The Context Layer is the foundation of ClarityQ. It’s a structured model that bridges the gap between your raw database tables and the business concepts your team uses every day — metrics, events, segments, dimensions, and more.
Without a Context Layer, ClarityQ would only see tables and columns. With it, ClarityQ understands what “daily active users” means in your organization, how “churn” is calculated, which events matter, and how your data relates to your business logic.
The Context Layer is a prerequisite for using Ask Anything. The more complete and accurate your context, the better ClarityQ’s answers will be.
The Five Components
The Context Layer is made up of five components, each serving a distinct purpose:
Table Catalog
The Table Catalog is a live inventory of the tables and columns in your data warehouse. ClarityQ automatically discovers your schema and keeps it up to date through daily discovery jobs. From here, you build entities that feed into the Semantic Catalog.
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Event Catalog
The Event Catalog maps your product’s tracked events, parameters, and user properties. Events are synced to the Semantic Catalog, where they become queryable business concepts. A built-in Missing Description Wizard helps you fill in gaps across your catalog.
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Semantic Catalog
The Semantic Catalog is where business logic lives. It contains the components that define how your organization measures and analyzes data:
- Entities — Core business objects that represent your data sources (e.g., users, orders, sessions)
- Dimensions — Properties used to filter and group data (e.g., country, platform, plan type)
- Metrics — Business KPIs and calculations (e.g., revenue, retention rate, conversion)
- Features — Tracked product behaviors promoted from the Event Catalog (e.g.,
signup_completed, purchase_made), with their event parameters available as dimensions
- Segments — Reusable cohort definitions (e.g., power users, churned customers)
ClarityQ’s AI agent actively helps build these components using your existing definitions and data structure.
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Skills
Skills are reusable analysis methodologies encoded as step-by-step instructions. When invoked, the AI agent follows them precisely — asking clarifying questions, executing the analysis, and validating results. Skills ensure complex workflows run consistently every time.
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Memory
Memory is persistent context that ClarityQ retains across conversations. It operates at two levels — personal and product — and stores business rules, naming conventions, and domain knowledge that doesn’t live in your database.
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How the Components Connect
Data Warehouse
↓
Table Catalog ──→ Entities ──→ Semantic Catalog
↓ ↑
Event Catalog ─── Sync ───────────┘
↑
Memory ───── Context ─────────────┘
↑
Skills ───── Workflows ───────────┘
↓
Ask Anything
