Syllabus
Registration via LPIS
Day | Date | Time | Room |
---|---|---|---|
Friday | 10/04/19 | 09:00 AM - 12:30 PM | D4.0.047 |
Friday | 10/18/19 | 09:00 AM - 12:30 PM | D4.0.047 |
Friday | 10/25/19 | 09:00 AM - 12:30 PM | D2.0.330 |
Friday | 11/08/19 | 09:00 AM - 12:30 PM | D2.0.330 |
Friday | 11/22/19 | 09:00 AM - 12:30 PM | D2.0.334 Teacher Training Lab |
Friday | 11/29/19 | 09:00 AM - 12:30 PM | D4.3.106 |
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
Geodata used: geocoded customer and business data, postcode and administrative geographies with geodemographic attributes, consumer- and lifestyle-data, navigable street networks and background maps
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
- autonomous project-based team work
- project management and documentation
- presentations
- discussions
case study projects development and documentation (70%)
case study project presentations (20%)
- 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)
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