Predictive analytics is an understandably popular concept for small, midsize and enterprise-level businesses — every company wants to see things coming. These solutions rely on the constant influx of big data to provide insights both relevant and actionable. But as the technology evolves, an important question emerges: Does bigger data really mean better answers?
There is a natural assumption that along with big data comes bigger data sets for modeling and that these larger sets return better results. As a recent Search CIO article discusses, however, other factors such as clean data, unbiased sampling and creative thinking are actually more important. For example, a 2013 Data Miner Survey found that the size of data sets was increasing, but when asked, companies said the number of records used in a typical data set for analysis was the same as in 2007.