Abstract
Location intelligence is a set of tools and techniques to integrate a geographical dimension into BI platforms, aimed at enhancing their capability of better monitoring and interpreting business events. Though most commercial data warehouse tools have implemented spatial extensions to support GIS integration, the user experience with spatial data is still mostly limited to the visualization of maps labeled with numerical indicators. To overcome this limit we developed Lily, a geo-enhanced library that adds true 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 features that truly take into account the spatial dimension. In this paper we describe Lily from a functional and architectural point of view, and show an example where Lily is coupled with the Oracle Suite to be used for location intelligence in the field of telecommunications.
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Golfarelli, M., Mantovani, M., Ravaldi, F., Rizzi, S. (2013). Lily: A Geo-Enhanced Library for Location Intelligence. In: Bellatreche, L., Mohania, M.K. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2013. Lecture Notes in Computer Science, vol 8057. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40131-2_7
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DOI: https://doi.org/10.1007/978-3-642-40131-2_7
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