sisällön jaksotus

-The basic idea of data engineering methods and pipelines
-different components
-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

Tavoitteet

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

Sisältö

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

Oppimateriaalit

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

Opetusmenetelmät

Contact learning, practical exercises, independent study

Pedagogiset toimintatavat ja kestävä kehitys

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

Opiskelijan ajankäyttö ja kuormitus

Contact hours 56 h
Inpendent studying 79h, including:
- Studying the course material
- Completing exercises
- Project

Arviointimenetelmät ja arvioinnin perusteet

Homework exercises returned throughout the course
Small project at the end of the course

Lisätiedot

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.