623.501 (20W) Data Engineering
Overview
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 20 (30 max.)
- Organisational unit
- Language of instruction English
- Course begins on 01.10.2020
- eLearning Go to Moodle course
Time and place
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.
- Big Data Frameworks
- MapReduce
- Apache Spark
- SQL on Big Data Architectures
- (Big) Data Integration
- Data Provenance and Data Quality
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
Modified examination information (exceptional COVID-19 provisions)
Online final project presentation with questions on theory topics.
Examination methodology
Oral exam.
Examination topic(s)
Project and theory topics.
Assessment criteria / Standards of assessment for examinations
Online oral exam.
Grading scheme
Grade / Grade grading schemePosition 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)
- 623.501 Data Engineering (2.0h VC / 4.0 ECTS) Absolvierung im 1. Semester empfohlen
-
1.1 Data Engineering (
2.0h VC / 4.0 ECTS)
-
Subject: Vertiefung Informatik (Specialization in Informatics)
(Compulsory subject)
- 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)
- 623.501 Data Engineering (2.0h VC / 4.0 ECTS) Absolvierung im 1. Semester empfohlen
-
1.1 Data Engineering (
0.0h VC / 4.0 ECTS)
-
Subject: Informatics
(Compulsory subject)
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)
-
Sommersemester 2021
- 623.500 VC Data Engineering (2.0h / 4.0ECTS)
-
Wintersemester 2020/21
- 623.500 VC Data Engineering (2.0h / 4.0ECTS)
-
Wintersemester 2019/20
- 623.500 VC Data Engineering (2.0h / 4.0ECTS)