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coginiti.co @coginiti.co · 24/09/2026

"Semantic layers are too rigid for AI" The opposite. The more probabilistic the interface, the more it needs a deterministic contract underneath. Without one, the same question gives different answers by prompt wording or model version. coginiti.co/blog/semanti...

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coginiti.co @coginiti.co · 22/09/2026

"Nobody agrees on the definitions anyway." That's the point. Disagreement is the reason semantic layers exist. Without one, four teams' definitions of "customer" get encoded silently into dashboards and queries. With one, disagreement becomes a governed decision. coginiti.co/blog/semanti...

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coginiti.co @coginiti.co · 17/09/2026

"Semantic layers are only useful after the data is perfect." The perfection trap. Nobody has perfect data, and waiting for it means waiting forever. The semantic layer is part of how you make data usable. Start with the metrics that matter most, not day-one everything. coginiti.co/blog/semanti...

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coginiti.co @coginiti.co · 15/09/2026

"We can solve this with prompt engineering." A prompt that says "use approved revenue" is not a governed revenue measure enforced in the execution path. Prompts are hard to audit, version, and test. Prompts guide behavior. A semantic layer governs meaning. coginiti.co/blog/semanti...

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coginiti.co @coginiti.co · 10/09/2026

"Governance kills agent autonomy." A self-driving car still needs traffic laws and lane markings. Let agents explore freely. But when one answers an enterprise metric question, it shouldn't invent the definition. Autonomy to explore, governed semantics to answer. coginiti.co/blog/semanti...

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coginiti.co @coginiti.co · 08/09/2026

Semantic model. Ontology. Context engineering. Three terms used interchangeably by people selling three different things. Richard Hall sorts them out at Big Data LDN. AI Context Theatre, Thu 24 Sept, 10:40. What each one does, and when it doesn't. #BigDataLDN

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coginiti.co @coginiti.co · 08/09/2026

"It's just an old BI idea with new marketing." The idea is decades old. That's a strength. What changed is the number of consumers: agents, notebooks, workflows, embedded apps, decision systems. AI multiplied the systems that need governed access to meaning. coginiti.co/blog/semanti...

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coginiti.co @coginiti.co · 03/09/2026

For 20 years the semantic layer was a BI convenience. Friendly names so nobody had to remember which table held revenue. That was built for humans clicking dashboards. The user has changed. Matthew Mullins, Big Data LDN, Wed 23 Sept 10:40, Lightning Talks Theatre. #BigDataLDN

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coginiti.co @coginiti.co · 03/09/2026

"Semantic layers hide the underlying data." A good one does the opposite: exposes definitions, shows the generated SQL, provides lineage, keeps version history When an agent answers, you should see the metric, the filters, and the query it ran. Explicit and inspectable coginiti.co/blog/semanti...

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coginiti.co @coginiti.co · 01/09/2026

We're exhibiting at Big Data LDN 2026. 23-24 Sept, Olympia London, Stand E34. Two talks: Matthew Mullins on the semantic layer as the control point for AI agents (Wed), Richard Hall on the context stack (Thu). Free tickets below. #BigDataLDN

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coginiti.co @coginiti.co · 01/09/2026

"Semantic layers are just another abstraction." Everything in analytics is an abstraction. Tables abstract files. Views abstract queries. SQL abstracts execution. The question is whether it captures the right contract. A semantic layer abstracts business meaning. coginiti.co/blog/semanti...

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coginiti.co @coginiti.co · 25/08/2026

"The LLM can just retrieve the documentation." Docs explains revenue in prose. The model still has to translate prose into query logic, and that translation is where drift enters: right definition, wrong table, wrong grain. coginiti.co/blog/semanti...

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coginiti.co @coginiti.co · 20/08/2026

"Ontologies and knowledge graphs will replace semantic layers." They describe how the business thinks about itself. Powerful, and complementary. But an ontology describes the business. A semantic layer has to answer questions against the data. coginiti.co/blog/semanti...

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coginiti.co @coginiti.co · 18/08/2026

"Semantic layers are only for business users." A leftover from the self-service BI era. Analysts, data engineers, analytics engineers, data scientists, applications, and agents all consume analytical meaning. Semantic layers are for every consumer, including software. coginiti.co/blog/semanti...

