Data Quality Assessment: Sparsity and Nullness

Blog Administrator | Analyzing Data, Analyzing Data Quality, Data Quality, Data Quality Assessment | , , , , , ,

By David Loshin

The first set of data quality assessment techniques that use column value frequency analysis focuses on the relationship of the population of values to the business processes that consume the data. The intent is to understand how the relative population of the column is associated with defined (or implicit) business rules, and then isolate and validate those rules.
Read More

Assessment is the Critical First Step

Blog Administrator | Analyzing Data Quality, Data Quality, Data Quality Assessment | , , , , ,

By Elliot King

Edward Deming taught us long ago about the virtuous cycle of continual quality improvement–plan for change; execute the change; study the results and then take action to improve the process. But Deming’s PDSA (plan, do, study, act) cycle is a generic approach. The cycle has to be modified and customized to address targeted areas for quality improvement.

The key steps in the virtuous cycle for data quality improvement are
assessment, measurement, integration, improvement and management.… Read More

Increasing Data Utility and Gaining Business Value from Data Enhancement

Blog Administrator | Data Enhancement | , , , ,

By David Loshin

  Most business applications are originally designed to serve a specific purpose, and
  consequently, the amount of data either collected or created by any specific application is
  typically just enough to get the specific job done. In this case, the data is utilized for the
  specific intent, and we’d say that the “degree of utility” is limited to that single business application.… Read More