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Note for Data Mining And Data Warehousing - DMDW by Ashutosh Jaiswal

  • Data Mining And Data Warehousing - DMDW
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Why Mine Data? Commercial Viewpoint  Lots of data is being collected and warehoused – Web data, e-commerce – purchases at department/ grocery stores – Bank/Credit Card transactions  Computers have become cheaper and more powerful  Competitive Pressure is Strong – Provide better, customized services for an edge (e.g. in Customer Relationship Management) © Tan,Steinbach, Kumar Introduction to Data Mining 4/18/2004 2

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Why Mine Data? Scientific Viewpoint  Data collected and stored at enormous speeds (GB/hour) – remote sensors on a satellite – telescopes scanning the skies – microarrays generating gene expression data – scientific simulations generating terabytes of data   Traditional techniques infeasible for raw data Data mining may help scientists – in classifying and segmenting data – in Hypothesis Formation

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Mining Large Data Sets - Motivation    There is often information “hidden” in the data that is not readily evident Human analysts may take weeks to discover useful information Much of the data is never analyzed at all 4,000,000 3,500,000 The Data Gap 3,000,000 2,500,000 2,000,000 1,500,000 Total new disk (TB) since 1995 1,000,000 Number of analysts 500,000 0 1995 1996 1997 1998 1999 ©From: Tan,Steinbach, R. Grossman, Kumar C. Kamath, V. Kumar, Introduction “Data Mining to Data for Mining Scientific and Engineering Applications” 4/18/2004 4

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What is Data Mining?  Many Definitions – Non-trivial extraction of implicit, previously unknown and potentially useful information from data – Exploration & analysis, by automatic or semi-automatic means, of large quantities of data in order to discover meaningful patterns © Tan,Steinbach, Kumar Introduction to Data Mining 4/18/2004 5

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