Integration of data mining with databases or data warehouses

Running head : An Overview of Data Mining An Overview of Data Mining

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Introduction

The Information System in the organisation should be used to improve the tasks people perform . The Information Technology is the fastest , easiest and time-savvy way of spreading knowledge throughout the organisation and in the organisation community . But this purpose can only be achieved if the people know how to use the information system in to improve their tasks performed . In similar way a large amount of data is not a

way to business success . The lack of information about the data and improper storage can result in complications . So in to use an Information System in a proper system , it is important that

It should be properly stored and categorise in an understandable manner

Data should be relevant and to the point

The Information System should be user friendly

It should enhance the performance of the employees

The employees should find it easier to use Information system

Data mining is an information analysis tool that involves the automated discovery of patterns and relationships in a data warehouse . Data mining represents the next step in the evolution of decision support systems It makes use of advanced statistical techniques and machine learning to discover facts in a large database , including databases on the Internet Unlike query tools , which require users to formulate and test a specific hypothesis , data mining uses built-in analysis tools to automatically generate a hypothesis about the patterns and anomalies found in the data and then from the hypothesis predict future behavior

Data mining 's objective is to extract patterns , trends , and rules from data warehouses to evaluate (i .e , predict or score ) proposed business strategies , which in turn will improve competitiveness , improve profits and transform Business processes . It is used extensively in marketing to improve customer retention cross-selling opportunities campaign management market , channel and pricing analysis and customer segmentation analysis (especially one-to-one marketing . In short , data mining tool help end users find answers to questions they never even thought to ask

There are thousands of data mining applications . Bell Canada uses data mining to identify patterns and group customers with similar characteristics and create predictive target models that help determine which customers should receive a particular offer (Wilde , 2000 Fingerhut uses data mining to create specialized catalogs and optimize mailings to secure the highest possible revenue from the more than one million catalogs it mails each day (Conolly , 1999 . Credit card issuers and insurers mine their data warehouses for subtle patterns within thousands of customer transactions to identify fraud , often just as it happens . One U .S cellular phone company is using Silicon Graphics MineSet software to dig through mountains of call data and pinpoint illegally cloned cell phone ID numbers . Manufacturers mine data collected from factory floor sensors to identify where an intermittent assembly line error is causing a defect that will show up only months after an appliance goes into use

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