Core Concepts
The main Stackless objects and how they fit together.
The short version
Stackless turns source data into trusted analytical outputs through a chain of governed objects:
Sources -> Warehouse Tables -> Transformation Models -> Semantic Models -> Dashboards and Agent Artifacts
The Agent can work across that chain, but each object has a different purpose.
[picture 1. Concept map from sources to artifacts and dashboards]
Source
A source is an upstream system Stackless reads from. Examples include commerce platforms, CRM systems, accounting tools, ad platforms, databases, spreadsheets, files, and APIs.
Source data is usually raw or lightly normalized. It is valuable, but it is not always ready for reporting because names, grains, IDs, time zones, and business rules may differ by system.
Warehouse table
A warehouse table is where source or modeled data physically lives. Many warehouse tables are technical assets. You may see them in the Catalog, but most business dashboards should not point directly at raw warehouse tables.
Transformation Model
A Transformation Model is a managed dbt-backed dataset. It defines how raw or intermediate data becomes a cleaner dataset. Transformations can:
- Select and rename fields.
- Cast data types.
- Join sources.
- Deduplicate records.
- Flatten nested JSON.
- Aggregate facts to a stable grain.
- Pivot or unpivot data into the shape reporting needs.
- Add tests such as uniqueness, not-null checks, and accepted values.
Published Transformation Models become reusable inputs for Semantic Models, dashboards, and future transformations.
Semantic Model
A Semantic Model gives business meaning to a table or transformation. It defines:
- Measures such as revenue, orders, margin, active customers, or conversion rate.
- Dimensions such as date, location, channel, product, customer segment, or campaign.
- Joins between models.
- Human-readable titles and descriptions.
The most reliable pattern is to build Semantic Models on top of published Transformation Models, because the transformation layer holds the cleaning and business logic.
Dashboard
A dashboard is a persistent analytical page. Dashboards can include KPIs, charts, tables, tabs, filters, and scheduled exports. Stackless supports private drafts and published dashboards. Published dashboards are the recurring reporting layer your team returns to.
Artifact
An artifact is a saved output created or attached inside an Agent conversation. Stackless supports:
- Briefs.
- Finding cards.
- Table artifacts.
- Chart cards.
- Draft dashboards.
Artifacts are useful when a result should survive the chat response. They can be reviewed, exported, reused, attached to other conversations, and promoted into dashboards where appropriate.
Catalog
The Catalog is the searchable inventory of visible Stackless assets. It helps users and the Agent answer questions like:
- What data exists?
- Which model defines this metric?
- What upstream sources feed this dashboard?
- What downstream dashboards depend on this transformation?
Monitor
Monitor shows operational state for recurring Stackless work: jobs, runs, refreshes, failures, and recent history. Use it when a dashboard is stale, a model did not refresh, or a scheduled export did not run.
Role and access
Stackless access is role-based. Your role controls which dashboards, source schemas, catalog assets, and Agent actions are available. The Agent follows those permissions when searching, querying, and building.