Data engineering is the process that makes it usable. It involves moving, cleaning, and organizing. This creates the foundation for BI and analytics. The goal is to replace guesswork with facts. That ...

With AI ambitions outpacing data readiness, CIOs must renovate their data strategies to create unified, AI-ready foundations ...

The future of the field isn't less engineering but better engineering, where people focus on design, integrity and impact ...

Ensuring that verification platforms can scale with industry demands and support new use cases as they emerge.

Artificial intelligence has dramatically expanded the toolkit available for reverse engineering, and in-house counsel might ...

Corporate leaders are racing to hire artificial intelligence talent, convinced that a few high-profile specialists can ...

Overview Cloud analytics platforms in 2025 are AI-native, enabling faster insights through automation, natural language ...

AI initiatives don’t stall because models aren’t good enough, but because data architecture lags the requirements of agentic systems.

Cloud bills rising? Here's how AI-powered rightsizing, predictive autoscaling and real-time anomaly detection can lower spend ...

New types of sensors can generate environmental data in real time using a range of tools, including flexible, printed ICs and ...

The modern healthcare data stack unifies patient data for real-time clinical and operational insights to improve decision-making in health systems.

Malaysia is racing to attract more data centres, including hyperscale facilities to power AI, cloud services and streaming.