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.
Configs to check when starting with ADE
Enforcing naming conventions and default attributes
To define tenant-specific naming conventions and define desired default attributes, modify contents of CONFIG_ENTITY_DEFAULTS -package. See also user guide for customizing default attributes.
For example, tenant might have the following rules:
Staging-tables should start with
STG_
Data Vault tables should have prefixes
H_
,L_
,S_
and so on.Data Vault -tables should have always columns
dv_id
,dv_load_time
anddv_source_system
These are just examples what to define with CONFIG_ENTITY_DEFAULTS -package. See examples and guides for more information.
Enforcing naming conventions and default attributes are 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 custom transformation logic for source entity attributes or defining custom transformation logic for Data Vault hash-keys, use CONFIG_LOAD_TRANSFORMATIONS -package.
There is a set of pre-defined transformations already in Agile Data Engine, but it might be useful to modify those to customer needs.
Transformation formulas:
Can be hidden from the Designer if not needed
Are DBMS product-specific SQL-code
Transformation formula accept FreeMarker syntax
How transformation formulas work:
In the entity mapping view, transformation formulas 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 from CONFIG_LOAD_TRANSFORMATIONS and from Data Warehouse modeling guide to get started with customizing transformations.