Data mining basically means pulling out important information from huge volume of data. Data mining tools are used for the purposes of examining the data from various viewpoints and summarizing it into a useful database library. However, lately these tools have become computer based applications in order to handle the growing amount of data. They are also sometimes referred to as knowledge discovery tools.
As a concept, data mining has always existed since the past and manual processes were used as data mining tools. Later with the advent of fast processing computers, analytical software tools, and increased storage capacities automated tools were developed, which drastically improved the accuracy of analysis, data mining speed, and also brought down the costs of operation. These methods of data mining are essentially employed to facilitate following major elements:
Pull out, convert, and load data to a data warehouse system
Collect and handle the data in a database system
Allow the concerned personnel to retrieve the data
Data analysis
Data presentation in a format that can be easily interpreted for further decision making
We use these methods of mining data to explore the correlations, associations, and trends in the stored data that are generally based on the following types of relationships:
Associations - simple relationships between the data
Clusters - logical correlations are used to categorise the collected data
Classes - certain predefined groups are drawn out and then data within the stored information is searched based on these groups
Sequential patterns - this helps to predict a particular behavior based on the trends observed in the stored data
Industries which cater heavily to consumers in retail, financial, entertainment, sports, hospitality and so on rely on these data methods of obtaining fast answers to questions to improve their business. The tools help them to study to the buying patterns of their consumers and hence plan a strategy for the future to improve sales. For e.g. restaurant might want to study the eating habits of their consumers at various times during the day. The data would then help them in deciding on the menu at different times of the day. Data mining tools certainly help a great deal when drawing out business plans, advertising strategies, discount plans, and so on. Some important factors to consider when selecting a data mining tool include the platforms supported, algorithms on which they work (neural networks, decisions trees), input and output options for data, database structure and storage required, usability and ease of operation, automation processes, and reporting methods.
Jeff Smith is the managing director of Karma Technologies and feels strongly about implementing ways to be green into their business practices, to a point they are almost a paper-free company.
Source: http://ezinearticles.com/?Data-Mining-Tools---Understanding-Data-Mining&id=1109771
As a concept, data mining has always existed since the past and manual processes were used as data mining tools. Later with the advent of fast processing computers, analytical software tools, and increased storage capacities automated tools were developed, which drastically improved the accuracy of analysis, data mining speed, and also brought down the costs of operation. These methods of data mining are essentially employed to facilitate following major elements:
Pull out, convert, and load data to a data warehouse system
Collect and handle the data in a database system
Allow the concerned personnel to retrieve the data
Data analysis
Data presentation in a format that can be easily interpreted for further decision making
We use these methods of mining data to explore the correlations, associations, and trends in the stored data that are generally based on the following types of relationships:
Associations - simple relationships between the data
Clusters - logical correlations are used to categorise the collected data
Classes - certain predefined groups are drawn out and then data within the stored information is searched based on these groups
Sequential patterns - this helps to predict a particular behavior based on the trends observed in the stored data
Industries which cater heavily to consumers in retail, financial, entertainment, sports, hospitality and so on rely on these data methods of obtaining fast answers to questions to improve their business. The tools help them to study to the buying patterns of their consumers and hence plan a strategy for the future to improve sales. For e.g. restaurant might want to study the eating habits of their consumers at various times during the day. The data would then help them in deciding on the menu at different times of the day. Data mining tools certainly help a great deal when drawing out business plans, advertising strategies, discount plans, and so on. Some important factors to consider when selecting a data mining tool include the platforms supported, algorithms on which they work (neural networks, decisions trees), input and output options for data, database structure and storage required, usability and ease of operation, automation processes, and reporting methods.
Jeff Smith is the managing director of Karma Technologies and feels strongly about implementing ways to be green into their business practices, to a point they are almost a paper-free company.
Source: http://ezinearticles.com/?Data-Mining-Tools---Understanding-Data-Mining&id=1109771
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