Without question, the plethora of Big Data is more prevalent now than ever before. More data has been created in the past two years than in the entire history of the human race, Forbes reports. By 2020, 1.7 megabytes of new information will be collected every second for each individual on the planet.
Data scientists have labeled this new era of data with “four Vs,” where thevolume of data, variety of data sets, velocity of data analysis and veracity or uncertainty of data quality are paving the way for new trends in predictive analytics.
Today, companies are hungrier than ever to utilize data to gain greater insight into their business performance, with a strong emphasis on the variety of data used. From traffic and weather patterns to changes in consumer sentiment and volatility in Asian markets, companies are dealing with more complex problems and are turning to external Big Data to for the answers.
No longer is data isolated in the IT department, and executives are looking to Big Data to provide big answers. They want to discern which external factors will impact the sales and demand of a particular product in the next six months – and by how much. They want to accurately determine which markets their company should exit and which markets are poised for growth. The demand for such answers – in real time, no less – is bringing about three distinct trends in today’s predictive analytics process.