Study Report On Data Mining

3613 Words15 Pages
UNIVERSITY OF NORTH CAROLINA AT CHARLOTTE

STUDY REPORT
ON
Data Mining

Submitted By Submitted To
Harshil Sheth DR. Anthony B. Wilkinson
800833329

Submitted in the partial fulfilment of Master’s Degree in Computer Science Contents
1. Abstract

2. Need for Data Mining

3. History of Data Mining

4. DATA MINING PROCESS

5. Applications of Data Mining

6. Privacy Concerns and Ethics

7. Precaution to be taken before using the data

8. References

Abstract
Data mining is the analysis step of the "Knowledge Discovery in Databases" process, or KDD. An interdisciplinary subfield of computer science, Data Mining is the computational process of discovering patterns in large data sets involving methods
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This usually involves using database techniques such as spatial indices. These patterns can then be seen as a kind of summary of the input data, and may be used in further analysis or, for example, in machine learning and predictive analytics.
From a practical perspective, Data Mining automates the whole process of categorizing and discovering new understandable relationship by using advanced tools and utilizing some basic understanding of statistics, machine learning and database systems. The useful accurate information we acquire after applying this process is reusable and utilized to take important steps towards increased revenue, reduced costs in retail, financial, communication, and marketing business organization. The wide range of applicability in heterogeneous domains which comprises of large volume of rich data makes Data Mining an important and challenging sector for the Data scientists.

Why do we need Data Mining?
• We are in an age often referred to as the information age. In this information age, we believe that information leads to power and success. We have been collecting tremendous amounts of data.
• Initially, with the advent of computers and means for mass digital storage, we started collecting and storing all sorts of data, counting on the power of computers to help sort through this amalgam of information. Unfortunately, these massive collections of data stored on disparate structures very rapidly
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