“Human brains have an extreme form of consciousness: they’re ravenous for new innovative solutions to problems in the world, ravenous for optimizing our lives, for building pyramids of knowledge.” – Daniel Bor, neuroscientist and author of “The Ravenous Brain“
Imagine all of the customers that visit your website and never purchase a product. Using traditional data analysis, you might evaluate your website analytics to determine how long customers stayed on each page, which pages had the highest exit rate, the source of the traffic, and more.
When you add big data to this scenario, you can look at your customer’s social media trends, organic search traffic, and the list goes on. But when you start looking at these various types of data, it can become too much for one person to review by hand and gain insight.
Dale Lehman with bizTime says, “while big data analysis reveals patterns, associations and predictive influences that were not anticipated, I am interested in the emotional appeal of finding answers to questions you did not know to ask. Why are people so motivated by seeking answers to questions they did not know to ask rather than answers to the questions they did know to ask?”.
This search for the unknown is part of what drives the move from traditional to big data analytics. As data is collected and analyzed more than ever before, it’s often collected before without an end goal in mind.
In many cases during the search for unknown associations in data, it makes sense to thoroughly examine traditional data before moving to big data. Otherwise, data with a high likelihood of providing insight may be overlooked.
As Daniel Bor said, the need persists to find new and innovative solutions to problems. To do so with analytics, ensure you evaluate traditional analytics first before jumping straight into the depths of big data.