Abstract:
Data mining is the process of analyzing enormous amounts of information and datasets, extracting
(or “mining”) useful intelligence to help organizations solve problems, predict trends, mitigate risks,
and find new opportunities. Data mining is like actual mining because, in both cases, the miners are
sifting through mountains of material to find valuable resources and elements. Data mining also
includes establishing relationships and finding patterns, anomalies, and correlations to tackle issues,
creating actionable information in the process. Data mining is a wide-ranging and varied process
that includes many different components, some of which are even confused for data mining itself.
Keywords— Knowledge Discovery in Data, or KDD, knowledge extraction, data pattern analysis,
data archaeology, data dredging, information harvesting, business intelligence.
Description:
Data mining is the process of analyzing enormous amounts of information and datasets, extracting
(or “mining”) useful intelligence to help organizations solve problems, predict trends, mitigate risks,
and find new opportunities. Data mining is like actual mining because, in both cases, the miners are
sifting through mountains of material to find valuable resources and elements. Data mining also
includes establishing relationships and finding patterns, anomalies, and correlations to tackle issues,
creating actionable information in the process. Data mining is a wide-ranging and varied process
that includes many different components, some of which are even confused for data mining itself.
Keywords— Knowledge Discovery in Data, or KDD, knowledge extraction, data pattern analysis,
data archaeology, data dredging, information harvesting, business intelligence.
