This is where AI-augmented data quality engineering emerges. It shifts data quality from deterministic, Boolean checks to ...

In some ways, data and its quality can seem strange to people used to assessing the quality of software. There’s often no observable behaviour to check and little in the way of structure to help you ...

Data quality in the modern economy, where data-driving action is critical to business success, can no longer be perceived as mere tech detail. Business leaders increasingly use data to make strategic ...

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 ...

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.

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 ...

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 ...

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

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 ...

Linying Dong is affiliated with Ryerson University, and volunteers at the Board of Directors of Carefirst. Karim Keshavjee is the CEO and majority shareholder of InfoClin Inc, an organization that ...