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Veranstaltungsbeschreibung

335107a Analytische Informationssysteme Vorlesung

Zuletzt geändert:25.09.2017 / Messerschmidt
EDV-Nr:335107a
Studiengänge: Studienübergreifendes Angebot - Minors, Prüfungsleistung im Modul Analytische Informationssysteme in Semester 1
Häufigkeit: derzeit nicht im Angebot
Wirtschaftsinformatik und digitale Medien (Bachelor, 7 Semester) , Prüfungsleistung im Modul Analytische Informationssysteme (ab SS 16) in Semester 4
Häufigkeit: W17/18
Dozent: Prof. Dr. Peter Lehmann
Sprache: Englisch
Art: V
Umfang: 2 SWS
ECTS-Punkte: 2
Workload:
  • Lecture: 15 weeks, 1,5 hours = 22 hours
  • Preparation: 15 weeks, 3 hours = 45 hours
Prüfungsform:
Beschreibung: Participants will learn the key aspects and principles of business intelligence, data warehousing and data mining know. Specifically, the following points are covered:
  • application fields of Business Intelligence and Data Warehousing
  • BI architectures
  • data sources
  • staging
  • metadata
  • data marts
  • BI front ends
  • ETL processes (Extract, Transform, Load)
  • Development of multi-dimensional data models (Star Schema, Snowflake Schema)
  • Online Analytical Processing (OLAP) and typical operations (roll up, drill down, etc.)concepts
  • methods and applications of data mining (clustering, Naive Bayes, decision trees, classification)
English Title: Analytical Information Systems
English Abstract: The lecuture will introduce the concept of Business Intelligence to the audience. For informed decision-making in companies an integrated view of all decision-relevant information is essential. Business Intelligence (BI) refers to strategies, methods and technologies to gain from heterogeneous distributed data and mission-critical knowledge about the status, potentials and prospects of a company. The associated functions are performed by different tools, seamless interaction is the key feature of a BI landscape. Data warehouse systems and their processes are central concepts for the integration of data and ensuring high data quality. Building on offer BI systems such as Management dashboards or OLAP-based BI services capabilities to analyze operational metrics and processes. Data mining methods also provide insights into previously unknown relationships in business data.
Literatur: Textbook available

Weitere Literatur finden Sie in der HdM-Bibliothek.
Internet: Material available on Moodle

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