The most important test of a data architecture is not how it performs on day one. It is how it behaves when the business ...

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 ...

Becoming truly data-driven requires more than adopting new tools-it demands clear alignment between business goals and data architecture. At Data Summit 2026, John O'Brien, principal advisor and ...

Effective data modeling enables value creation, efficiency gains, risk reduction, and strategic alignment in an environment of uncertainty and disruption. At Data Summit 2026, Pascal ...

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 ...

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 ...

For R&D leaders evaluating AI investments, I’d offer one piece of advice: Before spending more on models, look hard at your ...

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 ...

As LLMs hit the limits of scale and cost, specialized SLMs are emerging as the faster, cheaper, and more private workhorse ...