Collecting, processing, storing, and analyzing data, in order to discover and extract new information from that data, is known as data mining. The techniques of data mining can be basic or complex, and it helps organizations analyze their collected data to determine patterns or to gain new information about what they do. Without any kind of automation, processing all this information would just not be possible.

A few approaches to data mining include:

  • Cluster detection. This is a type of recognition used to detect patterns within large data sets by arranging all the gathered information into categories through patterning that shows up during analysis; these patterns might not be obvious to the human eye, but will trigger an automated system.
  • Anomaly detection. This type of recognition finds abnormalities in data, which can in turn be used in areas such as weather forecasting or forensic computing.
  • Regression. This technique is used to predict future outcomes using large sets of variables, and can be used to predict user engagement for the future, or in the area of customer retention.

The data mining technique that you choose, whether it be one of those listed above or another of the many available, will depend on what your goals are. There are many benefits to be gained from data mining:

  • Risk models. In the areas of banking and finance, data mining can be used to create risk models that are accurate when dealing with mortgages and loans. Fraudulent transactions can be detected through the use of mining, as well.
  • Conversion. The techniques of data mining can be helpful to improve conversions and increase the satisfaction of customers, and in creating advertising campaigns that are focused on certain criteria. Analyzing market needs and demands, as well as creating ideas for new products are a few other benefits, and are achieved by going through sales history and customer data to create prediction models. The more data and knowledge about customers that is collected, the more value that can be offered to them by the gained ability to provide what they want or need.
  • Fraud. Data mining techniques can used to assist tax governing organizations in detecting fraudulent transactions and suspicious tax returns as well as other business documents that are not legal.
  • Manufacturing. Data discovery is helpful in this area of business to improve product safety, usability, and comfort.

Data mining is a benefit to individual business owners and large businesses alike, in many ways. Here at Think Data Insights we have the expertise to help you to establish the perfect data mining processes for your organization. Contact us today to get started.