While the component supply crunch remains the headline, this also underscores that AI infrastructure architectures need to adapt.

Forbes contributors publish independent expert analyses and insights. Robert, founder of KramerERP, covers AI, ERP, SCM, data and security. Just like 2023, 2024 was a dynamic year for enterprise data ...

Data modeling is the process of defining datapoints and struc­tures at a detailed or abstract level to communicate information about the data shape, content, and relationships to target audiences.

If you're wondering whether data modeling is still relevant in today's fast-paced, data-driven world, this white paper is for you. You'll discover how data modeling can help you overcome challenges ...

Databases will soon be capable of monitoring their own health, identifying bottlenecks, adjusting configurations, and even rerouting traffic in real time. Generative AI has already had a profound ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

Integrating AI into chip workflows is pushing companies to overhaul their data management strategies, shifting from passive storage to active, structured, and machine-readable systems. As training and ...

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...

Data models are used to represent real-world entities, but they often have limitations. Avoid these common data modeling mistakes to keep data integrity. Data modeling is the process through which we ...