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Data Infrastructure Types

Data infrastructure types represent traditional data warehouse, BI, and pipeline assets. These are the most common product types in Qarion, typically created automatically by connector syncs.

Available Types

Table

The default product type. Represents a database table, view, or materialized view.

  • Icon: Table · Color: #3b82f6 (blue)
  • Created by: dbt sync, database scrapers, or manually
  • System variants: Scraped Table, dbt Model, dbt Source, View, Ephemeral

Tables get the full feature set including schema with column-level metadata, data profiling, quality checks, and environment diff.

Dashboard

Analytics dashboards and reports from BI tools.

  • Icon: BarChart3 · Color: #8b5cf6 (purple)
  • Created by: BI connectors (Superset, Metabase, Looker, Tableau, Power BI) or manually
  • System variants: BI Dashboard, BI Chart

Dashboards support lineage tracking back to their source warehouse tables, enabling impact analysis when upstream data changes.

API

REST or GraphQL API endpoints exposing data.

  • Icon: Code · Color: #10b981 (green)
  • Created by: Manual registration

API products track endpoint metadata, versioning, and consumer contracts.

Data Stream

Real-time data streams, Kafka topics, or event feeds.

  • Icon: Zap · Color: #ef4444 (red)
  • Created by: Manual registration

Stream products support freshness SLAs and real-time quality monitoring.

File/Dataset

Flat files and structured datasets (CSV, Parquet, JSON, etc.).

  • Icon: File · Color: #6366f1 (indigo)
  • Created by: Manual registration

File/Dataset products combine the standard schema tab with the File Metadata tab, bridging structured and file-based metadata.

Notebook

Jupyter notebooks, R Markdown, or other analysis notebooks.

  • Icon: BookOpen · Color: #ec4899 (pink)
  • Created by: Manual registration

Notebooks track the analytical code and its data dependencies via lineage.

Available Tabs & Features

All data infrastructure types share the universal feature set:

TabDescription
OverviewRich markdown description, ownership, stats, freshness indicator
SchemaColumns, data types, PK/FK/nullable flags, inline-editable descriptions
ProfileColumn-level statistics (null %, distinct count, min/max, histograms)
Env DiffCross-environment schema comparison
Sourcedbt SQL, view DDL, or code snippet (when available)
Quality HealthAutomated checks, scores, trends, and execution history
IssuesLinked quality tickets with Kanban tracking
GovernancePolicy compliance, governance role assignments
ContractsSLA agreements and compliance monitoring
Change RequestsFormal change proposals with impact analysis
RiskRisk assessment questionnaires and scoring
VersionsRelease history with Git tag linking
SnapshotsHistorical metadata snapshots
Use CasesRegistered business use cases
GlossaryLinked business glossary terms
LineageInteractive upstream/downstream dependency graph
RefreshesData refresh history and scheduling
UsageConsumption analytics and popularity metrics
InsightsAI-generated data insights
ChatterTeam conversations and @mentions
AttachmentsReference documents and files
AccessPermission management (when linked to a source system)

System Type Mapping

When connectors sync metadata, they assign specific system types:

ConnectorSystem Type Assigned
Database scraperScraped Table
dbt (table materialization)Table
dbt (view materialization)View
dbt (ephemeral)Ephemeral
dbt (other)dbt Model
dbt (source)dbt Source
BI connectorsBI Dashboard or BI Chart

Users can change the type at any time through the Edit Product modal. Manual edits are tracked in the user_edited_fields list, so subsequent syncs won't overwrite the user's choice.