by Hey guys, what is up. In this particular post, we will be talking about what is data mining with examples. Also about its history, advantages and how it works.
Updated on 05.10.2021
KEY POINTS
What is data mining?
Data mining is a method of studying large volumes of data to find business intelligence. That helps organizations to solve issues, reduce risks and grab new opportunities. This branch of data science gets its name from the similarities between findings of important data from a big database. And, extracting ore from a mountain. Both methods require refining through a huge amount of things to find hidden data.
It can reply to business questions that are time-consuming to sort out physically. It is used in many areas of research, business, including sales, healthcare, education, and product development. When this technology is used wisely it can help you in gaining several advantages over contenders. By helping you study customer needs, developing marketing plans, increasing profits, and decreasing prices.
History of data mining:
It is not a new discovery in the world. This concept was discovered around 100 years. But it came into human vision in the 1930s. One of the examples of this technique came into existence in 1936 when Alan Turing launched the concept of a modern machine. That can perform all the calculations and do work as a modern computer.
Now businesses are using machine learning, deep learning, and data mining. Businesses are using these technologies to upgrade their business from sales to financials for investing motives. As an outcome, data scientists have become important to companies that are thinking towards attaining higher aims with data science.
How this technology works:
It requires searching and scanning large blocks of data to obtain meaningful figures and trends. It can be used in several ways like fraud-spotting, credit risk control, database marketing, spam email clearing, or detect the point of view of customers.
Data mining techniques is divided into five steps.
1. Companies gather information and fill them in their data warehouse.
2. Then they keep and manage the information either in their private servers or in the cloud.
3. Business analysts, information technology, and controlling team executives read the information. Also, control that data as they want to arrange it
4. Then their software classifies the information based on the customer’s results.
5. Finally, the end-user organizes the information in an easy format, such as tables or graphs.
Examples:
- Marketing: This technology is use to examine growingly large databases and to improve market breakdown. By studying the parameters like gender, tastes, age, etc, it is likely to estimate their behavior in loyalty campaigns. It also predicts which customers will discontinue any service.
- Retail: Supermarkets, for instance, utilize buying patterns to recognize product association. Also, decides how to put them in racks. It also, finds which products on offers are mostly bought by customers.
- Banking: Banks use this technology to know market dangers. It is mostly put to credit rankings and to anti-fraud devices to study transactions, buying patterns, and customer financial information. It also allows banks to know more about their online choices or habits to boost the returns on their marketing campaigns.
- Medicine: It allows more precise diagnostics. Having the entire patient’s personal data, such as medical reports, physical examinations, and treatment figures. Moreover, this empowers them with more effective treatments to be advise. It also empowers more successful, systematic, and economical management of health resources.
Advantages:
Data is flowing into businesses in multiple numbers of forms at extraordinary speeds and volumes. Moreover, being a data-operated business is not an option. Business success leans on how fast you locate data from big data and include them into procedure and selection. With a huge amount of data to control this looks like a tedious task.
This technology certifies organizations and companies to improve the future by recognizing past and present actions. Also, making guesses about what is likely to occur in the future.
For instance, this technology can let you know which things are expect to become more profitable. With the help of user profiles based on past experience. Also, with the help of this information, you can grow your returns.
In the upcoming post, you will be getting information related to one of the most important coding topics. You can read previous posts by scrolling downwards. Also, stay tuned for the upcoming post.
