Value of spatial analytics

An Oracle White Paper April 2010

Value of Spatial Analytics in Business Intelligence

Oracle White Paper—Value of Spatial Analytics in Business Intelligence

Disclaimer
The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, orfunctionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle‟s products remains at the sole discretion of Oracle.

Oracle White Paper—Value of Spatial Analytics in Business Intelligence

Introduction ....................................................................................... 2Information Visualization ................................................................... 2 Geospatial Analytics .......................................................................... 8 Spatial Business Intelligence ............................................................. 8 Location and Context....................................................................... 12 Enhancing LocationBased Analytics ............................................... 15 Challenges ...................................................................................... 16 Conclusion ...................................................................................... 16

Oracle White Paper—Value of Spatial Analytics in Business Intelligence

Introduction
The ability to display data using anappropriate visualization is essential to providing insights to business intelligence users. For data with a geographical dimension, geo-spatial views can often be most appropriate. Wider adoption of geo-spatial analytic visualizations in companies has hampered because of the challenge of acquiring mapping and geospatial data, of integrating mapping applications into existing BI products, and ofmanaging these deployments. In this paper, we show how different types of data visualizations can be useful for analyzing data, and how data with a spatial dimension can be visualized and analyzed more effectively. Furthermore, we will also provide examples how spatial visualizations themselves can be enhanced to provide further insights.

Information Visualization
There is an explosion ofinformation that is captured by enterprise systems. This information makes its way into data marts, data warehouses, though often also staying as-is in transactional systems. From these data marts and data warehouses information is then analyzed. The purpose of this analysis is to provide the user(s) with insights in to the data, and therefore, into the business itself. By understanding trends andpatterns in the data, business analysts can make more effective decisions about planning and operations. Apart from the myriad challenges that are faced by business analysts when analyzing data, one of the biggest is deciding how best to visualize the data. Too high level a view and it becomes more or less meaningless; too detailed a view and any insights are buried under massive amounts of data.Visualizations, in order to provide insights, need to be effective, interactive, and bite-sized. Examples of commonly used visualizations used are: Tables Pivots or crosstabs Charts (pie, bar, line, …) Maps Trellis views Text based views Scorecards Gauges Funnel charts Hierarchical views Tag Clouds Treemaps Dashboards Sparklines Heatmaps

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Oracle White Paper—Value of Spatial Analytics inBusiness Intelligence

Visualizations need not be esoteric to be effective. The simple table and chart views can be just as effective in visualizing data. Let us start with an example. The table below displays one dimension – “District” – and one measure – “Dollars”. This can be visualized by means of a table. The benefits of such visualization are obvious – all the data is laid out, precisely, for...