The term big data is defined as “data that is so large, fast or complex that it’s difficult or impossible to process using traditional methods. The act of accessing and storing large amounts of information for analytics has been around a long time.” Companies that practice using good analysis are one step ahead of their competitors. Having a way to analyze the data and maximizing the data is essential to smart decision making, cost reduction, and optimizing offers. The key is to use the data to make is to gain the right information to gain that competitive edge.

We’ll be discussing three dominant types of analytics. Descriptive, predictive, and prescriptive.

Descriptive analytics is exactly as it sounds. It provides information and summarizes data onto things such as dashboards, alerts, and scorecards. It analyzes past events but does not explain why it occurred. It breaks down information down so that it is interpretable.

Predictive analytics used past data to determine future outcomes. It provides companies with actionable insights based on data. This is exactly what you want your data to provide. You want it to give you insights and be actionable. Examples of how to use predictive analytics are determining how a customer will respond to a sale or using predictive analytics on how to personalize a patient’s care, and it can be even used in sports to determine the future value of a player. Predictive analytics is very useful when used correctly and can provide great insight.

Lastly, we have prescriptive analytics. This type of analytics uses technology to help make businesses make smarter decisions. Examples of this are running an A/B test on an email campaign to see which one will perform better, or even adjusting ticket pricing for airlines and bus routes based on numerous factors such as weather conditions, customer demand, etc.

Regardless of how you look at it, big data is useful, and the term “big” can be considered as to how many advantages big data provides its users. Below are some useful links regarding big data.