#data-movement

#data-movement

Galileo provides AI teams with tools to evaluate the quality of AI outputs, detect errors before they reach end users, and continuously improve the behavior of AI agents in production.

Automating Kubernetes workloads with Operators can provide the same level of functionality as DBaaS, while still avoiding lock-in to a specific provider.

S3 Files is built on Amazon EFS and automatically translates file system operations into S3 requests, allowing applications to work with S3 data without code changes.

There is a growing emphasis on database compliance today due to the stricter enforcement of compliance rules and regulations to safeguard user privacy. For example, GDPR fines can reach £17.5 million or 4% of annual global turnover (the higher of the two applies). Besides the direct monetary implications, companies also need to prioritize compliance to protect their brand reputation and achieve growth.

A future-proof IT infrastructure is often positioned as a universal solution that can withstand any change. However, such a solution does not exist. Nevertheless, future-proofing is an important concept for IT leaders navigating continuous technological developments and security risks, all while ensuring that daily business operations continue. The challenge is finding a balance between reactive problem solving and proactive planning, because overlooking a change can cost your organization. So, how do you successfully prepare for the future without that one-size-fits-all solution?

Developers have spent the past decade trying to forget databases exist. Not literally, of course. We still store petabytes. But for the average developer, the database became an implementation detail; an essential but staid utility layer we worked hard not to think about. We abstracted it behind object-relational mappers (ORM). We wrapped it in APIs. We stuffed semi-structured objects into columns and told ourselves it was flexible.

"If you look at the enterprise, there's just enormous enthusiasm to deploy AI, but the problem is that the infrastructure, the power, and the operational foundation that is required to run it just aren't there," Alex Bouzari, CEO of DDN, told The Register. "And so as a result, it pops up in the financial elements with IT projects getting delayed, the GPUs being underutilized, power costs going up. And so the economics, I think, for lots of organizations don't pencil out because of these challenges."

Unverified and low quality data generated by artificial intelligence (AI) models - often known as AI slop - is forcing more security leaders to look to zero-trust models for data governance, with 50% of organisations likely to start adopting such policies by 2028, according to Gartner's seers. Currently, large language models (LLMs) are typically trained on data scraped - with or without permission - from the world wide web and other sources including books, research papers, and code repositories.