Data Mining Techniques And Their Applications

1891 Words Nov 16th, 2014 8 Pages
Data Mining Techniques and Their

Applications
Deepika Sattu, 800721246, dsattu@uncc.edu

Abstract— Data mining is logical process that is used to extract or “mining” large amount of data in order to find useful data [2]. Knowledge discovery from Data or KDD is synonym for Data Mining[13].There are many different types of techniques that can be used to retrieve information from large amount of data. Each type of technique will generate different results. The type of data mining technique that should be selected depends on the type of business problem that we are trying to solve.
Keywords: Clustering, Decision Trees, Classification,

Prediction

I. INTRODUCTION

Data is very critical for any organization. In an organization every by year massive amounts of data will be created and how fast your business reacts to that important information determines whether you succeed or fail. The big problem is how we efficiently handle the 3 V’s of Big Data.
3V’s of Big Data are Volume, Velocity, and Variety.
Volume: Amount of Data
Velocity: Speed at which the data is being processed.
Variety: Usage of data in various forms. i.e., graph, tree, nodes. [14]

Now a day’s data is in Exa Bytes and Zeta Bytes. It is impossible to manually analyze and extract data. In some Clusters data is increasing where as in others it is decreasing. There are various Data Mining techniques such as Association, Clustering, and Prediction that is used to retrieve data from Large databases (Big…
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