Types of problem suited to big data analysis 1

 


Pattern Recognition Problems

Pattern recognition is the utilization of large data in its most common form. It basically is the identification of similar behaviors or trends in a large amount of data. The tools designed to work with big data can skim through millions of records to identify human repetitious activities.

Online shopping is a perfect example of this. E-commerce giants like Amazon utilize big data to monitor users' browsing history, adding items to the cart, and completed purchases. So, if lots of people buying a phone also buy a charger, the system learns this pattern. After that, it suggests chargers to other phone buyers. This is called a “recommendation system.”

Besides, pattern recognition can also be applied in such areas like video streaming platforms. Netflix and YouTube get the information about what kind of videos people watch most and what they usually watch next. Based on that, they can propose you some new videos. All of this is done since big data identifies the patterns of user behavior.

Such an analysis is a great help for companies to make good decisions, offer the best services, and also raise customer satisfaction. Without big data, it would be impossible because the process would be extremely slow and hard to catch the pattern.

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