Tables
The Tables section in AnalyticsCreator displays all table metadata objects defined within the current project. These tables may be sourced from connectors or created during transformations and data warehouse modeling. The interface provides key attributes related to historization, persistence, type, and schema context.
Function
Tables represent the structured storage of data, either imported from external sources or generated as part of transformation and modeling processes. Each table has attributes that control its behavior in the data warehouse, including historization and persistence options.
Access
Tables are managed from the DWH > Tables section in the AnalyticsCreator user interface. The grid displays all tables in the project, and users can filter or search based on various criteria. Each entry provides details such as schema, table type, and description.
Properties
| ID | Property | Description |
|---|---|---|
| 1 | Table Schema | The database schema (e.g., DWH, IMP) where the table resides |
| 2 | Table Name | The name of the table used in the SQL database and pipelines |
| 3 | Historization of Table | Indicates if historization (type 2 SCD logic) is applied to the table |
| 4 | Persistance of Table | If enabled, stores the table as a persisted table (not a view) |
| 5 | Table Type | Defines the type of object (e.g., Import Table, View with History, View without History, Persisted Table with History) |
| 6 | Friendly Name | Optional user-defined label for easier identification of the table |
| 7 | Description | Free-text field used for documenting the purpose or contents of the table |
Screen Overview
The image below shows the List Tables interface with columns labeled for easy identification.
Behavior
- Tables can be views or physical tables, depending on historization and persistence settings
- Each table is associated with one Layer and Schema
- Changes to historization or persistence impact generation results
- Table metadata drives the generation of SQL objects and integration packages
Notes
- Metadata is stored at project level and used during deployment
- Friendly names and descriptions help improve documentation and collaboration
- Proper historization and persistence configurations are essential for accurate lineage and auditability
