As levels of data mining grow, companies need new storage technology to keep track of their information. Amreetha Vijayakumar of Frost & Sullivan reports.
Needles in the haystack
Amreetha Vijayakumar
Data mining came to prominence in the late 1990s with the
rapid growth of digital data and it is now commonly applied
across many industries. The rate of growth has been astounding,
and current systems are challenged in their efforts to process
and manage such large data sets.
Data mining involves software equipped with generic algorithms
and procedures that can extract patterns in data, explore
relationships that exist in the data sets, and generate risk
management solutions.
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