Data Mining Basics and its Techniques
Data mining, also known as Knowledge Discovery in Data (KDD) is about searching large stores of data to uncover patterns and trends that go beyond simple analysis. This, however, is not a single-step solution but a multi-step process and is completed in various stages. These include:
1] Data gathering and Preparation
It starts with data collection and its proper organization. This helps in significantly improving the chances of finding the information that can be discovered through data mining
2] Model Building and Evaluation
The second step in data mining process is the application of various modeling techniques. These are used to calibrate the parameters to optimal values. Techniques employed largely depend on analytic capabilities required to address a gamut of organizational needs and to arrive at a decision. Let us examine some data mining techniques in brief. It is found that most organizations combine two or more data mining techniques together to form an appropriate process that meets their business requirements. Read: What is Big Data?
Data Mining Techniques
Data Mining is at the heart of analytics efforts across a variety of industries and disciplines like communications, Insurance, Education, Manufacturing, Banking and Retail and more. Therefore, having correct information about it is essential before apply the different techniques.
