Why Data Quality Should Start At The Beginning, Not The End

Data quality issues emerge from multiple failure points from development practices to production life cycle, each compounding ...
SD Times

The hidden crisis behind AI’s promise: Why data quality became an afterthought

Value stream management involves people in the organization to examine workflows and other processes to ensure they are deriving the maximum value from their efforts while eliminating waste — of ...
TechRepublic

Data quality management: Roles & responsibilities

DQM is becoming a core capability for organizations that need to make better decisions with data. What are the responsibilities of different roles in DQM? Image: WrightStudio/Adobe Stock Data quality ...
TechRepublic

Top 7 Data Quality Tools and Software

It can be tough to manage data manually, and doing so can sometimes lead to errors or inefficiencies. Spreadsheets can get overly complex, and data quality can suffer. This has become a large enough ...
International Monetary Fund

Data Quality Assessment Framework and Data Quality Program

1. The Data Quality Assessment Framework (DQAF) was developed to address the Executive Board's interest in data quality as expressed during the December 1997 discussion of the Progress Report on the ...