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Course module: JM0140-M-6
JM0140-M-6
Data Engineering
Course info
Course moduleJM0140-M-6
Credits (ECTS)6
CategoryMA (Master)
Course typeCourse
Language of instructionEnglish
Offered byTilburg University; Tilburg School of Economics and Management; TiSEM: Management; TiSEM: Management;
Is part of
M Data Science and Entrepreneurship (joint degree)
Lecturer(s)
Lecturer
dr. D. Di Nucci
Other course modules lecturer
Lecturer
prof. dr. W.J.A.M. van den Heuvel
Other course modules lecturer
Lecturer
M. Mohammadi
Other course modules lecturer
Lecturer
E.U. Syed
Other course modules lecturer
Lecturer
dr. I.P.K. Weerasingha Dewage
Other course modules lecturer
Academic year2020
Starting block
SM 1
Course mode
Full-time
RemarksCaution: this information is subject to change
Registration openfrom 25/08/2020 up to and including 20/08/2021
Aims
The main goal of the Data Engineering course is threefold.
Firstly, students will learn the fundamental principles and techniques underpinning off-line data engineering and integration. This involves data modeling with ER/relational models, object data models, NoSQL data models, and integration techniques to synthesize them.
Secondly, students will learn the basic principles and mechanisms to develop run-time data integration, storage and processing. This includes: distributed (cloud) computing, distributed database architectures, batch/stream processing, complex event processing, and runtime data integration.
Lastly, at the end of this course, course participants will be able to judge from an architectural (conceptual) and implementation perspective, when which off- or/and online solution suits best to address particular practical challenges.
 
Content
The courses from the Data Science and Entrepreneurship program require specific prior knowledge. It is only possible to participate in this course if approved by the admission committee and if you are enrolled for the program.
Please note that this course will be taught in Mariënburg, ‘s-Hertogenbosch (JADS).
 
Recommended reading:
  1. Zomaya, Albert Y., and Sherif Sakr, eds. Handbook of Big Data Technologies. Berlin: Springer, 2017.
  2. Articles will be posted on Blackboard during the semester, creating a ”living” Syllabus.
Other useful texts:
  1. Kleppmann, Martin. Designing data-intensive applications: The big ideas behind reliable, scalable, and maintainable systems. " O'Reilly Media, Inc.", 2017.
  2. Gregor Hohpe and Bobby Woolf., Enterprise Integration Patterns: Designing, Building, and Deploying Messaging Solutions, 1st Edition, 2004, ISBN 978-0321200686.
Type of instructions:
A mixture of lectures, tutorials, workshops will be followed. Practical course assignments will be conducted with the help of and involving industry practitioners to demonstrate immediate practical relevance.
Type of exams:
The course will be based on a formal exam and practical assignments involving a real-world project submitted possibly by external organizations (in areas such as health, business, logistics, etc) .
Contact person
D.A. Tamburri PhD
Timetable information
Data Engineering
Written test opportunities
DescriptionTestBlockOpportunityDate
Written test opportunities (HIST)
DescriptionTestBlockOpportunityDate
Schriftelijk / WrittenEXAM_01SM 1110-12-2020
Schriftelijk / WrittenEXAM_01SM 1214-01-2021
Required materials
-
Recommended materials
-
Tests
Design and programming

Written

Final grade

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