Open Source Data Processing (Wintersemester 2020/2021)

Lecturer: Prof. Dr. Tilmann Rabl (Data Engineering Systems) , Lawrence Benson (Data Engineering Systems)
Course Website: https://hpi.de/rabl/teaching/winter-term-2020-21/open-source-data-processing.html

General Information

Weekly Hours: 4
Credits: 6
Graded: yes
Enrolment Deadline: via email to us by Nov 6th 23:59
Teaching Form: Project seminar
Enrolment Type: Compulsory Elective Module
Course Language: English
Maximum number of participants: 9

Programs, Module Groups & Modules

Cybersecurity MA

Data Engineering MA

IT-Systems Engineering MA

IT-Systems Engineering
- HPI-ITSE-K Konstruktion
IT-Systems Engineering
- HPI-ITSE-M Maintenance
SAMT: Software Architecture & Modeling Technology
- HPI-SAMT-K Konzepte und Methoden
SAMT: Software Architecture & Modeling Technology
- HPI-SAMT-T Techniken und Werkzeuge
SAMT: Software Architecture & Modeling Technology
- HPI-SAMT-S Spezialisierung

Description

The digital revolution leads to ever increasing amounts of data and a massively increased pace of data generation. In many use cases, archival of the data and later processing is either impossible or uneconomic due to the speed and amount of the data and the quick loss in value of data analysis over time. This has led to the development of stream processing engines (SPE), which can analysis large amounts of data in motion. This leads to two major challenges, the handling of time and potentially endless streams. In this course, we will focus on the SPE Apache Flink and develop code to support its ecosystem.

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