A feature dimension transformation creates a dimension table, previously called "enrichment table"
What is a Feature Dimension Table?
A feature dimension table is used to add additional features (columns) to any activity, by joining to one of its features. A single feature dimension table can be used to enrich multiple activities with feature details.
Columns in a Feature Dimension Transformation
A feature dim transformation generates a dataset with two required columns (which are used to join to an activity) and any number of additional columns which are the additional dimensions.
|Unique ID used to join to an activity feature|
|(optional) Timestamp in UTC, only used for incremental processing.|
|features columns||(optional) These columns are the additional dimensions used to enrich an activity or activities.|
The names should be descriptive of the data they represent and they do not need to use the feature_ convention used for activities.
How To: Create a Feature Dimension Transformation
Watch this step-by-step tutorial to create a feature dimension table transformation.
Explore the transformation library for examples by data source.
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Updated 7 days ago