Data Mining

Data Mining
Data Mining Process

Data mining is a complex activity that can be done by a few having large experience having used large 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 an evaluate mining models, and disseminate the new information relevant to achieve the goal set.

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

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

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

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

The world today is running behind 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 to turn raw data into useful information. 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 retails 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 with 20% are lossless. The company should aim at increasing profit with an additional 80%.
  • Corporations can appoint a 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 the products, data mining techniques can be useful to identify all the shopping patterns.
  • Data mining also helps in data optimization.
  • One of the most important factors of 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 telecommunication are the main reasons for that. With the help of the Data mining techniques, professionals can get fraud-related data such as caller ID, location, duration of the call, the exact date and time, etc which can help to 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 for 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.

Data Mining Techniques
Diagram of Data Mining Techniques