In this Q&A from the 2025 Veeva R&D and Quality Summit, Ibrahim Kamstrup-Akkaoui, vice president of data systems innovation at Novo Nordisk, discusses simplifying system use through the company’s ...

One key challenge in AI implementation is fragmented data across departments, which slows decision-making and reduces the effectiveness of data use.

Data integration: AI can be used to automate the integration development process, by recommending or deploying repetitive integration flows, such as source-to-target mappings.

Discover how to harness AI in software development while minimizing risks. Learn strategies for secure coding practices, managing AI-generated code risks, and implementing effective security measures.

Informatica (NYSE: INFA), an AI-powered enterprise cloud data management leader, today announced data management innovations designed to simplify and enhance ...

Bank of America’s DataConnect platform provides a range of data management capabilities designed to help users process and manage data throughout their business lifecycle. This environment provides an ...

DQM is a core capability for organizations that need to make better data decisions. What are the responsibilities of different roles in DQM?

OSF HealthCare implemented the vendor's provider data management technology, establishing it as the single source of truth for provider and location data. This involved creating a system-wide database ...

This article will discuss the significance of data analytics in modern retail operations and how data-driven decisions can enhance inventory management, pricing strategies and customer experience.

As the Army’s premier force enabling data-centric operations, ARCYBER is committed to executing the Army’s Data Management and Analytics Strategy. To su ...