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International Journal of Trend in Scientific Research and Development (IJTSRD)
Volume 4 Issue 4, June 2020 Available Online: e-ISSN: 2456 – 6470

@ IJTSRD | Unique Paper ID – IJTSRD31368 | Volume – 4 | Issue – 4 | May-June 2020 Page 1333

Overview of Data Mining

Rupashi Koul

Department of Computer Science Engineering, Dronacharya College of Engineering, Gurugram, Haryana, India


Data mining is the process of discovering patterns in large data sets involving

methods at the intersection of machine learning, statistics, and database

systems.[1] Data mining is an interdisciplinary sub field of computer science

and statistics with an overall goal to extract from a data set and transform the

information into a comprehensible structure for further use.[1][2][3][4] The

process of digging through data to discover hidden connections and predict

future trends has a long history. Sometimes referred to as ‘knowledge

discovery’ in databases, the term data mining wasn’t coined until the 1990s.

What was old is new again, as data mining technology keeps evolving to keep

pace with the limitless potential of big data and affordable computing power.

Over the last decade, advances in processing power and speed have enabled us

to move beyond manual, tedious and time-consuming practices to quick, easy

and automated data analysis. The more complex the data sets collected, the

more potential there is to uncover relevant insights.

KEYWORDS: database, data mining, techniques

How to cite this paper: Rupashi Koul

“Overview of Data Mining” Published in

International Journal

of Trend in Scientific

Research and


(ijtsrd), ISSN: 2456-

6470, Volume-4 |

Issue-4, June 2020,

pp.1333-1336, URL:

Copyright © 2020 by author(s) and

International Journal of Trend in Scientific

Research and Development Journal. This

is an Open Access article distributed

under the terms of

the Creative

Commons Attribution

License (CC BY 4.0)



The manual extraction of patterns from data has occurred

for centuries. Early methods of identifying patterns in data

include Bayes’ theorem (1700s) and regression analysis

(1800s). The proliferation, ubiquity and increasing power of

computer technology have dramatically increased data

collection, storage, and manipulation ability. As data sets

have grown in size and complexity, direct data analysis has

increasingly been augmented with indirect, automated data

processing, aided by other discoveries in computer science,

specially in the field of machine learning, such as neural

networks, cluster analysis, genetic algorithms (1950s),

decision trees and decision rules (1960s), and support

vector machines (1990s). Data mining is the process of

applying these methods with the intentio

When working with data, the file type is as important as how we data mine the information. In the article “Overview of Data Mining”, the author discusses multiple types of data mining. When you are asked to data-mine sale data sets, which data mining would work best for the process?

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