Forbes contributors publish independent expert analyses and insights. Gary Drenik is a writer covering AI, analytics and innovation. We are almost three years past the fanfare of ChatGPT’s big debut ...

Clinical data management is entering a new phase as AI automates EDC build, shortens timelines, and enables data teams to focus on quality.

Scaling agentic AI means trusting your data - here's what most CDOs are investing in ...

Modern enterprise data platforms operate at a petabyte scale, ingest fully unstructured sources, and evolve constantly. In such environments, rule-based data quality systems fail to keep pace. They ...

Let's discuss why AI-powered data management is becoming essential in industrial automation and how organizations can build it successfully.

Data quality management efforts — tied to disrupting innovations, rapid market shifts and regulation pressures — will continue to grow in 2023 and take on a more dominant role in the data management ...

Data is essential for the success of any artificial intelligence (AI) project, but understanding what makes data beneficial—or harmful—for AI is crucial. At a high level, machine learning (ML) and AI ...

SAN FRANCISCO--(BUSINESS WIRE)--Monte Carlo, the data and AI observability company, today announced a series of product enhancements and new capabilities at its annual IMPACT Data Observability Summit ...

DQM is becoming a core capability for organizations that need to make better decisions with data. What are the responsibilities of different roles in DQM? Image: WrightStudio/Adobe Stock Data quality ...

Test data management (TDM) is a crucial practice for ensuring compliant data and providing uniformity to test data. In the same way testing environments and data models are continuously evolving, test ...