What is data mining?

Data mining is a business technique to refine raw data. Companies use this technique to get useful statistics from raw information to make their sales more effective and efficient. By the analysis of patterns in data, companies can provide effective customer services, and can decrease their cost. Data mining is based on efficient and managed data and computer processing. The other name of data mining is knowledge discovery in data (KDD).

How does data mining work?

Data mining is a practice of exploring useful data from large information bank to get significant patterns that are easy to understand. It works in several ways, such as database marketing that is listing the names, emails, addresses, phone numbers, and shopping history of customers. It also works for fraud detection, credit risk management, and users’ opinions noticing to improve sales.

It helps to identify the habits of customers that buy the same product of your company. It predicts which customer can leave your company’s product for a Competitor Company’s product. Companies use data mining techniques to get a high response rate on their advertisement and enlist the products and services that most customers buy.

Data mining is associated with five different procedures. The first step is the collection of data in the warehouses of the organization. In the next step, the organization reserves and manages the useful data in house servers or clouds. The expert team of business analysts, management, and information technology; analyzes the data and organizes it. Computer software accesses the data based on the user’s result. Finally, experts and computer programs present the data in the form of graphs and tables, that is easy to understand and easy to store.

Data warehousing and mining software:

Data mining analyzes the relationships and patterns in data based on the users’ demand. The company needs data mining software for data classification; the best illustration is of a restaurant. The restaurant uses data mining software to analyze the data. It is useful for restaurants to determine the effective timing of special offers. Restaurant management examines the patterns in data to know the customer demand for a specific event.

In other words, data miners use a bunch of data to get trends in customer behavior. Data mining is the finding of the good that is in demand. It also helps in classifying customers according to their demand for a product and finding the product that has a high buying rate. It helps to increase the effective profit and to stand business well.

Data warehousing is a technique to store useful data. The companies compose the data from different sources in one comprehensive platform. This composed data is efficient and less time-consuming in finding the required information. Organizations store the data in form of tables and graphs. According to the customer’s point of view, that table may be of their names, contact numbers, email addresses. Graphs and tables are easy to store and efficient in learning.

Companies use the data mining and warehousing process in everyday decision making. This data helps to discover better decisions for the success of the business.

Example of data mining

Mostly, grocery stores use data mining techniques. Supermarkets provide their loyalty cards to the customers. The cardholder can enjoy special discounts on that supermarket product. With the help of that card, supermarkets have an analysis of customer buying. After the evaluation, the companies can efficiently target the audience with special offers that may avail the offer.

The most recent example occurred in US supermarkets. The store management started an analysis on the customers buying by looking at their shopping carts to target the pregnant ones. They set the rules and classifying their customers that are pregnant, likely to pregnant or not. Then they started promoting the nappies and cotton wools to the target audience. The analysis was so accurate that the advertisement targeted the families that were expecting and those that were not even realized at that time. This analysis was a success and resulted in a massive profit.

Data mining has a vast scope in many other fields as well. It is used in retail, banking, and finance and also in crime investigation.

Key takeaways:

• Data mining is the extraction of useful data in graphs and tables form from complex data sources like social media content.
• Companies use data mining techniques for connection building between the customers and the business to promote the sale.
• Data mining helps to classify the products that are in demand that helps to promote better decisions.
• Companies detect frauds and errors with the help of data mining. It helps companies to prevent profit loss and reputation damage.
• The main aim of data mining is to stand your business in this competitive environment by predicting effective decisions. Data mining drives those decisions by analyzing the trends in past data.