Hasso-Plattner-Institut25 Jahre HPI
Hasso-Plattner-Institut25 Jahre HPI
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Approximate Data Profiling (Wintersemester 2022/2023)

Dozent: Prof. Dr. Felix Naumann (Information Systems) , Tobias Bleifuß (Information Systems) , Youri Kaminsky
Website zum Kurs: https://hpi.de/naumann/teaching/current-courses/ws-22-23/approximate-data-profiling.html

Allgemeine Information

  • Semesterwochenstunden: 4
  • ECTS: 6
  • Benotet: Ja
  • Einschreibefrist: 01.10.2022 - 30.10.2022
  • Prüfungszeitpunkt §9 (4) BAMA-O: 08.12.2022
  • Lehrform: Projektseminar
  • Belegungsart: Wahlpflichtmodul
  • Lehrsprache: Englisch
  • Maximale Teilnehmerzahl: 6

Studiengänge, Modulgruppen & Module

IT-Systems Engineering MA
Data Engineering MA
  • DANA: Data Analytics
    • HPI-DANA-K Konzepte und Methoden
  • DANA: Data Analytics
    • HPI-DANA-T Techniken und Werkzeuge
  • DANA: Data Analytics
    • HPI-DANA-S Spezialisierung
  • CODS: Complex Data Systems
    • HPI-CODS-K Konzepte und Methoden
  • CODS: Complex Data Systems
    • HPI-CODS-T Techniken und Werkzeuge
  • CODS: Complex Data Systems
    • HPI-CODS-S Spezialisierung
Software Systems Engineering MA

Beschreibung

Data profiling is the process of extracting metadata from datasets. One important aspect is the discovery of data dependencies, such as Functional Dependencies (FDs), Inclusion Dependencies (INDs) and Unique Column Combinations (UCCs). However, the increasing size of datasets presents a challenge to traditional approaches of data profiling. Therefore, this seminar focuses on sampling-based methods for approximate data profiling.

First, the students become familiar with related work as an inspiration. Afterwards, each student team develops own ideas. These can concern both the sampling process itself or the actual discovery in the sample.

The students turn their ideas into working algorithms. There are two main goals for each algorithm:
1) Find a set of dependencies that is close to the actual solution.
2) Minimize the required runtime.
Benchmark Datasets are provided to the students.
Finally, the students present their approaches and write a short report.

Literatur

Lern- und Lehrformen

Project seminar with weekly meetings, talks, discussions and report writing

Leistungserfassung

Presentation and report

Termine

See webpage.

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