Data Mining


Data Mining Process

Data mining is a complex activity that can be done by a few people with large experience and who have used large amounts of data from different fields and various applications.

The Data mining process involves a series of steps to define a business problem, gather and prepare the data, build and evaluate mining models, and disseminate the new information relevant to achieving the goal set.

Data mining is how patterns in large data sets are viewed and discovered by making use of intersecting techniques such as statistics, machine learning, and database systems.

It involves the extraction of data from a set of raw and unidentified sets of data to provide some meaningful results using mining.

The extracted data is then further put to use by making use of transformation and ensuring that it is put to the best use as per business requirements and needs.

It is only about the right techniques and some analysis to make your usual normal business a differentiator among the competitors.

The world today is running behind in data and its management and efficient handling is the key factor that impacts majorly the growth of an organization, especially in today’s times.

Data mining is a process used by companies / Government Departments / Banks, and Income-tax departments to turn raw data into useful information based on the analysis required based on various parameters.

By using software to look for patterns in large batches of data, businesses can learn more about their customers to develop more effective marketing strategies, increase sales, and decrease costs. Data mining depends on effective data collection, warehousing, and computer processing.

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 Email filtering, or even to discern the sentiment or opinion of users.

Data Mining has enormous advantages. Some are listed below –

  1. To predict future trends
  2. In Finance and banking related to customers
  3. Determining customer groups
  4. Increases brand loyalty
  5. Helps in decision making
  6. Increases company revenues
  7. Marketing and retail for various analysis
  8. Increases website optimization
  9. For website traffic Analysis

Important points to remember –

  • Communication is important when dealing directly with data mining so that strong relationships and connections can be determined.
  • Due to the 80/20 principle, if there are 20% of customers, then the profit will be 80%.
  • The customers that are important have 20% of them being lossless. The company should aim to increase profit by an additional 80%.
  • Corporations can appoint Data Mining consultants for their data analysis.
  • There are two concepts called segmentation and clustering that are important in advertising and the connection of customers to successfully use the data mining on the details.
  • Data mining was also used as part of the strategy for preventing health fraud, waste, and abuse in society in the area of CMIP of the Medicaid Integrity Program.
  • If you have knowledge of data mining techniques, you can manage applications in various areas such as Market Analysis, Production Control, Sports, Fraud Detection, Astrology, etc.
  • If you have a website for shopping, then data mining will help in defining a shopping pattern. If you are having issues with designing or selecting products, data mining techniques can be useful to identify all shopping patterns.
  • Data mining also helps in data optimization.
  • One of the most important factors in data mining is that it determines hidden profitability.
  • The risk factor in business can be taken care of because data mining provides clear identification of hidden profitability.
  • Frauds and malware/hackers are the most dangerous threats on the internet, which are increasing day by day. Credit card services and telecommunications are the main reasons for that. With the help of data mining techniques, professionals can get fraud-related data such as caller ID, location, duration of the call, exact date and time, etc., which can help them find a person or group who is responsible for that fraud.
  • Also in the Corporate world, where time is money, data mining techniques can help organizations in real-time planning finances and resources, evaluation of assets, an idea about business competitors, etc.

I have done many projects of data mining for Banks, as well as for Government Departments.