Generator Configuration
Each Generator corresponds to a Target Technology and a Modeling approach.
To better understand the different modeling approaches, please refer to the article Model a BI solution.
Some of the generator capabilities are standard across multiple Generators, such as incremental load and delete detection.
To streamline the creation and maintenance of new Generators, as well as to configure each capability, the Generator architecture is divided into two layers, namely the Architecture Layer and the Implementation Layer.
- The Architecture Layer itself is composed of 2 parts: the Semantic part and the Architecture part.
- The Semantic part is the business representation of a Generator and configures all possible semantic objects.
- Target Layers: Source, Stage, Raw Vault, Business Vault, ...
- Model Object Types: Stage, Raw Vault Composite, Hub, Satellite, ...
- Default Terms: SourceSystem, ...
- Properties: DeduplicationMethod, ...
- The Architecture part uses the Semantic part to define the architecture based on the modeling approach. For example, it has been determined that a Satellite can only have a relationship with Hubs and not with Links.
- The Semantic part is the business representation of a Generator and configures all possible semantic objects.
- On the other hand, the Implementation Layer uses the Architecture Layer to create Target code based on the selected Target Technology. For example, in SQL Server, we create a table starting with the statement CREATE TABLE, whereas in another Target Technology, the statement looks different.
The biGENIUS-X Generators contain C# code that allows a set of Unit Tests to ensure quality.
Which Generator Configurations are available?
The Generator Configurations are organized into Generator Groups.
The following Generator Configurations are available in biGENIUS-X:
- DataVault Microsoft Fabric Spark:
- DataVault Databricks:
- Dimensional Snowflake:
- DataVault Snowflake:
- Dimensional MSSQL:
- DataVault MSSQL: