Learn what overfitting is, how it impacts data models, and effective strategies to prevent it, such as cross-validation and simplification.

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 ...

At its heart, data modeling is about understanding how data flows through a system. Just as a map can help us understand a city’s layout, data modeling can help us understand the complexities of a ...

Vector databases and search aren’t new, but vectorization is essential for generative AI and working with LLMs. Here's what you need to know. One of my first projects as a software developer was ...

Enterprises are creating huge amounts of data and it is being generated, stored, accessed, and analyzed everywhere – in core datacenters, in the cloud distributed among various providers, at the edge, ...

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 ...

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

ManureDB, a publicly available database, houses U.S. manure and organic amendment data from multiple laboratory sources. The ManureDB website allows for simple summaries, data visualizations and data ...