Predictive Analytics
Glossary of terms

What Is Predictive Analytics?

Predictive analytics is the practice of using algorithms and machine learning to anticipate future outcomes based on data. A form of predictive modeling, predictive analytics is the branch of big data analytics that is specifically concerned with revealing insights on what will happen in the future based on what has already occurred in the past. More accurately, it is concerned with what is likely to happen, since predictive analytics is not akin to having a crystal ball.

Predictive analytics has widespread applications across industries, from retail to healthcare and other sectors. In healthcare, for example, predictive analytics is increasingly used to anticipate patient outcomes and health risks. Regardless of industry, predictive analytics is one of the wide-ranging use cases for data science and machine learning in businesses and other organizations.

Why Predictive Analytics?

Predictive analytics can deliver crucial, data-driven insights into what is likely to happen in the future. This can lead to all manner of smarter decisions, such as anticipating (and taking steps to prevent) customer churn, improving health outcomes, and proactively mitigating information security threats. Predictive analytics is an essential segment of big data analysis. It enables individuals and organizations to better understand not only what has happened in the past, but what is likely to occur in the future.

Glossary of terms

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