Data Mining

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What is data mining?

Data mining is a process used by companies to transform raw data into useful information. By using software to find patterns in large amounts of data, companies can learn more about their customers to develop more effective marketing strategies, increase sales, and reduce costs. Data mining depends on efficient data collection, storage and processing.

Data mining processes are used to create machine learning models that power applications, including search engine technology and website recommendation programs.

How Data Mining Works

Data mining involves exploring and analyzing large blocks of information to glean meaningful patterns and trends. It can be used in a variety of ways, such as database marketing, credit risk management, fraud detection, spam filtering, or even to discern users’ feelings or opinions.

The data mining process is broken down into five stages. First, organizations collect data and upload it to their data warehouses. Then they store and manage the data, either on internal servers or in the cloud. Business analysts, management teams, and IT professionals access data and determine how they want to organize it. Next, the application software sorts the data based on the user’s results, and finally, the end user presents the data in an easy-to-share format, such as a graph or table.

Data warehousing and exploitation software

Data mining programs analyze relationships and data models based on what users are asking for. For example, a company can use data mining software to create information classes. To illustrate this, imagine that a restaurant wants to use data mining to determine when it should offer certain special offers. He examines the information he has collected and creates classes based on when customers visit and what they order.

In other cases, data miners find clusters of information based on logical relationships or examine associations and sequential models to draw conclusions about trends in consumer behavior.

Warehousing is an important aspect of data mining. Warehousing is when companies centralize their data in a database or program. With a data warehouse, an organization can generate data segments for specific users to analyze and use.

However, in other cases, analysts can start with the data they want and create a data warehouse based on these specifications. No matter how companies and other entities organize their data, they use it to support management decision-making.

Example of data mining

Grocery stores are well known users of data mining techniques. Many supermarkets offer free loyalty cards to customers which give them access to discounted prices not available to non-members. The cards make it easy for stores to track who buys what, when they buy it, and at what price. After analyzing the data, stores can then use this data to offer customers targeted coupons on their buying habits and decide when to put items on sale or when to sell them at a high price.

Data mining can be a concern when a company uses only selected information, which is not representative of the entire group of samples, to prove a certain hypothesis.

Key points to remember

  • Data mining is the process of analyzing a large batch of information to discern trends and patterns.
  • Data mining can be used by businesses for everything from knowing what interests or wants to buy customers to fraud detection and spam filtering.
  • Data mining programs break down models and data connections based on the information that users request or provide.

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