Universität Wien
Achtung! Das Lehrangebot ist noch nicht vollständig und wird bis Semesterbeginn laufend ergänzt.

040310 KU Modelling and Handling of Large Databases (MA) (2021S)

6.00 ECTS (4.00 SWS), SPL 4 - Wirtschaftswissenschaften
Prüfungsimmanente Lehrveranstaltung
DIGITAL
Moodle

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

max. 50 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

Dieser Kurs wird komplett digital stattfinden. Webcam und Mikrofon sind zur Teilnahme empfohlen.

  • Dienstag 02.03. 09:45 - 11:15 Digital
  • Mittwoch 03.03. 11:30 - 13:00 Digital
  • Dienstag 09.03. 09:45 - 11:15 Digital
  • Mittwoch 10.03. 11:30 - 13:00 Digital
  • Dienstag 16.03. 09:45 - 11:15 Digital
  • Mittwoch 17.03. 11:30 - 13:00 Digital
  • Dienstag 23.03. 09:45 - 11:15 Digital
  • Mittwoch 24.03. 11:30 - 13:00 Digital
  • Dienstag 13.04. 09:45 - 11:15 Digital
  • Mittwoch 14.04. 11:30 - 13:00 Digital
  • Dienstag 20.04. 09:45 - 11:15 Digital
  • Mittwoch 21.04. 11:30 - 13:00 Digital
  • Dienstag 27.04. 09:45 - 11:15 Digital
  • Mittwoch 28.04. 11:30 - 13:00 Digital
  • Dienstag 04.05. 09:45 - 11:15 Digital
  • Mittwoch 05.05. 11:30 - 13:00 Digital
  • Dienstag 11.05. 09:45 - 11:15 Digital
  • Mittwoch 12.05. 11:30 - 13:00 Digital
  • Dienstag 18.05. 09:45 - 11:15 Digital
  • Mittwoch 19.05. 11:30 - 13:00 Digital
  • Mittwoch 26.05. 11:30 - 13:00 Digital
  • Dienstag 01.06. 09:45 - 11:15 Digital
  • Mittwoch 02.06. 11:30 - 13:00 Digital
  • Dienstag 08.06. 09:45 - 11:15 Digital
  • Mittwoch 09.06. 11:30 - 13:00 Digital
  • Dienstag 15.06. 09:45 - 11:15 Digital
  • Mittwoch 16.06. 11:30 - 13:00 Digital
  • Dienstag 22.06. 09:45 - 11:15 Digital
  • Mittwoch 23.06. 11:30 - 13:00 Digital
  • Dienstag 29.06. 09:45 - 11:15 Digital
  • Mittwoch 30.06. 11:30 - 13:00 Digital

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

The course introduces central methods to understand modeling and daily usage (CRUD operations) of databases and the characteristics of computer-based information systems. This knowledge will be applied to aggregate information and to facilitate and accelerate decision-making processes. Particular attention will be paid to conceptual and logical databases design, data analysis using SQL, algorithms for selecting materialized views, databases systems technology (indexes, star query optimization, physical design, query rewrite methods to use materialized views), and tools for managing a large amount of data. The student will acquire knowledge of the fundamental concepts to design and use database models. Furthermore, the student will learn to generate reports, data cubes and evaluate the performance of the modeled key processes to improve them. Beyond the relational part, we will have a look at NoSQL databases, such as Graphdatabases, Textdatabases and Document oriented databases. If there is enough time, the students will use process mining based on event-logs to model business scenarios.

This course consists of lectures, homework, and project presentations. Students will work on their projects in interdisciplinary groups.

Generic goals:
- Teamwork
- Improvement of programming skills
- Understanding of interplay in Business Administration and databases.

This course consists of lectures, homework, and project presentations. Students will work on their projects in interdisciplinary groups.

Generic goals:
- Teamwork
- Improvement of programming skills
- Understanding of interplay in Business Administration and databases.

Art der Leistungskontrolle und erlaubte Hilfsmittel

Midterm test (30%, 5th May 2021)
Final test (20%, 30th June 2021 )
Pen and Paper homework (10%, during the second part)
Project Work (40%, ongoing work )

Mindestanforderungen und Beurteilungsmaßstab

In total, 100 points can be achieved. Grades are assigned as follows:
1 (very good) • 100-87 %
2 (good) • 86-75 %
3 (satisfactory) • 74-63 %
4 (sufficient) • 62-50 %
5 (not enough) • 49-0 %

Prüfungsstoff

Slides and topics covered in the lectures.

Literatur

- Paulraj Ponniah, Data Warehousing Fundamentals for IT Professionals, Second Edition, Wiley
- Wil van der Aalst, Process Mining - Data Science in Action, Second Edition, Springer

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Fr 12.05.2023 00:12