Often called data or knowledge discovery, data mining is the process of analyzing data from various perspectives and summarizing it into useful information to help beef up revenue or cut costs. Data mining software is among the many analytical tools used to analyze data. It allows categorizing of data and shows a summary of the relationships identified. From a technical perspective, it is finding patterns or correlations among fields in large relational databases. Find out how data mining works and its innovations, what technological infrastructures are needed, and what tools like phone number validation can do.
Data mining may be a relatively new term, but it uses old technology. For instance, companies have made use of computers to sift through supermarket scanner data - volumes of them - and analyze years' worth of market research. These kinds of analyses help define the frequency of customer shopping, how many items are usually bought, and other information that will help the establishment increase revenue. These days, however, what makes this easy and more cost-effective are disk storage, statistical software, and computer processing power.
Data mining is mainly used by companies who want to maintain a strong customer focus, whether they're engaged in retail, finance, marketing, or communications. It enables companies to determine the different relationships among varying factors, including staffing, pricing, product positioning, market competition, and social demographics.
Data mining software, for example, vary in types: statistical, machine learning, and neural networks. It seeks any of the four types of relationships: classes (stored data is used for locating data in predetermined groups), clusters (data are grouped according to logical relationships or consumer preferences), associations (data is mined to identify associations), and sequential patterns (data is mined to estimate behavioral trends and patterns). There are different levels of analysis, including artificial neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction, and data visualization.
In today's world, data mining applications are available on all size systems from client/server, mainframe, and PC platforms. When it comes to enterprise-wide applications, the size usually ranges from 10 gigabytes to more than 11 terabytes. The two important technological drivers are the size of the database and query complexity. A more powerful system is required with more data being processed and maintained, and with more complex and greater queries.
Programmable XML web services like phone number validation will assist your company in improving the quality of your data needed for data mining. Used to validate phone numbers, a phone number validation service allows you to improve the quality of your contact database by eliminating invalid telephone numbers at the point of entry. Upon verification, phone number and other customer information can work wonders for your business and its constant improvement.
Source: http://ezinearticles.com/?What-You-Should-Know-About-Data-Mining&id=6916646
Data mining may be a relatively new term, but it uses old technology. For instance, companies have made use of computers to sift through supermarket scanner data - volumes of them - and analyze years' worth of market research. These kinds of analyses help define the frequency of customer shopping, how many items are usually bought, and other information that will help the establishment increase revenue. These days, however, what makes this easy and more cost-effective are disk storage, statistical software, and computer processing power.
Data mining is mainly used by companies who want to maintain a strong customer focus, whether they're engaged in retail, finance, marketing, or communications. It enables companies to determine the different relationships among varying factors, including staffing, pricing, product positioning, market competition, and social demographics.
Data mining software, for example, vary in types: statistical, machine learning, and neural networks. It seeks any of the four types of relationships: classes (stored data is used for locating data in predetermined groups), clusters (data are grouped according to logical relationships or consumer preferences), associations (data is mined to identify associations), and sequential patterns (data is mined to estimate behavioral trends and patterns). There are different levels of analysis, including artificial neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction, and data visualization.
In today's world, data mining applications are available on all size systems from client/server, mainframe, and PC platforms. When it comes to enterprise-wide applications, the size usually ranges from 10 gigabytes to more than 11 terabytes. The two important technological drivers are the size of the database and query complexity. A more powerful system is required with more data being processed and maintained, and with more complex and greater queries.
Programmable XML web services like phone number validation will assist your company in improving the quality of your data needed for data mining. Used to validate phone numbers, a phone number validation service allows you to improve the quality of your contact database by eliminating invalid telephone numbers at the point of entry. Upon verification, phone number and other customer information can work wonders for your business and its constant improvement.
Source: http://ezinearticles.com/?What-You-Should-Know-About-Data-Mining&id=6916646
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