Product lifecycle management (PLM) is a discipline for managing the lifecycle of a product, encompassing processes and software systems for tracking and improving every development phase, from ...

This approach is repeatable, minimizes dependence on manual controls, harnesses technology and AI for data management and integrates seamlessly into the digital product development process.

To discuss the effectiveness of PDM systems, we must first understand how "painful" CAE simulation data management can be.

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

AI-enabled data collection and management can reduce the time and effort required for clinical trials, accelerate the drug development process, and help companies get new treatments to market more ...

Customer Data Management (CDM) is defined as an enterprise process by which customer data is gathered, stored, updated, accessed and analyzed.

See how SAS Data Management solutions can help you solve key business challenges and accelerate your business.

This framework prioritizes proactive risk management and governance, transparency, and accountability across the AI life cycle. Additionally, it emphasizes anchoring AI development in human rights and ...