#data-management

#data-management

Modern AI needs more than raw data. It needs context that evolves as new sources appear and applications multiply. This context is reflected in four practical capabilities essential for any robust metadata infrastructure: discover, understand, trust, and use. Discover means navigating billions of objects without tedious manual work. A modern metadata system automates metadata harvesting across diverse data stores, lakes, and third-party databases.

"I can look across our different functions, pull up the red threads as and when I see them, and find commonality in processes."

"Contracts really are how businesses run. They're the lifeblood of a business - and they contain a lot of valuable data that often goes unnoticed or not tracked or not acted upon."

Oracle's advanced database, cloud and AI solutions deliver unmatched speed, security, and scalability - core capabilities for transforming how government manages and secures sensitive data.

Ordnance Survey is seeking a tech supplier for the National Underground Asset Register, which aims to manage data from utilities companies to prevent damage to subterranean infrastructure, costing £2.4 billion annually.

The arrival of truly intelligent, always-on, AI-native revenue engines is dismantling the way we've structured go-to-market motions for 20 years. This shift suggests a need for businesses to embrace AI-driven technologies to remain competitive.

The Rubin Observatory released its first images, showcasing vast star fields with a massive field of view and deep vision, marking a significant advancement in astronomical observations.

EHRs enhance patient-centered care by facilitating better communication and coordination among healthcare providers, ensuring swift access to essential medical information.

AI Factory simplifies this process, separating the infrastructures where needed and making it possible to do all of the AI workstream, or at least the most expensive part of it, on premises.

LinkedIn introduces Northguard, a log storage system overcoming Kafka's challenges by offering scalable architecture and seamless integration, enabling greater efficiency in data management.

"Top web [RAG] agents still only succeed 25% of the time, which is unacceptable in real software. Developers should focus on writing clear business logic."

"Our mixed IT ecosystem was hampering our ability to grow," Sandoval says.

Many charities mistakenly send standard messages to all donors, forgetting that personalizing communication can enhance engagement and foster meaningful connections.

This little piece of tech has really saved me from having to delete files I'd rather keep, just to make room for new video clips.

A factory reset will delete all user profiles, game downloads, and non-cloud save data from your Nintendo Switch 2, ensuring a clean slate.

I try to make change detection a first-class part of the pipeline: Hashes of source content, Timestamps or version numbers, Diffing at the chunk or field level.

Once live, WhatsApp will let users log out while choosing to erase all data or keep preferences, catering to those needing a temporary break.

Understanding the different systems of P2P, distributed, and decentralized networks is essential for knowing data and fund management.

Excel's drop-down lists significantly enhance productivity by reducing typing errors, maintaining organization, and enabling quick data entry for managing tasks effectively.

VA, like many other agencies across the federal government, has faced challenges overseeing its software licenses in recent years.

The UKRI must overcome ongoing challenges such as a lack of coordinated direction from government and inefficient data systems to improve funding assurance.

Rather than embark on large-scale AI implementations, start with smaller, controlled pilot projects tailored to well-scoped use cases.