I'll explore data-related challenges, the increasing importance of a robust data strategy and considerations for businesses ...

Quality data is critical to informing public health actions. | The time has come for CMS to implement performance measures—or quantitative metrics—for public health and clinical data exchange, writes ...

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 ...

Without high-quality, well-governed data, every downstream AI initiative becomes fragile, expensive, inaccurate or downright ...

While companies may share common ground when it comes to their data quality problems, data quality tools and strategies are not one-size-fits-all solutions to the problem. Each company should approach ...

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.

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 ...

It has been estimated by MITSloan that the cumulative cost of inaccurate data is 15 to 25 per cent of revenue for most organisations. This is because poor quality data wastes resources, undermines ...