Five Critical Predictive Analytics Mistakes (and How to Avoid Them)
The business world is increasingly in love with all things AI. Included in this is the increasing demand for predictive analytics among enterprise companies. In fact, according to research firm Markets & Markets, demand for predictive analytics is expected to grow to an impressive US$28B by the year 2026. Forecasts are often educated guesses, but if demand for data scientists (the specialists needed for most predictive analytics projects) is any indication, the estimates might just be on target. In fact, in 2021, the demand for data scientists, as measured by job openings, grew by over 250% over 2020. Yet, with all the need for machine learning and predictive analytics, the reality is that over 87% of machine learning projects still fail. The past five years have seen a flurry of activity in the world of machine learning and predictive analytics with new tools that promise to make predictive analytics simple…