About
“Hybrid by default” is the normal situation for most companies: SaaS, operational databases, APIs, multiple clouds, legacy platforms. And even though the intention is to simplify, it often leads to chaotic data consumption that goes everywhere.
Trusting and accessing the right data becomes a challenge, especially when there is no consensus on what the data actually means. FTE, Customer, Revenue, Risk, Order… definitions drift across domains and tools, and you end up with duplicated pipelines, fragile integrations, and endless reconciliation.
Let’s challenge that. With AI now sitting on everyone’s agenda, the need for basic data sanity is not optional anymore. If teams want to scale analytics, automation, and AI safely, we need a way to consume data across the estate while keeping meaning consistent. We need to decide where semantics live, how they’re maintained, how governance and security travel with the data, and when caching is a smart optimisation versus just another copy that nobody owns.
So how do we enable cross-estate consumption that scales? Do we keep rebuilding the same logic five times? Do we force every team to learn a new dialect for every platform? Or do we finally agree on a shared semantic contract and make it usable across the enterprise?
