Using Every Pixel to Visualize Big Data

Design Ballroom CD
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Visualizing patterns, relationships and anomalies in multi-sourced data is challenging when the number of records continues to grow exponentially. Many traditional methods of visualization for business intelligence and reporting aggregate the results into units which are easily computed and displayed. However, these visuals often fail to reveal the true patterns of the underlying data. If we used more pixels in our visualizations we could see millions of data representations on a screen.

Computing a value for each pixel is a difficult challenge because it often requires whole set aggregates and table scans. There are so many pixels that it quickly becomes efficient to render these visuals on the server.

In this session we will cover some of our favorite examples of big data visualizations and show you how rendering every pixel can be an effective tool for analysis. We will also discuss the tools and architectural considerations necessary to create these visualizations for your organization.

Photo of Lynwood Bishop

Lynwood Bishop

Map Large, Inc.

Lynwood Bishop is President of Map Large, Inc.

Dynamic Visualization of Big Data: The MapLarge API can render millions of interactive points and shapes with no pre-caching or client side processing.

MapLarge maintains a cutting edge data visualization API for dynamic maps, charts and interactive query interfaces with machine assisted pattern recognition and data mining analytics. Our distributed platform has utilized thousands of servers to process large jobs. We can provide both existing product and R&D services.

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