Predictive analytics has become an increasingly important tool for businesses as they look to make better use of all the data they’re gathering. Machine learning can provide even more punch to analytics, giving enterprises an even more powerful data resource.
Data analysts are increasingly using machine learning techniques for predictive analytics because they “tend to outperform statistical techniques for prediction problems,” said Thomas Dinsmore, an independent consultant and author of Disruptive Analytics.
“When organizations deploy machine learning broadly, they improve the efficiency and effectiveness of business processes,” Dinsmore said. “Business gains depend on how and where the organization deploys predictions.”
For example, better predictions deployed in an insurance claims process can reduce the rate of fraudulent claims and improve customer satisfaction. In a marketing process, better predictions improve ad targeting, audience selection, and offer optimization. And, in retail store operations, better predictions of in-store foot traffic help the retailer optimize staffing.
“The list of potential applications for predictions in business operations is broad and deep,” Dinsmore said.
Machine learning makes it possible to do things that would be impossible otherwise, Dinsmore said. For instance, machine learning makes it possible to estimate storm damage from images of properties or regions, diagnose cancer, or detect the unique “signature” of a computer user.
Machine learning techniques generally produce more accurate predictions, especially when the behavior you’re looking to predict is rare, Dinsmore said. They “tend to work better with dirty data and ‘wide’ data sets — sets with a very large number of features — and with unlabeled data,” he said.
Machine learning algorithms tend to scale well to large volumes of data, and they are more easily incorporated into large-scale applications.
This year, Dinsmore expects to see more machine learning vendors claiming to offer some degree of automation. “There is a crowded market for ‘desktop’ predictive analytics accessible to the business user; some existing startups will likely be acquired,” he said. “New startups will likely focus on targeted business solutions” in marketing, financial service, healthcare, and security.
Read the source article at ZDNet.