Machine Learning Vs Predictive Analytics: What’s The Difference

As Artificial Intelligence becomes more involved in business operations, the terms “machine learning” and “predictive analytics” are often confused to be the same thing. Though the two are basically under the same umbrella, they are completely different concepts. We decided to break down each concept and explain what they do and why they tend to get mixed up in conversation.

Machine Learning

Machine learning is an artificial intelligence technique where algorithms are used to process massive amounts of data without predetermined rules. Machine learning is growing in popularity for businesses because it allows for them to process massive amounts of data in real time. What makes them so powerful is that ML algorithms learn from their mistakes on past datasets to process future data more efficiently. An example would be feeding a company’s e-mail data to a machine learning algorithm, that would then use specific patterns to determine the difference between spam and important e-mails.

Predictive Analytics

Predictive Analytics is an area of study that has been around long before artificial intelligence. Predictive Analytics is the process of analyzing historical data and current data to find patterns. Businesses use these patterns to make informed predictions of the future and make better business decisions. Businesses that use predictive analytics usually have an upper hand on those who don’t. Predicative analytics allow businesses to as an example, make smarter marketing decisions by implementing specific marketing efforts based on past consumer data. If a company sees that a specific type of customer is more likely to make a purchase after receiving a 10% off coupon, businesses will target those customers.

Where They Collide

Because the two operations piggyback on each other, people tend to assume they’re the same thing when they’re really two separate operations; where predictive analytics can be a subset of the data garnered from Machine Learning. This relationship has made predictive analytics one of the more favorable applications for businesses trying to gain insight on their customers’ buying habits. Whereas, the organization’s that implement Machine Learning allows the businesses to process their data faster and more efficiently. After machine learning has processed the data, businesses are able to take this data, implement a predictive analytics strategy, and are then able to make educated predictions to support their business efforts moving forward. Looking to implement a machine learning solution to help process your organization’s data sets? Contact us at Pumex Computing and we can start the discuss what the best solution would be for your specific needs.