What was once seen as an operational inefficiency is now a growth problem. Companies that cannot trust their data struggle to ...

The data purgatory hits major technology initiatives like AI projects when obstacles are created by data accuracy, quality, and accessibility. Fast Company has put a spotlight on the make-or-break ...

PHILADELPHIA--(BUSINESS WIRE)--Qlik®, a global leader in data integration, data quality, analytics, and artificial intelligence (AI), today released a new survey of 500 professionals working with AI ...

This content has been created by the Finextra editorial team with inputs from subject matter experts at the funding sponsor. Joining the FinextraTV virtual studio, Andrew Colombi, Co-Founder & CTO, ...

As data estates have grown more complex, enterprises have invested in observability tools that monitor pipelines, track ...

Anomalo Inc. today launched a new tool that aims to help enterprises keep check on the unstructured information that’s becoming critical to the success of artificial intelligence systems. The ...

A global survey by Dun & Bradstreet highlights rising cyber threats and data quality issues in financial services, impacting AI adoption and decision-making. Despite increased risk mitigation spending ...

Data observability firm Monte Carlo Data Inc. is turning its attention to unstructured information, introducing a new capability that will allow enterprises to monitor the enormous volumes of text, ...

As clinical development grows increasingly complex, the industry has recognized the critical role of centralized processes and risk‑based monitoring in ensuring high‑quality, reliable data. Regulatory ...

Data lays the foundation of modern B2B operations. It shapes everything starting from routine workflows to long-term strategic decisions. Yet, managing data quality remains the most persistent, yet ...

Concerns about bots answering online surveys are exaggerated, but a new threat is emerging in artificial intelligence agents.

Synthetic data is generated as a replacement for real data that is considered poor quality, fragmented, siloed, sensitive or otherwise unusable for AI training in the enterprise. However, synthetic ...