Configuring ADE

When setting up ADE, you need to decide some conventions for ADE usage and configure those to ADE by using configuration packages.

Role of configuration packages

Configuration packages are a way to configure Agile Data Engine. They are committed and deployed in the same way as entity packages and they enable sharing configurations between tenants.

ADE comes with pre-configured default configurations. You can find the latest versions in this GitHub repository.

Configs to check when starting with ADE

Enforcing naming conventions and default attributes

To define tenant-specific naming conventions and desired default attributes, modify the contents of CONFIG_ENTITY_DEFAULTS package. See also user guide for customizing default attributes.

Here are some examples of naming conventions and default attributes:

• Staging-tables should start with STG_

• Data Vault table names should have prefixes H_, L_, S_ and so on.

• Data Vault tables should have default columns dv_id, dv_load_time and dv_source_system.

Enforcing naming conventions and default attributes is important to keep the ADE-built solution consistent between developers and developer teams.

Customizing default transformations

To define tenant-specific load transformations, such as defining a custom transformation logic for source entity attributes or for Data Vault hash keys, use the CONFIG_LOAD_TRANSFORMATIONS package.

Agile Data Engine comes with pre-defined transformation types but they can be modified and new transformation types can be added according to your needs.

Transformation formulas:

• Can be hidden from the Designer if not needed

• Produce DBMS-product-specific SQL code

• Transformation formulas are defined with FreeMarker syntax

How transformation formulas work:

• In the entity mapping view, transformation types can be chosen from a drop-down menu.

• It is possible to set transformation formulas as default, for example, when mapping attributes from source entity to target entity.

See examples in GitHub, CONFIG_LOAD_TRANSFORMATIONS and the Data Warehouse modeling guide to get started with customizing transformations.