Data quality issues emerge from multiple failure points from development practices to production life cycle, each compounding others in ways that are detected only at the end: Improper data testing ...

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 ...

Forbes contributors publish independent expert analyses and insights. I track enterprise software application development & data management. Data has grades. Much like olive oil, flour, gasoline, beef ...

Good data quality is crucial for successful data and analytics initiatives and is increasingly pivotal to artificial intelligence impact. D&A leaders, including chief data and analytics officers, are ...

63% of business leaders describe their organizations as very data-driven, up 10% from 2023. Only one in two business leaders is confident about the ability to deliver timely business insights. The ...

In today's data-driven healthcare landscape, medical imaging stands at the forefront of diagnosis and treatment planning. From X-rays and MRIs to CT scans and ultrasounds, these images provide crucial ...

PHILADELPHIA--(BUSINESS WIRE)--Qlik®, a global leader in data integration, data quality, analytics, and artificial intelligence (AI), today released a new survey of 500 professionals working with AI ...

For all the talk of innovation and analytics, most business decisions still come down to trust. Can we trust what the numbers are telling us? Can we trust that our systems are secure? Can we trust the ...

Marketers suffer from a variety of negative consequences stemming from poor-quality data that collectively drains marketing resources and limits effectiveness. Wasted media spend is the most ...

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 ...

As the push to integrate artificial intelligence and increase interoperability evolves, Clinical Architecture sees a dire need for tools that can assess the quality of healthcare data. Poor quality ...