Basically, data mining is about pulling out the important information from big volume of data. Tools used for data mining are there primarily for the purpose of examining data from different perspectives and summarizing it to useful database library. On the other hand, these tools have lately become computer based applications to be able to handle growing volume of data. At times, they are referred as well to knowledge discovery tools.
As a concept, data mining has been used long before and manual processes are what used as data mining tools. As time goes by, the onset of advanced and fast computers, increased storage capacities and analytical software tools lead to the development of automated tools which has enhanced accuracy of data mining speed, analysis and at the same time, brought down the operation costs.
These methods for data mining are employed in order to facilitate major elements similar to pull out, convert as well as load data to warehouse system, collecting and handling data in database system, allow concerned personnel to acquire the data, do data analysis as well as data presentation in format that can be interpreted easily for further decision making. These methods of data mining are used in an effort to explore the associations, trends and correlations in stored data that are based generally on different types of relationships like for instance: associations or the simplest relationship between data, clusters or logical correlations used in categorizing the data collected, classes which is a certain predefined group drawn out and the data within it is searched based on the groups, sequential patterns that is used to help in predicting a certain behavior according to the observed trends in stored data.
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The industries that cater heavily to consumers in the financial, retail, sports, entertainment, hospitality and the likes heavily depend on such methods of data mining for them to obtain quick answers to questions and at the same time, improve their business. The tools are helping them study buying patterns of consumers and for that, plan a strategy that can be made for future sales.
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A basic example of this is restaurant; they may want to know the eating habits of their consumers on different times of the day. After getting the data on hand, it is going to help them to make better decisions on what to offer on their menu on different parts of the day. With data mining tools, it helps them a lot to draw out a business plan, discount plans, advertising strategy and everything in between to further boosts their operations and sales.