In recent years a powerful combination of database technologies, data mining techniques, and analytics software have created vast new opportunities for data analysts and statisticians. For example, corporations have duly stored the results of their customer transactions in corporate databases for over a generation. There are, quite literally millions of records. Massively parallel engines can examine these data in heretofore unimagined ways. The potentials to understand customer profitability, develop better understandings of customers’ past needs and predict future ones, and to use those insights to develop new product niches are enormous.

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Data Quality (Poor Quality Data: The Fly in the Data Analytics Ointment)

  • Frank M. Guess,
  • Thomas C. Redman

摘要

In recent years a powerful combination of database technologies, data mining techniques, and analytics software have created vast new opportunities for data analysts and statisticians. For example, corporations have duly stored the results of their customer transactions in corporate databases for over a generation. There are, quite literally millions of records. Massively parallel engines can examine these data in heretofore unimagined ways. The potentials to understand customer profitability, develop better understandings of customers’ past needs and predict future ones, and to use those insights to develop new product niches are enormous.