One of the greatest strength of data visualization is our ability to process visual information much faster than textual or verbal information. Using good tools for data visualization is the key to the success of using appropriate techniques and technologies. It expands the horizon of our thoughts in new and interesting fields of analytics.
Arbor.js is an appropriate library that efficiently handles graph organization abstractions and refreshes handling, besides managing algorithm layouts that are force directed. Cubism.js and Rickshaw are others helping create horizon graphs that D3 based and involve time series that are interactive. These flexibly and efficiently create complicated and manipulative interactions by supporting SVG rendering.
Polymaps is useful in making dynamic, interactive maps. The purpose of this mapping library is specifically aimed towards the audience of data visualization. Protovis is a library that creates artistically custom views of data by simple marking such as bars and dots.
CartoDB is a web service that converts CSV file of address strings to latitudes and longitudes and plots them on a map. Other uses are analyzing and building applications with data.
Circos is a software package for visualizing data in a circular layout.
Degrafa is a strong ‘declarative graphics framework’ used for rich user interfaces, data visualizations and mapping.
NodeBox, a desktop OS X application that creates 2D graphics and visualisations is a swift and easy option to see result at a glance, except Python code.
Other highly favored tools for data visualization to optimize the goal are Tableau Public, Raphaël, R, Paper.js, Gephi, Processing, Katograph, Flare and many others. Only we have to choose it with a little bit of thought and intelligence.