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

Forbes contributors publish independent expert analyses and insights. Gary Drenik is a writer covering AI, analytics and innovation. In today’s rapidly transforming world, Data has emerged as a key ...

Two IT air quality data systems that inform the U.S. Environmental Protection Agency’s (EPA’s) regulatory and compliance decisions are outdated, the U.S. Government Accountability Office (GAO) has ...

The biggest challenge to AI initiatives is the data they rely on. More powerful computing and higher-capacity storage at lower cost has created a flood of information, and not all of it is clean. It ...

The Government Accountability Office (GAO) is concerned that aging systems present challenges in obtaining reliable air quality data. The Environmental Protection Agency (EPA) primarily uses two ...

Learn the definition of data quality and discover best practices for maintaining accurate and reliable data. Data quality refers to the reliability, accuracy, consistency, and validity of your data.

Fab operations have wrestled with big data management issues for decades. Standards help, but only if sufficient attention to detail is taken during collection. Semiconductor wafer manufacturing ...

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 ...