Data Mining and Warehousing

INTRODUCTION: The technology that exists with Data Mining and Warehousing is comparatively a new term but the technology is not. Data Mining is the process of digging or gathering information from various databases. This includes data from point of sales transactions, credit card purchases, online forms which are just a few of the many things that some of the large companies dig to find out more about their clients. The information is used to find out how major of the clients shopping behavior, or what makes them irritated or simply how can they make the life of the client happier. Since gathering all this information is a necessity in order to increase sales and have a better relationship ...

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about the database and the objects in the database and, if the database is a faithful mirror, of the real world registered by the database (Holshemier & Siebes, 1994). Data mining or knowledge discovery is a way of sifting through millions and millions of records that help the people who make decisions to better understand the needs of the customer. Although this technology is in its infancy state many industries are using this technology some of them to note are retailers, finance, health care, transportation and aerospace are just a noted few. These industries are already using the technology. By using complex mathematical and statistical techniques and pattern recognition techniques they get information that about 10 years ago would seem an enormous a job that would require months to process. Today these figures are processed at an amazingly high speed and with precision to the “T’. These figures and analysis help an analyst in recognizing the fact of relationship, trends, ...

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are collected by various means and sources. This could come by various means. Organizations collect huge amounts on a daily basis. These are in different formats and in different databases, some of the types that these software’s collect are given below:

1. Operational data such as sales, cost, inventory, payroll and accounting

2. Non operational data such as industry sales, forecast data and macro economic data

3. Meta data: - data about the data itself such as logical database design or data dictionary definitions.

These are then collected and stored away in Data Warehouses where it will be analyzed for different reasons.

Today Data Mining can help businesses in many ...

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PAPER DETAILS
Added: 3/15/2011 04:30:46 PM
Submitted By: kartikeyan4686
Category: Computers
Type: Premium Paper
Words: 3212
Pages: 12

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