Universität Wien

040310 KU Modelling and Handling of Large Databases (MA) (2025S)

6.00 ECTS (4.00 SWS), SPL 4 - Wirtschaftswissenschaften
Prüfungsimmanente Lehrveranstaltung
Moodle
Di 29.04. 09:45-11:15 PC-Seminarraum 1, Kolingasse 14-16, OG01

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

  • Dienstag 04.03. 09:45 - 11:15 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Mittwoch 05.03. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Dienstag 11.03. 09:45 - 11:15 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Dienstag 18.03. 09:45 - 11:15 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Mittwoch 19.03. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Dienstag 25.03. 09:45 - 11:15 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Mittwoch 26.03. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Dienstag 01.04. 09:45 - 11:15 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Mittwoch 02.04. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Dienstag 08.04. 09:45 - 11:15 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Mittwoch 09.04. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Mittwoch 30.04. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Dienstag 06.05. 09:45 - 11:15 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Mittwoch 07.05. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Dienstag 13.05. 09:45 - 11:15 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Mittwoch 14.05. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Dienstag 20.05. 09:45 - 11:15 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Mittwoch 21.05. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Dienstag 27.05. 09:45 - 11:15 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Mittwoch 28.05. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Dienstag 03.06. 09:45 - 11:15 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Mittwoch 04.06. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Dienstag 10.06. 09:45 - 11:15 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Mittwoch 11.06. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Dienstag 17.06. 09:45 - 11:15 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Mittwoch 18.06. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Dienstag 24.06. 09:45 - 11:15 PC-Seminarraum 1, Kolingasse 14-16, OG01
  • Mittwoch 25.06. 11:30 - 13:00 PC-Seminarraum 1, Kolingasse 14-16, OG01

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

The course introduces central methods to understand the 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 database design, data analysis using SQL, algorithms for selecting materialized views, database systems technology, and tools for managing a large amount of data. The student will acquire knowledge of the fundamental concepts to design and use database models. Beyond the relational part, we will have a look at NoSQL databases, such as Graphdatabases, Textdatabases, and Document-oriented databases.

This course consists of lectures, homework, and exams.

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

Students of the Master Business Analytics program who have not yet passed the exam "Introduction to Programming with Python" can be admitted to the course on a daily basis after successfully passing the exam. Please contact the course management for this purpose.

Art der Leistungskontrolle und erlaubte Hilfsmittel

Midterm test (35%)
Final test (35%)
Homework/Exercises(30% )

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

- Ramakrishnan and Gehrke. Database Management Systems. 3rd Edition
- Garcia-Molina, Ullmann. Database Systems 2nd Edition. Prentice Hall
- 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: Mo 17.02.2025 21:25