Predictive analytics requires varied skills
TechTarget recently spoke to insurance-industry analytics expert Jennifer Golec. She said success in predictive analytics requires a unique employee skill set, with programming, data analysis and storytelling skills combining to make large quantities of unstructured data into a viable source of predictive insight.
"You have to be able to interpret those results," Golec told the source. "[That means] really being able to interpret the insight that you pull from the data. You have to be able to relay that because if you don't, you'll be sitting on this great model and you won't be able to implement it."
She stated that the programming skill is important to conduct exploratory analysis on huge data sets, the statistical analysis skill can help build multi-variable models and a flair for storytelling can make the data into a coherent business case. She emphasized the last point, stating that predictive projects need to take information from a dry and data-based state to something employees can understand.
A recent Wireless Week report stated that predictive analytics is a hot field, with predicting in context becoming especially widespread. Such systems automatically project future moves based on real-time data and, according to the source, can help in fields such as retail predict how much a customer is willing to spend.