Types of problem suited to big data analysis 3



Anomaly Detection Problems

Anomaly detection is the process of recognizing an item which follows an unexpected pattern. This problem is significantly important because it allows the detection of errors, dangers, or even illegal acts in large arrays of data. Big data tools can quickly scan through thousands or millions of records to find anything that looks unusual.

For instance, banking is a sector where big data can be utilized to detect fraud. If a card is utilized in a different country without your knowledge while you are still at home, the system considers it to be “anomalous” behavior. It informs the bank of the situation and hence, your card may be blocked to stop the misuse. The reason for such a quick response is that big data automatically adapts to your changes in behavior.

Big data are monitoring tool of machines in factories. They pick up information such as a vibration, a temperature, and a speed. If a change occurs suddenly, the system gives the staff a warning before the machine stops working. Thus money is saved, and accidents avoided.

Definitely, anomaly detection is the initial point in ways of medical care, cybersecurity, and traffic systems. The method is the most efficient in breaking out the problems before their repercussions would be going further—possibly even before the human senses coming across the problems.

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