Prof. Dr. Tilmann Rabl

Lecture Series on Practical Data Engineering


Prof. Dr. Tilmann Rabl, Prof. Dr. Felix Naumann


The Lecture Series on Practical Data Engineering will feature presentations by distinguished speakers from industry and academia on the topic of data engineering. We will cover topics on the application of data engineering in industrial setups as well as system level advancements in data engineering research.


The agenda will be finalized until the start of the semester.

15.10.IntroductionTilmann Rabl, Felix Naumann
22.10.Recommending Tourist Activities - Data Science Challenges And The Needs for Data PipelinesMaximilian Jenders, GetYourGuide
29.10.20 Years HPI Conference - no lecture 
05.11.Towards Interactive Data AnalyticsCarsten Binnig, TU Darmstadt
12.11.File Metadata Management at SnowflakeMax Heimel, Martin Hentschel, Snowflake
19.11.Introduction to Apache FlinkArvid Heise, Ververica
26.11.Deep Earth Query: Advances in Satellite Image Indexing from Massive ArchivesBegüm Demir, TU Berlin
03.12.Scale-In, then Scale-Out - New Database Scaling Options with FPGAs and Hardware AccelerationYana Krasteva, Thomas Richter, Swarm64
10.12.Dimensions of Hardware Parallelism and Exploiting Them for Data-Intensive SystemsPinar Tözün, IT University of Copenhagen
10.12.SAP HANA Software Development ProcessAlexander Böhm, SAP
07.01.A Programming Language and Compiler View on Data Management and Machine Learning SystemsTiark Rompf, Purdue University
14.01.Applications of AI in the Credit Information BusinessGjergji Kasneci, Uni Tübingen
21.01.Ethical Data EngineeringBirgit Beck, TU Berlin
28.01.Data CleaningZiawasch Abedjan, TU Berlin
04.02.Poster PresentationsTilmann Rabl, Felix Naumann

General Information

Time and Location: Tuesdays 5:00 - 6:30 pm, HS 2

The course is graded and has 3 ECTS.


Lecture Summary

You have to write a summary for one lecture. Depending on the number of participants, this will be done in groups. Each lecture will be assigned to one person or group.

All summaries will be published on the course website. The summary should give a quick and engaging overview of the talk (10-15 min reading time). We will ask the presenters to review your summary and help you with questions.

Individual Poster Project

You have to prepare an A1 poster, with one of the following contents. You will be able to present your poster at the final session.

For Bachelor Students

Based on one or more of the lectures, you can either prepare a technology landscape or explain a data science or data engineering process. Both should be as detailed as possible.

For Master Students

Extending technology or methodology presented in one or multiple of the lectures, you should prepare a research project proposal. The poster should highlight goal, problem, and solution of your proposal and the connection to the lecture.

Mark Breakdown

  • 50% Lecture summary
  • 50% Individual poster project



Poster Download