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Ryan Goodman CEO Centigon Solutions @rmgoodm Ryan Goodman is Centigon Solutions CEO, author, and expert in Business Intelligence. Ryan applies over 12 years designing business applications to his leadership role shaping Centigon Solutions’ Location Intelligence platform strategy. Today, Ryan is focused on pushing wider adoption of Business Intelligence through visualization and Location based services.

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Topological Data Analysis

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Many data sources do not always fit nicely into a linear regression during statistical analysis so when the shapes vary, you may want to understanding the shape and relationship between data elements.

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Topological Data Analysis is a perfect aid to conceptualize relationships and visual trends that could otherwise be hidden.

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http://www.ayasdi.com/blog/bigdata/why-topological-data-analysis-works/ This example illustrates retail data for different locations along with retention rates.

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Using geography as a common dimension to understand spatial relationships from a bird's eye view is a very popular visualization type.

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Using geographic attributes or coordinates also provides additional context like distance and proximity to analyze data.

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http://pureinformation.net/projects/building-age-nyc/ This example illustrates over one million buildings and the age of those buildings

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Tree Map

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A Tree Map is a great way to visualize a multidimensional data set in a compressed two dimensional space.

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A Tree Map has its own algorithm for organizing and placing square boxes which are nested based on a hierarchical tree.

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http://deletedcity.net/ The size of the boxes represents the hierarchy of pages created inside of geocities

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3D Spatial

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Three-dimensional visualizations can unlock time and space dimensions to simulate real world objects and scenarios.

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While 3D requires more computer power and lots of data, the results can be profound. This example demonstrates a computer simulated crash and the resulting damage to vehicle components...

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http://tctmagazine.com With millions of individual components, 3D visualization and predictive analysis can relay critical information not visible in the real world.

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Density / Heat Map

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Density, also referred to as heat maps display color intensity as the number of points increase and overlap within a given space.

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Density maps are popular for spatial data visualization (both 3D and geographic). Heatmaps can be particularly useful for big data visualizations. The following example illustrates foot traffic through interaction with beacon sensors.

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Indoors This particular solution is provided by Indoors where public and privately owned venues can become data rich spaces. The opportunities to understand real-time traffic patterns of people through space provide tremendous insight to consumer engagement.

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For more great content go to… BIBrainz.com/aof Edited by Matthew Broderick Managing Editor of Analytics on Fire @MattdBroderick