Lecture Series on Practical Data Engineering

Instructors

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

Description

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.

Agenda

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

Date	Topic	Lecturer
15.10.	Introduction	Tilmann Rabl, Felix Naumann
22.10.	Recommending Tourist Activities - Data Science Challenges And The Needs for Data Pipelines	Maximilian Jenders, GetYourGuide
29.10.	20 Years HPI Conference - no lecture
05.11.	Towards Interactive Data Analytics	Carsten Binnig, TU Darmstadt
12.11.	File Metadata Management at Snowflake	Max Heimel, Martin Hentschel, Snowflake
19.11.	Introduction to Apache Flink	Arvid Heise, Ververica
26.11.	Deep Earth Query: Advances in Satellite Image Indexing from Massive Archives	Begüm Demir, TU Berlin
03.12.	Scale-In, then Scale-Out - New Database Scaling Options with FPGAs and Hardware Acceleration	Yana Krasteva, Thomas Richter, Swarm64
10.12.	Dimensions of Hardware Parallelism and Exploiting Them for Data-Intensive Systems	Pinar Tözün, IT University of Copenhagen
10.12.	SAP HANA Software Development Process	Alexander Böhm, SAP
07.01.	A Programming Language and Compiler View on Data Management and Machine Learning Systems	Tiark Rompf, Purdue University
14.01.	Applications of AI in the Credit Information Business	Gjergji Kasneci, Uni Tübingen
21.01.	Ethical Data Engineering	Birgit Beck, TU Berlin
28.01.	Data Cleaning	Ziawasch Abedjan, TU Berlin
04.02.	Poster Presentations	Tilmann Rabl, Felix Naumann

General Information

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

The course is graded and has 3 ECTS.

Deliverables

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.