623.500 (21S) Data Engineering

Sommersemester 2021

Registration deadline has expired.

First course session
08.03.2021 10:00 - 12:00 online Off Campus
... no further dates known

Overview

Due to the COVID-19 pandemic, it may be necessary to make changes to courses and examinations at short notice (e.g. cancellation of attendance-based courses and switching to online examinations).

For further information regarding teaching on campus, please visit: https://www.aau.at/en/corona.
Lecturer
Course title german Data Engineering
Type Lecture - Course (continuous assessment course )
Course model Online course
Hours per Week 2.0
ECTS credits 4.0
Registrations 24 (30 max.)
Organisational unit
Language of instruction English
Course begins on 08.03.2021
eLearning Go to Moodle course

Time and place

Please note that the currently displayed dates may be subject to change due to COVID-19 measures.
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Course Information

Intended learning outcomes

The successful student will have a deeper understanding of the challenges imposed by Big Data and know state of the art data engineering methods and techniques focusing on big data applications. 



Teaching methodology including the use of eLearning tools

The VC will be a mixture of a classical lecture, presentations of assignment solutions and student presentations. The course will be held fully online via MS Teams.

Course content

  • Introduction to Big Data, Data Engineering and Data Science.
  • Recap on RDBMS and common file formats. 
  • Managing XML and JSON in RDBMS. 
  • Advanced SQL queries.
  • Scaling of RDBMS. 
  • Data Warehouses
  • Big Data Frameworks
    • MapReduce
    • Apache Spark
    • SQL on Big Data Architectures
  • (Big) Data Integration
  • Data Provenance and Data Quality
  • Data Lakes

Prior knowledge expected

Relational Databases (Lecture "Datenbanken"),  Java Programming


Literature

Principles of Database Management: The Practical Guide to Storing, Managing and Analyzing Big and Small Data. Cambridge University Press New York, NY, USA ©2018 ISBN:1107186129 9781107186125

Examination information

Im Fall von online durchgeführten Prüfungen sind die Standards zu beachten, die die technischen Geräte der Studierenden erfüllen müssen, um an diesen Prüfungen teilnehmen zu können.

Examination methodology

  • Credits for weekly assignments.
  • Project and Project Presentation.
  • Final Exam (either written, or oral, depending on the pandemic situation)

Examination topic(s)

All topics addressed by the lecture or practical parts.

Assessment criteria / Standards of assessment for examinations

the successful participant will have reached at least 50% of all parts (weekly assignments, project, and final exam)

Grading scheme

Grade / Grade grading scheme

Position in the curriculum

  • Master's degree programme Informatics (SKZ: 911, Version: 19W.2)
    • Subject: Vertiefung Informatik (Specialization in Informatics) (Compulsory subject)
      • 1.1 Data Engineering ( 2.0h VC / 4.0 ECTS)
        • 623.500 Data Engineering (2.0h VC / 4.0 ECTS)
          Absolvierung im 1. Semester empfohlen
  • Master's degree programme Information Management (SKZ: 922, Version: 19W.1)
    • Subject: Informatics (Compulsory subject)
      • 1.1 Data Engineering ( 0.0h VC / 4.0 ECTS)
        • 623.500 Data Engineering (2.0h VC / 4.0 ECTS)
          Absolvierung im 1. Semester empfohlen

Equivalent courses for counting the examination attempts

Sommersemester 2024
  • 623.500 VC Data Engineering (2.0h / 4.0ECTS)
Wintersemester 2023/24
  • 623.500 VC Data Engineering (2.0h / 4.0ECTS)
Sommersemester 2023
  • 623.500 VC Data Engineering (2.0h / 4.0ECTS)
Wintersemester 2022/23
  • 623.500 VC Data Engineering (2.0h / 4.0ECTS)
Sommersemester 2022
  • 623.500 VC Data Engineering (2.0h / 4.0ECTS)
Wintersemester 2021/22
  • 623.500 VC Data Engineering (2.0h / 4.0ECTS)
Wintersemester 2020/21
  • 623.500 VC Data Engineering (2.0h / 4.0ECTS)
  • 623.501 VC Data Engineering (2.0h / 4.0ECTS)
Wintersemester 2019/20
  • 623.500 VC Data Engineering (2.0h / 4.0ECTS)