Foundations in Data Engineering
For any questions regarding this lecture, please contact us using: email@example.com
This website provides preliminary information on the course organization. The lecture itself will be organized via this moodle course. You are automatically added to the moodle course when you register for the lecture in TUMOnline. The moodle course will be updated the week before the lecture starts.
- Lecture: Tuesdays, 4 - 6 p.m. & Thursdays, 4 - 6 p.m.
Start: October 19, 2021
- Tutorial Sessions: There are five sessions available which cover the same topics.
Please see the moodle course for details and how to enroll.
Start: week of October 27, 2021
- Moodle Course: If you cannot access the moodle course because you are not completely enrolled for your master yet, please mail the teaching assistants (Mr. Beischl & Mr. Reif) using firstname.lastname@example.org.
Corona (COVID-19) Information
Due to the COVID-19 pandemic, the lecture will be taught in hybrid mode.
- Lecture: on-site and recordings (published on Moodle)
- Tutorials: on-site and online (Big Blue Button, link will be published in Moodle)
- Exam & Retake Exam: only on-site at TUM
There are two lectures per week at TUM each Tuesday (4 - 6 p.m.) and Thursday (4 - 6 p.m.). Lecture recordings will be uploaded to the moodle course.
If the infection rate increases during the semester, we might need to adapt the lecture mode. However, the lecture recordings are uploaded for students that can't visit the on-site lecture. We will announce updates in Moodle.
The tutorial session will take place on-sight and online live sessions using the tool Big Blue Button.
We offer online and on-site time slots, all covering the same content.
Thus, you only need to attend one tutorial session per week.
You can register for a slot via TUMOnline. This will be explained during the first lecture week.
After registration, we provide you a link to the tutorial session of your time slot.
Please always watch the lecture before participating in the tutorial session!
The exam will be held on-site (attendence in person required) at TUM and there will also be a retake exam (also on-site).
There will be three bonus projects that accompany this lecture.
All three projects are programming tasks.
If you complete all three projects, you will receive a grade bonus of 0.3 on your final exam grade.
The grade bonus is only applied on passed exams (4.0 or better).
The programming tasks will be done in C++ and Scala.
Prior C++ knowledge is required, but you can also learn it yourself during the semester.
The bonus projects will be published in the moodle course.
C++ learning materials:
- Basic Building Blocks
- Advanced SQL
- SQL Query Unnesting
- Distributed Data Processing
- No-SQL Databases
- Other Data Models
- Neo Join
- RDF Query Optimization
Please find all exercise sheets, discussion and further material on the moodle course.
- Anand Rajaraman, Jeffrey David Ullman Mining of Massive DatasetsCambridge University Press B31
- Maurice Herlihy, Nir Shavit The Art of Multiprocessor Programming Morgan Kaufmann, 2012.
- Garcia-Molina, Ullman, Widom Database Systems: The Complete Book Prentice Hall, 2000.
- Alfons Kemper, André Eickler Datenbanksysteme. Eine Einführung 10., aktualisierte und erweiterte Auflage, Oldenbourg Verlag, 2015.