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

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 ...

Data quality assessments help you avoid introducing errors into your database. Learn how they work and why you need them. Image: Sikov/Adobe Stock Data quality assessments have the same goal that data ...

Modern analytics pipelines often follow the medallion architecture, which organizes data into Bronze (raw), Silver (cleansed) and Gold (curated) layers. The idea is that each stage should refine the ...

Enhance your data strategy with effective data quality and data governance practices. Learn their differences and how to integrate the strategies successfully. Image: Dmitry/Adobe Stock Data quality ...

In this podcast, we talk with Cody David, solutions architect with Syniti, which is part of Capgemini, about the importance of ensuring data quality for artificial intelligence (AI) workloads. Being ...

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 ...

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 ...

Alation Inc., the data intelligence company, is announcing the launch of its Agentic Platform—a solution that empowers data teams with AI-driven automation—and with it, three additional new ...