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coginiti.co @coginiti.co · 13/08/2026

"Semantic layers are too hard to maintain." You're already maintaining semantic logic, scattered across snippets, stored procs, notebooks, and Slack. The layer doesn't add the burden. It makes it visible. Maintain it explicitly, or let it sprawl. coginiti.co/blog/semanti...

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coginiti.co @coginiti.co · 11/08/2026

"Semantic layers are brittle because the business changes." The business changing is the reason to govern definitions, not skip them. The alternative to governed change is silent drift across queries, dashboards, notebooks, and prompts. Pick which you'd rather have. coginiti.co/blog/semanti...

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coginiti.co @coginiti.co · 04/08/2026

"Semantic layers can't handle complex analytics." They aren't meant to replace SQL, modeling, or exploration. But complex work still needs stable definitions: which customers are active, what counts as revenue. Not a cage. The governed foundation you build on. coginiti.co/blog/semanti...

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coginiti.co @coginiti.co · 30/07/2026

"Semantic layers are just metric stores." A metric without its business structure is incomplete. "Revenue" by what? Customer? Region? Recognized date? At what grain? Through which join path? Semantic layers model the structure, not just the formula. coginiti.co/blog/semanti...

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coginiti.co @coginiti.co · 28/07/2026

"Semantic layers slow analysts down." Bad governance does. A good semantic layer speeds people up: no rediscovering the approved revenue calc, no reverse engineering joins, no asking five people which churn is correct. Restriction slows. Reuse accelerates. coginiti.co/blog/semanti...

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coginiti.co @coginiti.co · 23/07/2026

"BI tools already have semantic layers." They do, and they were built to govern dashboards inside one tool. Governed meaning now has to serve SQL analysts, data products, APIs, and agents. BI semantics can't reach all of that. Enterprise semantics have to. coginiti.co/blog/semanti...

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coginiti.co @coginiti.co · 21/07/2026

"The warehouse should own the semantic layer." Fine if you live inside one platform. Most enterprises run many, plus BI tools, notebooks, APIs, and agents. Trap semantics in one warehouse and consistency becomes lock-in. Enterprise meaning has to be portable. coginiti.co/blog/semanti...

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coginiti.co @coginiti.co · 16/07/2026

"The data catalog is enough context." A catalog helps you discover and understand data. It does not define the approved measure, its grain, its join paths, or the executable logic to answer consistently. Discovery is not governance of execution. coginiti.co/blog/semanti...

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coginiti.co @coginiti.co · 14/07/2026

"Agents can infer the business logic from the schema." Schemas encode physical structure, not meaning. A table named orders won't tell an agent whether cancelled orders count as revenue. Metadata helps it reason. A semantic layer tells it what you agreed things mean. coginiti.co/blog/semanti...

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coginiti.co @coginiti.co · 10/07/2026

the scary part is how good the wrong answer looks.

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coginiti.co @coginiti.co · 03/07/2026

Documentation was fine when humans were the consumers, but agents don't ask clarifying questions. #databs

The four stages of semantic enlightenment:

SQL pasted into every dashboard
Views with comments nobody reads
Metric definitions in a YAML file
Semantics your agents can actually execute against

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coginiti.co @coginiti.co · 26/06/2026

This is the conversation happening in a lot of AI analytics pilots right now. The demo works, the SQL is syntactically perfect, but then someone checks the number against the board deck only to discover the model invented its own churn definition and reported it with confidence.

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coginiti.co @coginiti.co · 19/06/2026

the AI agent, given full warehouse access, scrolling past your governed metric definitions to write a query against rev_amt_v2_final_OLD it's not bad at SQL. it's bad at knowing which of your six revenue columns is real. nothing in the schema tells it.

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coginiti.co @coginiti.co · 17/04/2026

Valerie Kwiatkowski just joined Coginiti as Director of Partnerships. Former CIO Americas at APM Terminals (Maersk), EVP IT at SDCCU, Managing Partner at StrataFusion, and Associate Partner at IBM Global Services. She's governed data at enterprise scale. Perfect fit.

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coginiti.co @coginiti.co · 29/10/2024

We are proud to share that we have achieved three Google Cloud Ready designations for AlloyDB, CloudSQL, and Regulated & Sovereignty Solutions. Extending our ability to provide one door to data and help our customers run in compliance with programs such as FedRAMP or CJIS. bit.ly/CoginitiClou...

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