Big data is a term that’s used to describe the collection and storage of vast amounts of information — typically beyond what traditional database systems and spreadsheet tools can handle. It can be gathered from many sources – including publicly shared comments on social media sites, data from sensors on products, volunteered data through online questionnaires and app usage, as well as transactional data logged by digital systems.
The challenge has moved from collecting as much data as possible to efficiently managing it in order to make useful discoveries and inform business decisions. Data is only valuable if it can be accessed and understood, so it’s important to have a system in place that can organize the information, catalog it so other systems can find it, and provide an agile framework for accessing and managing changes to the data over time.
One of the ways that organizations make sense of their big data is through visualization techniques. The human brain is hard-wired to take in visual information, and it excels at recognizing patterns. Big data visualization allows enterprises to present large sets of raw data in graphical forms that can be processed by this hardwired human ability, often revealing hidden relationships that would have been obscured otherwise. Some of the most popular visualizations are linear, such as tables and lists, while others are 2D or geospatial – such as cartograms, dot distribution maps, proportional symbol maps, and contour maps.