Data Management

Almost every AI project reaches a point where the pilot works and the demo is convincing. The agent does what you hoped it would. Yet the transition to ...

From race-day strategy to new engine development, and from fan engagement to talent scouting, Oracle plays a key role across all these areas at the Oracle Red ...

Almost everyone has tried it by now. You open a generic AI tool and ask it to summarize a report or draft an email. The result is genuinely impressive. But as ...

Why metadata and data definitions are the silent dealbreakers of data-driven working. Data-driven working often gets bogged down by culture, ownership, and ...

A wrong decision can cost money. Most organizations know this. But what is often forgotten is that making no decision at all can sometimes be even more ...

Standards always sound like a great idea. One language. One structure. One way to exchange product data. Less confusion, fewer emails, cleaner processes, ...

AI is all the rage, says Maarten van den Outenaar. In the long run, the hype may pay off, but for now he sees a productivity paradox: “The intriguing reality ...

Most AI initiatives never make it past the experimental phase, leaving organizations stuck in impressive pilots that fail to yield tangible results. Frans ...

Discussions about digital sovereignty often center on what isn't possible — the CLOUD Act, dependencies, and the fallout if a vendor cuts off access. These are ...

Everyone wants to talk about AI. Fine. AI is useful, exciting, and it will change a lot. But in commerce, the most important file of the week is often still an ...