Big data implementation and visualization

Abstract

Government agencies and large corporations are launching research programs to address big data's challenges. Visualization in today's time is very effective for presenting essential information in vast amounts of data. Big-data discovery tools present new research opportunities to the graphics and visualization community. The size of the collected data about the Web and mobile device users is even greater. To provide the ability to make sense and maximize utilization of such vast amounts of data for knowledge discovery and decision making is crucial to scientific advancement; we need new tools beyond conventional data mining and statistical analysis. Visualization is a tool which is shown to be effective for gleaning insight in big data. Here we also discuss data cube that fits in a tablet or a smart phone memory, actually for billions of entrances; we call this information structure a nanocube. [13]. We present pseudo code to compute and query a nanocube [13], and show how it can be used to generate well-known visual encodings such as heat maps, histograms, and parallel coordinate plots. While Apache* Hadoop* and other technologies are emerging to support back-end concerns such as storage and processing, visualization-based data discovery tools focus on the front end of big data-on helping businesses explore the data more easily and understand it more fully.