Databricks Ontology: Giving Enterprise AI the Context It Needs

Data can be technically correct — yet still mean different things to different teams. That's where ontology becomes powerful.

Databricks' Genie Ontology creates a business-aware map of your organization by connecting business terms, definitions, relationships, metrics, and knowledge across enterprise data. It is designed to help Genie deliver more accurate, context-aware answers.

A simple example: insurance claims

Imagine three teams using the same business concept:

• Claims team: Policy ID
• Finance team: Policy Number
• Underwriting team: Policy No.

Technically, these may point to the same business entity — but without shared context, analytics and AI systems can interpret them inconsistently.

With an ontology, the organization can establish:

… along with the business definitions, relationships, and trusted sources behind those concepts.

Now an AI assistant doesn't just see columns and tables. It understands the business context behind them.

Why this matters

• More consistent business definitions
• Better context for AI & GenAI
• More trustworthy analytics
• Faster data discovery
• Stronger alignment between business and data teams
• A foundation for context-aware enterprise agents

The bigger shift is this:

At Karsient, we see ontology as an important step toward building enterprise data platforms where AI doesn't simply query data — it understands how the business works.

Turn your data into intelligence. With context.