Studying Data Quality

OCDQ Radio is a vendor-neutral podcast about data quality and its related disciplines, produced and hosted by Jim Harris.

On this episode, Gordon Hamilton and I discuss data quality key concepts, including those which we have studied in some of our favorite data quality books, and more important, those which we have implemented in our careers as data quality practitioners.

Gordon Hamilton is a Data Quality and Data Warehouse professional, whose 30 years’ experience in the information business encompasses many industries, including government, legal, healthcare, insurance and financial.  Gordon was most recently engaged in the healthcare industry in British Columbia, Canada, where he continues to advise several health care authorities on data quality and business intelligence platform issues.

Gordon Hamilton’s passion is to bring together:

  • Exposure of business rules through data profiling as recommended by Ralph Kimball.
  • Monitoring business rules in the EQTL (Extract-Quality-Transform-Load) pipeline leading into the data warehouse.
  • Managing the business rule violations through systemic and specific solutions within the statistical process control framework of Shewhart/Deming.
  • Researching how to sustain data quality metrics as the “fit for purpose” definitions change faster than the information product process can easily adapt.

Gordon Hamilton’s moniker of DQStudent on Twitter hints at his plan to dovetail his Lean Six Sigma skills and experience with the data quality foundations to improve the manufacture of the “information product” in today’s organizations.  Gordon is a member of IAIDQ, TDWI, and ASQ, as well as an enthusiastic reader of anything pertaining to data.

Gordon Hamilton recently became an Information Quality Certified Professional (IQCP), via the IAIDQ certification program.

 

Studying Data Quality

Additional listening options:

 

Recommended Data Quality Books

By no means a comprehensive list, and listed in no particular order whatsoever, the following books were either discussed during this OCDQ Radio episode, or are otherwise recommended for anyone looking to study data quality and its related disciplines:

 

PLEASE NOTE: You are welcome to recommend additional books for this reading list by posting a comment below.

 

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