Data integrity is an ongoing concern across all R&D organizations, no matter what part of the research lifecycle they’re navigating. These concerns extend beyond the potential for delayed timelines or ...

Digital-first continues to accelerate, along with the creation of customer data. As such, it’s essential for companies to implement these data best practices. The pandemic has pushed companies to ...

The pharmaceutical industry’s approach to data integrity has been historically manual, leveraging physical documentation and potentially unreliable paper-based ...

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. GenAI is also making a splash in software development and mobile applications. In fact, due ...

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.

Winners include organizations using trusted data for AI-powered climate risk assessment, advancing sustainability reporting, and giving underserved communities access to vital services "Trusted data ...