We know data is very important and huge companies are hiring data analyst. But have you ever thought about the reason behind that? The practise of mining data for hidden relationships and forecasting future trends has a long history. The term "data mining," also known as "knowledge discovery in databases," was not coined until the 1990s. However, it is built on the foundations of three linked scientific disciplines: statistics (the numerical analysis of data correlations), artificial intelligence (human-like intelligence demonstrated by software and/or machines), and machine learning (algorithms that can learn from data to make predictions). As data mining technology evolves to keep up with the endless potential of big data and affordable computer power, what was old becomes new again. Advances in processing power and speed have enabled us to shift away from manual, arduous, and time-consuming data analysis and toward quick, easy, and automated data analysis during the previous decade. The more complex the data sets collected, the more likely it is that meaningful insights will be discovered. Data mining is being used by retailers, banks, manufacturers, telecommunications providers, and insurers to discover relationships between everything from price optimization, promotions, and demographics to how the economy, risk, competition, and social media are affecting their business models, revenues, operations, and customer relationships.

Gokul Pradeep

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