Understanding Data Mining

What is Data Mining?

Data Mining is the process of finding patterns in data and use these patterns to predict future outcomes. These predictions are generally used to make important decisions. It includes analyzing large amount of historical data that was previously incomprehensible and ignored. 

The goal of Data Mining is to transform large amount of incomprehensible data into something meaningful, so that it can be understood easily. Thus, it is a process which is used by data scientists to convert large sets of data into something usable.

Data Science vs. Data Mining

Both of these words have become the buzz words of 21st century. The definitions of both Data Science and Data Mining are similar. Understandably, people are confused between these two terms. 

Here are a few differences between these two:

• Data Science is an area, whereas Data Mining is a technique.
• Data Mining is basically a subset of Data Science.
• The goal of Data Science is to build data-centric products for organizaions whereas the goal of Data Mining is to make data more usable.
• Data Science deals with structured, semi-structured and unstructured data whereas Data Mining mostly works with structured data.