Data mining is not a new term. In fact it is quite old, around a century. But it is in focus nowadays a lot. Due to the boom of the digital era, now there is a whole lot more data than there has ever been. All this data plays a very important role in expanding any business. Data needs to be organized in order to carry out decisions. Hence understand the term “data mining and applications of data mining.”
What is data mining?
Data mining as the name suggests is mining the valuable data from large amounts of data.
Data mining is the process of analyzing large amounts of data and discovering solutions that help businesses solve problems, avoid risks and carry out new strategies. Data mining gives businesses the power to predict the future by understanding the past and present scenarios. Every business wants to thrive in the market. But with so much competition it gets quite difficult. One has to plan strategies in order to keep himself ahead of its competitors. Data mining helps businesses by providing the in- sights about the data that help in timely decision making.
Nowadays there is more data than ever before. Manually processing that data in order to carry out results is literally impossible. Data mining can literally process terabytes of data in just minutes or hours making it easier for you to make decisions. One can apply a wide range of statistical techniques in order to analyze that data. One can get useful insights about customer behavior, trends and relationships, identifying patterns etc. These findings can be used in order to influence the future outcome of the business.
Depending on the data only is not a solution for successful business nowadays. In fact one has to dig deep into the big data in order to get the insights and incorporate those into business in order to achieve the desired results and stay ahead of competitors.
Data mining gives insight about the future. It can be used to solve any problem in the business related to data like-
- Understanding customer behavior
- Retaining customers
- Acquiring new customers
- Generate sales
- Increasing revenues
- Fraudulent behavior
- Raising capital
- Market campaigns
Data mining helps in taking decisions keeping in mind the real-world scenario which keeps business ahead of its competitors.
Data mining process-
A typical data mining process consists of six steps-
- Understanding business
- Understanding data
- Preparation of data
- Modeling
- Evaluation
- Deployment
The first and foremost scenario is thorough understanding of the business. What are its objectives and the criteria for success?
After that, gathering the data from reliable sources. It is the most important step as the whole outcome depends on the data. Hence it is very important to have reliable and right data.
After collecting the data, you need to organize the data in the appropriate format. Remove any redundancies in the data.
After that you need to use modeling to identify the patterns for the given data. You can apply different algorithms in order to identify the trends.
After that you need to evaluate the model to see how well it will help achieve the results. You can use different algorithms to find the best modeling technique in order to achieve the goal.
At this stage you will present your research to the others, to the decision makers so that they can take decisions regarding the business.
Applications of data mining-
- Financial and banking sector
- Education sector
- Healthcare sector
- Market basket analysis
- Telecommunication
- Retail sector
- Research analysis
- Intrusion detection
Financial and banking sector- financial and banking sector relies heavily on high quality data. It requires accurate data to make its decision. For example- before giving a loan to a customer, it would like to see the earlier record of the customer like its earlier loan repaying behavior, credit card score etc. It can also be used in determining the loan payments. Data mining can easily give the information regarding the customers.
Education sector- In the education sector, EDM ( educational data mining ) is used. Its patterns can be used by both students and teachers. It helps in identifying some of the important patterns like student performance, teacher performance, developing curriculum, placement opportunities for students.
Healthcare sector- data plays an important role in the healthcare sector. It can literally improve a lot of health care infrastructure. It can help in proper utilization of resources to ensure everyone gets the best healthcare facility.
Market basket analysis- market basket analysis is basically an analysis of customer buying patterns. If a customer buys a certain item frequently, then he will buy that item in future more. Data mining helps in analyzing the customer behavior which in turns helps in promoting deals, sales and offers by the companies. Data mining helps in better customer service and hence helps in retaining the customers.
Telecommunication- with the advent of the internet, the telecommunication industry is growing at a very fast pace. Data mining can help in improving the quality of the services or creating a product according to market requirements to stay ahead in the market.
Retail sector- retail sector holds a large amount of data. This data helps in studying the patterns of buying behavior of customers, sales, and delivery of goods. With the onset of e- commerce now there is a larger quantity of data. With the help of data mining, online retailers can figure out how to promote their product.
Research analysis- data mining applications help in research analysis. Data mining helps in the cleaning of data, organizing the data, processing the data and integration of various database warehouses which helps in carrying out research.
Intrusion detection- data mining uses IDS i.e. intrusion detection system to classify relevant data. With the advent of technology and global connectivity, there is a great fear of network attacks. Network intrusion is basically an unauthorized access to a network which can steal valuable resources. Hence it has become a very important practice in data mining. An intrusion detection system generates an alarm when it detects any malicious activity.
Conclusion-
Data on its own has no value unless it is converted into meaningful information. Data mining does this job perfectly. It converts the raw data into meaningful data in order to analyze and carry out decisions. These decisions are really helpful in different areas. Data mining gives valuable in- sights into the data. With the large amounts of data we are creating now than ever, it has now become more important to organize that data. Data mining helps in identifying the patterns which act as a foundation for decision making.
