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| Content Provider | ACM Digital Library |
|---|---|
| Author | Golfarelli, Matteo Rizzi, Stefano Mantovani, Marco Ravaldi, Federico |
| Abstract | Location intelligence is a set of tools and techniques to integrate spatial features into BI platforms, aimed at better monitoring and interpreting business events related to the territory. In this demonstration we present Lily, a geo-enhanced library that relies on a spatial data warehouse to add real location intelligence capabilities to existing BI platforms. Lily provides end-users with a highly-interactive interface that seamlessly achieves a bidirectional integration between the BI and the geospatial worlds, so as to enable advanced analytical, prediction, and simulation features taking into account the spatial dimension. In particular we focus on the impact of Lily on the user experience with reference to three case studies in the domain of healthcare, telco, and school services respectively. |
| Starting Page | 33 |
| Ending Page | 36 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781450309998 |
| DOI | 10.1145/2666158.2666176 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2014-11-07 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Gis Spatial data warehouse Business intelligence |
| Content Type | Text |
| Resource Type | Article |
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