Syllabus

Titel
1019 Spatial Business Intelligence Project
LV-Leiter/innen
Ass.Prof. Mag.Dr. Petra Staufer-Steinnocher, Mag. Georg Magenschab, Mag. Gerhard Trichtl
Kontakt
  • LV-Typ
    PI
  • Semesterstunden
    1
  • Unterrichtssprache
    Englisch
Anmeldung
02.09.2019 bis 01.10.2019
Anmeldung über LPIS
Hinweise zur LV
Die Lehrveranstaltung wird nur im WS angeboten.
Planpunkt(e) Master
Termine
Wochentag Datum Uhrzeit Raum
Freitag 04.10.2019 09:00 - 12:30 D4.0.047
Freitag 18.10.2019 09:00 - 12:30 D4.0.047
Freitag 25.10.2019 09:00 - 12:30 D2.0.330
Freitag 08.11.2019 09:00 - 12:30 D2.0.330
Freitag 22.11.2019 09:00 - 12:30 D2.0.334 Teacher Training Lab
Freitag 29.11.2019 09:00 - 12:30 D4.3.106

Inhalte der LV

The IT Competence Field Spatial Business Intelligence (SBI) is a novel area that has emerged at the interface between GISystems (GIS) and Business Intelligence (BI) technologies. SBI allows integrating different systems and technologies, saving valuable resources, visualizing organization’s assets, streamlining work flow processes, minimizing risk and enhancing business decision-making. Only recently it has been realized that integrating the geospatial component of business operations through GIS technology provides business intelligence solutions that lead to better business decisions.

In this course, the major issues are the application of methodological and technical skillsI to real-world SBI-application problems, and the critical discussion of results which are presented in the SBI literature. Students will work in teams on different real-world or methodological/technical problems, will develop solutions and present them to the study group

Main topics covered in case study projects are:

  • spatial data integration: from enterprise databases and data warehouses to spatial data warehouses
  • spatially enabling enterprise data, integrating external geospatial market data, spatial data maintenance
  • mapping database contents: ArcGIS Server/Geoserver (APIs, REST interfaces, RIA toolkits, WMS and WFS)
  • thematic mapping and spatial analysis, BigData visualization techniques
Software used: ESRI ArcGIS Desktop and ArcGIS Server, MSQL Server 2008R2 (commercial); ProstgesSQL with PostGIS, GeoServer (open source)
Geodata used: geocoded customer and business data, postcode and administrative geographies with geodemographic attributes, consumer- and lifestyle-data, navigable street networks and background maps

Lernergebnisse (Learning Outcomes)

After successful completion of the class, students should be able to

  • analyse and solve real SBI and location analytics problems in selected industries and businesses
  • develop and present solutions in a team
  • critically evaluate and discuss published results from the SBI literature


Regelung zur Anwesenheit

Attendance in class is mandatory

Lehr-/Lerndesign

  • autonomous project-based team work
  • project management and documentation
  • presentations
  • discussions

Leistung(en) für eine Beurteilung

active class participation (10%)
case study projects development and documentation (70%)
case study project presentations (20%)

Teilnahmevoraussetzung(en) und Vergabe von Wartelistenplätzen

  • Basic understanding of programming languages: HTML, Javascript, SQL, PHP (or the like)
  • foundations of location analytics: geospatial data modeling and analysis, OGC standards, ArcGIS Desktop software (taught in SBI-1 course)
  • basic software and tools skills: ArcGIS Server, MSQL Server 2008R2 (commercial); ProstgesSQL with PostGIS, GeoServer (open source) (taught in SBI-2 course)

Detailinformationen zu einzelnen Lehrveranstaltungseinheiten

Einheit Datum Inhalte
1 Unit details are available for course members only (see below)
Zuletzt bearbeitet: 02.05.2019



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