Table types

Table types define how tables behave in AnalyticsCreator and what role they play in the generated data warehouse structure.

Use this section to understand the available table types and choose the appropriate one for staging, historization, persistence, dimensional modeling, or Data Vault modeling.

Available Table Types

Import Table

Used to receive source data during import into the staging layer.

  • Entry point for source loading
  • Filled by generated workflows
  • Basis for downstream processing

Open reference

Historized Table

Used to store historized data with validity periods and change tracking.

  • Supports history over time
  • Typical basis for persistent staging
  • Common for SCD2-style processing

Open reference

Persisting Table

Used to materialize transformation results physically instead of keeping them only as views.

  • Improves performance for complex logic
  • Stores generated output physically
  • Maintained by generated procedures

Open reference

Dimension Table

Used to store descriptive business entities for dimensional modeling.

  • Typical star schema component
  • Contains descriptive attributes
  • Referenced by fact tables

Open reference

Externally Filled Table

Used when table content is populated outside the standard AnalyticsCreator-generated loading process.

  • Externally maintained data
  • Not filled by standard generated import logic
  • Useful for integration scenarios

Open reference

Fact Table

Used to store measurable business events and transactions in dimensional models.

  • Contains measures and foreign keys
  • Central table in star schemas
  • Supports analytical aggregation

Open reference

DataVault Hub

Used to store stable business keys in Data Vault models.

  • Represents core business entities
  • Key-centric structure
  • Foundation of hub-based modeling

Open reference

DataVault Link

Used to store relationships between business entities in Data Vault models.

  • Connects hubs
  • Represents business relationships
  • Supports scalable model design

Open reference

DataVault Satellite

Used to store descriptive and changing attributes in Data Vault models.

  • Contains contextual attributes
  • Often historized by design
  • Separated from business keys

Open reference

How to Choose a Table Type

  • Use Import Table for source ingestion into staging
  • Use Historized Table when changes over time must be tracked
  • Use Persisting Table when transformation results should be materialized physically
  • Use Dimension Table and Fact Table for dimensional modeling
  • Use Externally Filled Table when data is maintained outside the generated loading process
  • Use DataVault Hub, DataVault Link, and DataVault Satellite for Data Vault models

Key Takeaway

Table types define how data is stored and modeled in AnalyticsCreator, from source ingestion and historization to dimensional and Data Vault structures.