Create

Create Metadata Objects

In AnalyticsCreator, you can create certain metadata objects directly within the project repository. Unlike imported objects, manually created objects typically serve specialized purposes — such as staging tables, custom transformations, or manually defined sources.

This section explains how to create new sources and define transformations from scratch using the navigation tree or diagram interface.

Create New Source

Use Create New Source when you need to define a table that does not exist in an external system but should still be processed in the data warehouse. For example, custom mapping tables, manually maintained reference data, or externally filled bridge tables.

How to Create

1. In the Navigation Tree, expand the Connectors node.
2. Right-click on the desired connector and select Add Source.
3. In the source editor, manually define columns, data types, and primary keys as needed.

Use Cases

• Define manually maintained reference or lookup tables.
• Create bridge or control tables for workflow logic.
• Model sources that are loaded outside AnalyticsCreator but still need lineage tracking.

Create Transformations

Transformations in AnalyticsCreator are metadata objects that define how data is processed between layers — from staging to core, or from core to datamart. You can create transformations manually using the transformation diagram editor.

Transformation Types

• Regular Transformation – Create SELECT-based logic joining multiple tables.
• Script Transformation – Use SQL or stored procedures for custom logic.
• Union Transformation – Combine multiple datasets into one output table.
• Manual Transformation – Define custom columns manually without SQL logic.

How to Create

1. In the Diagram or Navigation Tree, right-click the target schema or package.
2. Select Add Transformation and choose the appropriate transformation type.
3. Use the graphical editor to define input tables, joins, filters, and mappings.

Best Practices

• Use Predefined Transformations for common logic (e.g., trimming, type conversions).
• Document the transformation logic clearly for maintainability.
• Use naming conventions to indicate the purpose and stage (e.g., trx_FactSales).

Summary

Creating objects manually in AnalyticsCreator supports flexibility in ETL logic, model extensions, and custom workflows. These definitions are stored as metadata and automatically deployed as part of the DWH pipeline.