Expanding Data Visualization
The ability to visualize large data sets has become more critical than ever. The term "Big Data" has organizations compiling larger and larger sets of data every day. Unfortunately, the data needs to be brought into use to extract the value within. This typically comes in the form of data visualization. To display this data we need to move past the old line, bar, and pie charts. We must expand our abilities to represent multiple axis and variables in a single plane. This creates the need of new data types, binning structures, and simplification.
The web has given individuals the ideas and tools to visualize their data as they see fit. No longer are the restrictions in place to limit our abilities. Organizations such as D3 (Data-Driven Documents) have provided toolboxes open to everyone. Access to these tools, examples, and ideas on how to visualize data opens new paths for everyone to create, trial, and discover how to make big data work for us.
Now, as organizations create more and more big data sets, they need to look into teams of individuals simply on how to visualize the information within it. Leaving this visualization to the creators of data sets most likely is not the answer. It is similar to letting your engineering R&D team lead the marketing effort. Different mindsets are required to push the usage beyond the simple query, data table and known data usages. Big data needs to provide big solutions or it is just that, Big.
Examples of Data Visualization: https://github.com/mbostock/d3/wiki/Gallery
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