**What Is Data Mining?**

Data mining is a critical part of data science. This is the starting point for data science and data analytics. It is a technique for collecting data from various sources, and there are millions of sources where data can be collected. Data mining is the process of extracting hidden predictive information from an extensive database.

The firm uses data mining to convert raw data into useful information. Most organizations use different software to look at patterns in large batches of data. Using the software, a businessman can learn more about their client's behaviour towards your business.

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**What Are The Goals Of Data Mining?**

There are various gaols in data mining, and some of them are the following which are shown below:

**Prediction**

Data mining fields focus on forecasting compared to generating accurate results for future purposes. This determines how specific attributes within the data will work in the future. For example, in predictive models, the marketing manager predicts how much a particular customer will spend during a sale.

**Identification**

Identification allows us to identify the data pattern in the current item. Natural language processing techniques are used to identify key entities in individual articles. For example, newlyweds spend more money on buying furniture.

**Classification**

Data mining can divide data into classes. For example, a supermarket. In a supermarket, a customer with different shopping behaviors can be classified into several categories, such as discount seekers, loyal regular shoppers, busy shopper & rare buyers.

**Optimization**

One goal of data mining is to optimize limited resources such as time, space, money, or material. For example, how best to use advertising to increase profits.