Data mining is the process of restructuring a large database in order to generate meaningful information. It encompasses discovering patterns and trends in the data sets and converting them into a comprehensible structure for further use. The goal is to extract the patterns which will help the organization to predict future trends, assist in taking business decisions, define more effective strategies, and increase profits.

Data mining techniques and their uses.

Each of the data mining techniques caters to different business problems and provides a different insight. Let us understand the techniques used to analyze and mine different data and find insights from it:

  • Classification- this technique is used to classify data into different classes. You will use algorithms to structure how the new data set should be classified. A simple example of this can be our emails. An email program is set based on some algorithms to recognize a “legitimate” or “spam” email.
  • Anomaly detection – these are knowns as outliers, deviations, or some kinds of exceptions. Identifying the unusual data records which need investigation or attention.
  • Summarization – a concise representation of data or data set, which helps you in understanding various elements from the data.
  • Clustering – clustering is an important technique that collects data sets that are similar in nature. This process defines clusters of data that are in some way or other same within one group but different from the data in other groups or clusters.
  • Regression – regression analysis is the process of determining a relationship between multiple data or data sets. It will help you in understanding the character of one dependent data if any of the data is varied. It is widely used for forecasting and prediction.

Actually, if we see we are getting buried down with data but are hungry for knowledge within it. These techniques will help you in getting the knowledge to decide a variety of business problems to increase revenue, better customer dealing, and mitigation of risk. Only we need to think creatively about algorithms, and how to manage data using sophisticated techniques.

Effective access and use of data have even changed the way companies are operating their business in this highly competitive and challenging environment. Many data-based learning and decision systems are developed using different algorithms like Classification, Clustering, Regression, Feature Selection, Forecasting, Collaborative Filtering/Recommendation Systems, etc. Read our white paper on Artificial Intelligence, Data Mining & Contract Extraction to understand how Artificial intelligence and data mining technologies are helping companies organize their contracts and contractual obligations.