Even as large language models have been making a splash with ChatGPT and its competitors, another incoming AI wave has been quietly emerging: large database models. Even as large language models have ...

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 ...

Back in the 1970s, the ANSI SPARC three-tiered model arose, foreshadowing a smooth intertwining of data and architectural design. The three tiers concept isolated the physical storage needs of data ...

It has been widely documented - data is growing at astronomical rates. The amount of data your organization has is less important than how the data is being used. Is data growth hindering your ...

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

Big data is less predictable than traditional data, and therefore requires special consideration when building models. Here are some things to keep in mind. Image: iStock/z_wei Data modeling is a ...

Distributed database consistency models form the backbone of reliable and high-performance systems in today’s interconnected digital landscape. These models define the guarantees provided by a ...

AI promises a smarter, faster, more efficient future, but beneath that optimism lies a quiet problem that’s getting worse: the data itself.

NoSQL entered the scene nearly six years ago as an alternative to traditional relational databases. The offerings from the major relational vendors couldn’t cut it in terms of the cost, scalability, ...