Recognizing the Gap Between Raw Data and Information:
A Case Study in Data Quality with the Covid-19 Pandemic.

Join us and speaker Michael Scofield, Asst Clinical Professor at Loma Linda University. There is often a long path between the reality which raw data describes, and decision-maker understanding of what is going on (“big picture”). This “data-to-understanding supply chain” has many steps, with potential for lapses in the quality of data and information. This gap (with threats to quality) is particularly evident in the flow of Covid-19 data being passed around units of government in the U.S. The state and county totals suffer from a variety of definitions, inconsistent processes, and various sources of delay in reporting. This slide presentation provides simple explanations of the kinds of tests (antigen vs. antibody), and other issues of false negatives, comorbidity, and sampling techniques. Ambiguities abound. We shall also consider other new metrics which would be useful to understand this pandemic. We shall also touch on best practices in data visualization.

Michael Scofield, M.B.A. is an Assistant Clinical Professor at Loma Linda University. He is a frequent speaker and author in topics of data management, data quality, data visualization, and data warehousing. He has spoken in over 27 states, Canada, Australia, and the U.K. Audiences have included 24 DAMA chapters, 5 TDWI chapters, 14 ASQ sections and many accounting professional organizations. He also does guest lectures at several universities.
His career experience includes some time with a CPA firm, developing an accounting and general ledger system for a major California bank, as well as experience in government, manufacturing, finance, and software development. Now semi-retired, he still does pro bono data mining and data quality analysis for non-profit organizations. His greatest interest currently is data visualization, data quality assessment, and using graphic techniques