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 ...

Time flies in the world of data analytics and artificial intelligence (AI). Seemingly every day, new technologies rise, new use cases emerge, and new frontiers unfurl themselves before a world that ...

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

Data modeling is the procedure of crafting a visual representation of an entire information system or portions of it in order to convey connections between data points and structures. The objective is ...

There’s always a worry that “agentic AI” means people step aside. The reality is sort of the opposite. Agents take on the minute-by-minute decision loops, but humans define the goals, priorities, ...

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 ...

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 ...

TiDB is a prime example of an intrinsically scalable and reliable distributed SQL database architecture. Here’s how it works. In the good old days, databases had a relatively simple job: help with the ...

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 ...