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Knowledge Discovery Nuggets 97:04, e-mailed 97-01-28

News:
* GPS, Information Week on Debunking Data-Mining Myths
  • http://www.techweb.com/se/directlink.cgi?IWK19970120S0042

    • * N. Uffenheimer, EDS in the data warehouse, datamining, DSS areas
    Publications:
    * J. P. Brown, Data Mining: What Needs To Be Done, And Why.
  • http://www.hal-pc.org/~jpbrown

    • * F. Famili, Intelligent Data Analysis Journal - First Issue is live,
  • http://www.elsevier.com/locate/ida

    • Siftware:
    * B. Li, Parallel C4.5,
  • http://merv.cs.nyu.edu:8001/~binli/pc4.5/

    • Positions:
    * E. Babb, Jobs in data mining in London,
  • http://www.parsys.com/dafs.htm

    • * D. Berleant, Tenure Track, Teaching and Research at U. of Arkansas
    Meetings:
    * D. Stodder, Data Mining Summit program,
  • http://www.dbsummit.com

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    Previous  1 Next   Top
    Date: Mon, 27 Jan 1997 17:11:18 -0500
    From: gps@gte.com (Gregory Piatetsky-Shapiro)
    Subject: Information week on Debunking Data-Mining Myths -
    Content-Length: 23384

    see
  • http://www.techweb.com/se/directlink.cgi?IWK19970120S0042

    • for full text

    January 20, 1997, Issue: 614
    Section: InformationWeek Labs


    Debunking Data-Mining Myths --
    Don't let contradictory claims about
    data mining keep you from improving
    your business

    By Robert D. Small

    A great deal of what is said about data mining is
    incomplete, exaggerated, or wrong. Data mining has
    taken the business world by storm, but as with many
    new technologies, there seems to be a direct
    relationship between its potential benefits and the
    quantity of often-contradictory claims, or myths,
    about its capabilities and weaknesses. It's difficult to
    fight these myths, which are based on
    misunderstandings, hopes, and fears. The new
    technology cycle typically goes like this: Enthusiasm
    for an innovation leads to spectacular assertions.
    Ignorant of the technology's true capabilities, users
    jump in without adequate preparation or training.
    Then, sobering reality sets in. Finally, frustrated and
    unhappy, users complain about the new technology
    and urge a return to 'business as usual.' When you
    undertake a data-mining project, avoid a cycle of
    unrealistic expectations followed by disappointment.
    Understand the facts instead, and your data-mining
    efforts will be successful. - Simply put, data mining
    is used to discover patterns and relationships in your
    data in order to help you make better business
    decisions.

    Myth: Data mining produces surprising results that
    will utterly transform your business.

    Fact: Most often, the results of data mining yield
    steady improvement to an already successful
    organization, often contributing important incremental
    changes rather than revolutionary ones.

    Nevertheless, data mining can lead to significant
    change in several ways. First, it may give the talented
    business manager a small advantage each year, on
    each project, with each customer. Compounded over
    a period of time, these small advantages turn into a
    large competitive edge. For example, a catalog retailer
    that can better target its mailing list can increase
    profits by reducing the cost of mailings while
    increasing the number