Data mining and warehousing
Data mining and warehousing and its importance in the organization
Data Mining
Data mining is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases.
Data mining is primarily used today by companies with a strong consumer focus - retail, financial, communication, and marketing organizations. It enables these companies to determine relationships among internal factors such as price, product positioning, or staff skills, and external factors such as economic indicators, competition, and customer demographics. And, it enables them to determine the impact on sales, customer satisfaction, and corporate profits. Finally, it enables them to drill down into summary information to view detail transactional data.
For example, “Entertainers Incorporated” is an organization which deals with entertainers for events. So the need to attract customers and communicating with them is essential. Customer satisfaction in their service is much needed for them, for the customers to approach them for the next event too. So considering all this data mining helps the organization in all the ways.
There are several major data mining techniques that have been developed and used in data mining projects recently including association, classification, clustering, prediction and sequential patterns. We will briefly examine those data mining techniques with example to have a good overview of them.
Association
Association is one of the best known data mining technique. Data can be mined to identify associations. In
Data Mining
Data mining is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases.
Data mining is primarily used today by companies with a strong consumer focus - retail, financial, communication, and marketing organizations. It enables these companies to determine relationships among internal factors such as price, product positioning, or staff skills, and external factors such as economic indicators, competition, and customer demographics. And, it enables them to determine the impact on sales, customer satisfaction, and corporate profits. Finally, it enables them to drill down into summary information to view detail transactional data.
For example, “Entertainers Incorporated” is an organization which deals with entertainers for events. So the need to attract customers and communicating with them is essential. Customer satisfaction in their service is much needed for them, for the customers to approach them for the next event too. So considering all this data mining helps the organization in all the ways.
There are several major data mining techniques that have been developed and used in data mining projects recently including association, classification, clustering, prediction and sequential patterns. We will briefly examine those data mining techniques with example to have a good overview of them.
Association
Association is one of the best known data mining technique. Data can be mined to identify associations. In