Customer Analytics

An interesting assessment from Dylan Wan at Oracle on the unique characteristics and importance of the customer data dimension in a Customer Analytics / data mining offer:

“Why is the customer dimension so important?

  • A well-maintained, well-deployed conforming customer dimension is the cornerstone of sound customer centric analysis

What are special characteristics of the customer dimension?

  • Customer dimension is extremely deep. It may have million rows.
  • Customer dimension is extremely wide. It has hundreds of attributes.
  • Customer dimension changes often. It is not really a slowly
    changing dimension. It is sometimes called as rapidly changing monster
  • Keeping the historical images of the customer data is important.
  • The data in the customer dimension come from multiple sources.
    Matching, de-dup, standardization among different sources is critical
    for successfully conforming the dimension.
  • The customer dimension with data may be enriched from the external data.
  • Customer data is the source for other dimensions – geography, industry, lines of business, etc.
  • You have to comply with the privacy regulation.
  • The data from external source may be only licensed for a period of
    time. The external data need to be associated with your own internal
    data for analysis for special purposes and the data need to be removed
    from your database.
  • The customer dimension itself is actually a source of fact tables.
    For example, # of customer living in California with the breakdown by
    age groups.”

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