Common Mistakes That Can Derail Your Team’s Predictive Analytics Efforts
With high demand for data scientists and the high salaries that they draw, it’s often not practical for organizations to keep them on staff. Instead, various organizations work to ramp up their prevailing staff’s analytics skills, comprising predictive analytics. But companies need to advance with caution. Predictive analytics is particularly easy to get wrong. Here are the first few “don’ts” your team needs to learn, and their parallel cures. 1. Don’t Fall for Buzzwords — Explain Your Objective Data Science doesn’t essentially refer to any specific technology, method, or value proposition. Rather, it indicates a culture — one of smart people doing creative things to discover value in their data. It’s essential for everyone to keep this on the top of the mind when learning to work with data. Under the broad umbrella of data science sits predictive analytics, which provides the most actionable win you can draw from data. In a nutshell, predictive analytics is technology t