Predictive analytics is a rather interesting and intriguing category of data analytics. The aim, as the name apprises, is to make a prediction of future events on the basis of past data using various analytic techniques. These techniques include quite sophisticated tools and models. And using them, companies can make reliable forecasts even years into the future.


How does it work?

Predictive analytics utilizes a big range of data analytics tools like data mining, big data, statistical modeling, machine learning, and so on. Organizations use such methods to move through current and past data and detect trends and then use them to forecast events. Using predictive analytics, organizations can find patterns in the data, and exploit it to find future opportunities and eliminate risks.

Statistical models can help discover relationships between various factors, subject to some conditions. These relationships can be used to make the decision-making process much more informed.


What are the benefits?

Predictive analytics essentially allows us to have a very constrained look into the future. And this will help those who adopt predictive analytics save and earn a lot of money.

For instance, retailers can use predictive analytics to forecast future inventory requirements, decide their shipping schedules and even have an idea about their store layouts.

The airline industry can use past trends to predict demand and set prices for different routes accordingly. Restaurants, hotels, and other hospitality agencies can use predictive analytics to maximize their occupancy, and hence, their revenue.

The financial sector is perhaps where predictive analytics is utilized the most. Investors and corporations can use these tools to develop complex credit risk models. They can forecast financial market trends over a long period of time. The newer, more complex predictive analytics tools can even predict the impact of new laws and policies on markets.