“A picture is worth a thousand words.” This old, English idiom could not ring more true than in today’s fast-paced, digital age – the big data age. At a time when we are creating 2.5 quintillion bytes (or 2.5 million terabytes) of data each day, executives and decision-makers across the globe are looking for ways to turn complex and voluminous data into comprehendible and comprehensive, actionable insights. Enter, data visualization.
What is Data Visualization?
The visualization of data for purposes of analysis is not a new concept. Finding their roots in Descartes’ Cartesian coordinate system, several graphical diagrams such as the line, area and bar chart were invented in the late 18th century by Scottish engineer and political economist, William Playfair. He was also the inventor of the once widely-popular, yet more recently denounced, pie chart.
Data Visualization sits atop the Big Data Analytics pyramid (Figure 1) and is often the only layer that is visible to executives and other decision-makers. Thus, the success or failure of a Big Data analytics program often depends on the success of the visualization layer. A company may have the most advanced data capture, storage, and transformation technology (and use the most complex algorithms and statistical models to analyze that data), but if the information isn’t displayed clearly, accurately and efficiently, the whole point of leveraging Big Data is lost.