Types of problem suited to big data analysis 2

 


Prediction Problems

Prediction problems are where big data is used to make the best guess about the future. This is accomplished by analyzing past data in order to identify trends or recurring patterns. If we know how something behaved, we can often be able to predict how it will act next.

The first example that comes to mind is weather forecasting. Weather stations collect huge amounts of data every day, recording temperature, wind, humidity, pressure, and many other parameters. Big data systems look into years of such data to guess if it will be rainy tomorrow or if there is going to be a hot spell. Moreover, these forecasts become the basis for a person’s daily routine and safety.

Also, businesses make use of big data to decide on the number of products that they could probably sell next month. This allows them to plan production, storage, and transportation accordingly. Supermarkets might use big data to guess how many people will buy cold drinks during a hot week. This helps them avoid running out of stock.

Predictive analysis provides solutions to a problem with time, money, and effort. The presence of big data makes the predictions more accurate and hence more useful, mainly when the environment is rapid in changing.

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