EVOLVE, an agentic framework that autonomously optimizes AI training data, model architectures, and learning algorithms — ...

As organizations look to build out more complex digital frameworks, breaking down data silos is essential. But there’s a catch: As data analysts, data scientists and others work across various groups, ...

IEEE research highlights multi-model databases outperform single-model systems, reducing AI costs, latency, and schema issues ...

Google's Agentic Data Cloud rewires BigQuery, its data catalog and pipeline tooling around autonomous AI agents — not the ...

Data foundations were never designed to support intelligent workloads at scale, but unified data lakehouse architecture might ...

Generative artificial intelligence disrupted the enterprise in 2023 and is now a must-have consideration in 2024 plans. With this in mind, technical professionals must strive to enhance and modernize ...

Enterprise data platforms become harder to scale as data volumes grow. Organisations then tend to use multiple tools to fix, ...

AI may be the visible goal, but data architecture is what determines whether that goal can actually be achieved.

In the first quarter of 2025, nearly 60% of DBTA subscribers told us they were actively researching GenAI with LLMs, including RAG and knowledge graphs. On top of this, when asked which technologies ...

Data decay, dark funnel gaps, and identity issues limit visibility. Learn how to turn scattered signals into a connected, ...

Architecting modern applications is a tough job, and architecting a solid data model for modern applications is one of the toughest, yet most important, parts of a modern application architecture.