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Nowadays, large quantities of data is being accumulated. The amount of data collected is said to be almost doubled every 9 months. Seeking knowledge from massive data is one of the most desired attributes of Data Mining. Data could be large in two senses. In terms of size, e.g. for Image Data or in terms of dimensionality, e.g. for Gene expression data. |
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Usually there is a huge gap from the stored data to the knowledge that could be construed from the data. This transition won't occur automatically, that's where Data Mining comes into picture. In Exploratory Data Analysis, some initial knowledge is known about the data, but Data Mining could help in a more in-depth knowledge about the data. |
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Manual data analysis has been around for some time now, but it creates a bottleneck for large data analysis. |
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Fast developing computer science and engineering techniques and methodology generates new demands. Data Mining techniques are now being applied to all kinds of domains, which are rich in data, e.g. Image Mining and Gene data analysis. |