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Data mining is emerging as a key technology for enterprises that wish to improve the quality of their decision making and competitive advantage by exploiting operational and other available data. Data mining, the extraction of hidden predictive information from large databases, is a powerful new technology with great potential to help companies focus on the most important information in their data warehouse.
Modern organizations respond quickly to changes in the market. Clearly, in order to do this we need rapid access to all kinds of information before we can make any logical decisions. To assist in making the right choices for the organization, it is essential to be able to research the past and identify relevant trends. Obviously, in order to perform any trend analysis we must have access to all the information needed to support us, and this information is mainly stored in very large databases. The easiest way to gain access to this data and facilitate effective decision making is to set up a data warehouse.
The application of data mining techniques can be carried out from the existing data warehouse the part of the information that is of interest to the end user. Trying to mine operational data is almost impossible because there are different types of attributes and different data types but no historical data. With a data warehouse this problem does not exist as all the information has been transferred from the operational database to the data warehouse.
In most organizations we will find really large databases in operation for normal daily transactions. These types of databases are known as operational databases. These are not designed to store historical data or to respond to queries. A data warehouse is designed especially for decision support queries; therefore only data that is needed for decision support is extracted from the operational data and stored in the warehouse.
Data Mining is the "automatic" extraction of patterns of information from historical data, enabling companies to focus on the most important aspects of their business -- telling them what they did not know and had not even thought of asking.
Click here to download more information
Modern organizations respond quickly to changes in the market. Clearly, in order to do this we need rapid access to all kinds of information before we can make any logical decisions. To assist in making the right choices for the organization, it is essential to be able to research the past and identify relevant trends. Obviously, in order to perform any trend analysis we must have access to all the information needed to support us, and this information is mainly stored in very large databases. The easiest way to gain access to this data and facilitate effective decision making is to set up a data warehouse.
The application of data mining techniques can be carried out from the existing data warehouse the part of the information that is of interest to the end user. Trying to mine operational data is almost impossible because there are different types of attributes and different data types but no historical data. With a data warehouse this problem does not exist as all the information has been transferred from the operational database to the data warehouse.
In most organizations we will find really large databases in operation for normal daily transactions. These types of databases are known as operational databases. These are not designed to store historical data or to respond to queries. A data warehouse is designed especially for decision support queries; therefore only data that is needed for decision support is extracted from the operational data and stored in the warehouse.
Data Mining is the "automatic" extraction of patterns of information from historical data, enabling companies to focus on the most important aspects of their business -- telling them what they did not know and had not even thought of asking.
Click here to download more information
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