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  • Avoiding Pitfalls in Data Acquisition - Michael Scofield

Avoiding Pitfalls in Data Acquisition - Michael Scofield

  • November 13, 2012
  • 6:00 PM - 9:00 PM
  • Best Western Executive Inn - 200 Taylor Ave N, Seattle


  • Includes keynote presentation, dinner and materials. Current DAMA-PS membership required.
  • Includes keynote presentation, dinner and materials. Discounts available for DAMA-PS members.
  • Includes keynote presentation and materials.

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Avoiding Pitfalls in Data Acquisition


By Michael Scofield

Asst. Professor, Health Information Management

Loma Linda University

Loma Linda, California  


Any time data is imported from external organizations which are distinct and dissimilar from your own, a relationship exists with a variety of duties, expectations, and technical issues.  This relationship and its data flow must be carefully spelled-out and managed. 

When one party seeks to acquire data from another, there are a host of issues which must be addressed unambiguously.  The extraction of data (particularly from business production systems and their granular databases) usually places some kind of burden upon the data originator/supplier, both for initial extract, and recurring updates.   At the target environment, the imported data, to be most useful, is probably intended to be integrated with other, existing data--very likely with a different logical architecture, and different semantics.   Hence, issues of architectural differences, architectural stability, scope, data quality, replication techniques, permissible usage, liabilities undefined all these must be addressed.

A host of questions which you should ask about the data exchange can be clustered into the following general topics:  


  • A taxonomy of kinds of data and information
  • Data suitable for your needs
  • Burden placed upon source organization & systems
  • Logical data architecture of source
  • Physical format and media
  • Data semantics and meaning
  • Documentation and testing
  • Scope & completeness
  • Versioning
  • Quality and currency
  • Update/refresh/corrections
  • Confidentiality
  • Ownership and usage
  • Purpose of original data collection and transfer
  • Potential liabilities.


 We will explore these in detail, as time permits. 


Michael Scofield is an information architect for a major U.S. financial services company.   He holds an adjunct faculty position at Loma Linda University in the Department of Health Information Management.  He a frequent speaker on topics of data quality, semantic data integration, data visualization, and data warehousing.  He has spoken to over 24 DAMA chapters in the U.S., eleven DAMA-International conferences, DAMA conferences in London and Australia.  He also speaks to numerous other professional groups including Oracle User Groups, American Society of Quality, information quality conferences, The Data Warehousing Institute, Institute of Internal Auditors, Assn. of Government Accountants, and Quality Assurance Association chapters.  He also speaks widely to general audiences on topics of the succession to the English monarchy, satellite imagery, the influence of digital technology upon society, and related topics.  He also has humor published in the L.A. Times and other journals.

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