Posts tagged "business-ontology"
- From Data Vault to an AI-ready silver layer: same build order
Vault steps build an AI-ready silver layer's meaning layer: unhashed business keys, persistent staging audit, data contract, not point-in-time or bridge tables.
- You don't need to unlearn Data Vault to model for AI agents
In data modeling for AI, Ensemble Logical Modeling becomes a business ontology: the meaning layer of an AI-ready data architecture. It doesn't need the tables.
- AI for modeling, or modeling for AI?
AI-assisted data modeling guesses. Data modeling for AI writes business context for AI once as metadata in a context layer: AI proposes, a person approves.
- Who is the data model for?
A data model for AI isn't a new table shape. The model did two jobs: a diagram for people and a build instruction for machines. AI retires the second.
- Seven steps to a meaning layer
Where to start on a silver layer an AI agent can read: one business area, seven steps in order, and a check you can run at the end of each one.
- What a hub becomes when an agent reads the model
Data Vault and third normal form beside AIMS, construct by construct: where each hub, link and same-as link goes when an agent reads the model.
- Every method stops at the concept
Silver layer modeling methods say which business thing a table is about. Only the costliest says what each column means, and that's where AI answers break.
- Integration by exception
Silver layer integration is the last step, not an entry fee. AIMS adds a shared key and a golden record only when a business requirement needs one.
- What the agent reads
An AI agent's answer is only as good as what it reads, and every platform keeps its semantic layer for AI agents inside its own walls. Write the meaning first.
- You don't need Data Vault anymore
You don't need Data Vault or third normal form in your silver layer. AI reads business meaning from an ontology: the deciding stays, the rebuilding goes.
- Modeling for Machines That Can Read
Once a machine can read a sentence about your business, every benefit Data Vault's tables bought has a cheaper home. That's data modeling for AI.
- The economics of meaning flipped
Stated meaning now costs a sentence, not a table. What an ontology adds to AI accuracy on the benchmarks, and where the AI still has to stop.
- You already own the stack
You already own the lakehouse, storage, and orchestration. The missing layer is data warehouse automation: business meaning in, Data Vault and workflows out.
- The Medallion Three-Body Problem
Without an agreed business model, bronze, silver, and gold drift apart: three suns pulling the medallion architecture into a three-body problem.
- Your Database Is Not Your Business
AI can infer a semantic layer from your technical exhaust. It cannot define your business ontology. Why a system of record is not a system of meaning.
- No Human, No Loop
Human in the loop puts a person at the end of an AI process as a checkpoint. In DeltaVault the human starts the loop, so there is no loop without one.