Types of problem suited to big data analysis. (1)

 


Predictive Problems

Predictive problems are the ones that are used to figure out the reasonable future based on historical data. For instance, a company may want to know who is more likely to buy their product or which machines are more likely to break down in a short time. The use of big data in analyzing the data helps in identifying the patterns of the historical data that can be used to predict the future.

The above mentioned statement is important because it lets the businesses analyze the future in advance and be able to do such things as offering discounts to those customers, who are likely to leave, or identify the machines that might fail this is to say the company can improve its foresight and act in advance. On the other hand, the data that is too big for the human brain to process can be used and thus, many process mistakes will be avoided and a lot of patterns and trends will be noticed that lead to improvements.

These problems are general in several areas such as: exposure of stock prices in finance, indicating disease outbreaks in healthcare, and getting prepared for the seasonal demand in retail. If what is foreseen genuinely comes to pass, companies can benefit from such achievements as cost-effectiveness, client satisfaction, and lower exposure to risks.

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