New capabilities shift enterprises from app-centric to data-centric model with enhanced governance and AI-ready intelligence ...

Enterprises racing to deploy generative AI often focus on models. In practice, outcomes depend on how well organizations ...

The evolution of data architecture is accelerating. In 2025, 85% of DBTA subscribers reported plans to modernize their data platforms—driven largely by the explosive rise of GenAI and large language ...

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 ...

Every data modernization effort starts with a blueprint. The architecture looks clean. The data flows are defined. The platform choice is justified. Whether it is a data warehouse, a data lake or a ...

With access to many different types of data fabrics, companies big and small can use them to provide AI agents with wide ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

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 ...

The US Food and Drug Administration (FDA) recommends that trading partners use the semi-distributed model to trace drug products though the drug distribution chain because of this model’s flexibility ...

Large language models like ChatGPT and Llama-2 are notorious for their extensive memory and computational demands, making them costly to run. Trimming even a small fraction of their size can lead to ...