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 ...

If your AI feels slow, expensive or risky, the problem isn’t the models — it’s the data, and cognitive data architecture is ...

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

SAN MATEO, Calif.--(BUSINESS WIRE)--Hammerspace, the company orchestrating the Next Data Cycle, today released the data architecture being used for training inference for Large Language Models (LLMs) ...

Healthcare organizations are awash in data. But not every health system is able to utilize its data in ways that yield actionable insights or opportunities for performance improvement. Without a clear ...

Organizations often force the DBA to take on the job of data modeling. That does not mean that DBAs are well-trained in data modeling, nor does it mean that DBAs are best suited to take on this task.

In an era where data is a strategic asset, organizations often falter not because they lack data—but because their architecture doesn’t scale with their needs. Leaders must design data ecosystems that ...

The Covid-19 pandemic reminded us that everyday life is full of interdependencies. The data models and logic for tracking the progress of the pandemic, understanding its spread in the population, ...

A headless data architecture means no longer having to coordinate multiple copies of data and being free to use whatever processing or query engine is most suitable for the job. Here’s how it works.

Data modeling tools play an important role in business, representing how data flows through an organization. It’s important for businesses to understand what the best data modeling tools are across ...