According to Wikipedia, predictive analytics is described as:
Predictive analytics encompasses a variety of techniques from statistics, modeling, machine learning, and data mining that analyze current and historical facts to make predictions about future, or otherwise unknown, events.
While I’m not a huge fan of relying on Wikipedia for definitions, this is a decent description.
Around the Internet and media, you might see people using Big Data and predictive analytics interchangeably, but in reality they are different. Big Data is the overarching collection of datasets and can cover all of the things that you ‘do’ to that data, but it’s inaccurate to use the terms Big Data and Predictive Analytics interchangeably.
Predictive analytics is an approach to using data, regardless of the size or origin of said data. It covers techniques that have been used for quite a long time and pre-dates the idea of Big Data.
At its core, Predictive analytics is a simple concept: Using techniques to make predictions based on current and previous data. Predictive analytics acts on data in some manner to predict future actions and activities.
Predictive analytics can be used in many different areas. A few examples are:
Marketers use it to determine what market segment is best served with a particular marketing campaign.
Organizations can use predictive analytics to determine which of their customers are more ‘valuable’ than others and then target those customers with special incentives and services to keep them engaged.
Automotive manufactures are using predictive analytics to determine when or if customers should be alerted that the vehicles should be brought into the shop for maintenance.
More examples of the use of predictive analytics can be found by taking a look at this infographic from IBM.
Next time you hear someone try to use Big Data and predictive analytics interchangeably, feel free to correct them. They aren’t the same. Of course, they both hit on the use of data, but Big Data covers much more than just analytics.
This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I’ve been compensated to contribute to this program, but the opinions expressed in this post are my own and don’t necessarily represent IBM’s positions, strategies or opinions.