It is said that a picture is worth a thousand words.
Pictorial representation of data makes it more understandable and more relatable. And most often than not, the interest is in summarized information. And in today's world where we deal with terabytes and petabytes of data, its all about conveying a lot of information in the fastest and most understandable form of way.
So what is Geospatial Analytics all about? To put it plain and simple, it refers to analysis of data from a geographical or spatial point of view, or presenting data on a map, or even using the location coordinates for various kinds of analyses. It could be as simple as a representation of points of interests on a map like hospitals, or heat maps showing areas against a population scale.
The traditional way of viewing information in reports in OBIEE have been tabular views, pivot, charts/graphs, etc. But now, with the availability of Map view in OBIEE, we can leverage mapping engines like Google Maps to deliver spatial information along with the application data.
Below picture shows a map view (heat map) done in OBIEE. The heat map is one of the many ways of representing data on a map by utilizing geospatial information.
Let's get to know some of the basic concepts in spatial analytics (with relevance to configuration and usage in OBIEE) before we deep-dive into the actual configuration/visualization.
SRID
An SRID (Spatial Reference ID) is a unique identifier (number) for projection systems used to represent/store geospatial data. These standards are used for cartography, surveying, geodetic data storage, navigation, etc.. There are multiple sources of SRIDs created by various geospatial vendors/organizations (e.g. EPSG - European Petroleum Survey Group). In a spatial database, the SRID gives information about the projection system used to derive the geometry/spatial column.
If the base map to be used in OBIEE is Google Maps, the SRIDs should follow the WGS84 standard, which uses Latitudes and Longitudes. The WGS84 standard is also used and some of them are 8307, 4326, 3785 (used by Google Maps and Bing Maps), 3857 (latest version used by Google).
In our blogs, we will be using either 8307 or 4326.
Shapefiles
The most important building block for Geospatial Analytics in OBIEE is the shapefile.
The shapefile is a popular spatial data format used to represent geographical information. They define spatial information in vector graphics, meaning, as lines, points or polygons. These can be used to represent any sort of geographical or spatial feature. Although the shapefiles themselves are open source, the standards for shapefiles are regulated by ESRI (formerly Environmental Standards Research Institute). The shapefiles come in the .SHP format, but usually when we refer to shapefiles, they come with a bunch of supporting files as well. The most important of these supporting files are:
.shx file — shape index format; its like a positional index file for the geometry defined in the .shp file
.dbf file — attribute format; columnar attributes for each shape, in DBase IV format
.prj file — this file which gives information about the projection/coordinate system used to define the geometry in the shapefile
Shapefiles are created using GIS tools like ArcGIS, QGIS etc. You could download shapefiles for geographical administrative areas (countries, regions, etc.) from http://gadm.org/. You could check the SRID used in a .shp file by checking your .prj file at this location - http://prj2epsg.org/search.
The area of Geospatial Sciences is a vast ocean, but the focus of this blog (and the succeeding ones) would be specifically to cover the idea of presenting geospatial information in OBIEE.
In my next blog, I will be covering how to use shapefiles for spatial analysis in OBIEE and how the shapefile information can be interpreted and configured.
Until then, happy learning!
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