Predictive analytics has opened up new possibilities for predicting future events by studying past performance. Predictive analytics is the use of data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data. The goal is to go beyond knowing what has happened to providing a best assessment of what will happen in the future.

Big data enables data scientists to review massive amounts of data, so one could hope that the degree of accuracy in future predictions will only rise. DATAVERSITY brought this news to us in their article, “Limitations of Predictive Analytics: Lessons for Data Scientists.”

Actual field tests might disagree, though. Because the element of surprise is so high in predictive analytics, even the best of algorithms, computational models, and analytics tools can lead to complete failure in some cases. Despite this, more and more organizations are turning to predictive analytics to increase their bottom line and competitive advantage.

Melody K. Smith

Sponsored by Data Harmony, a unit of Access Innovations, the world leader in indexing and making content findable.