Concept: Dataset Stages
A stage is a dataset component that takes in data, transforms it in some way, and outputs modified data. A stage performs a single computational function, such as joining data with a Join stage or importing data from the dataset source with an Import stage.
Adding a stage can change the number of records and fields in the dataset.
Prism Analytics supports these stage types:
Stage Type | Description |
|---|---|
Import | Workday creates this stage automatically as the first stage in derived datasets because they import a table or another dataset as the source. You can't delete or add an Import stage. |
Parse | Workday creates this stage automatically for base datasets. You can't delete or add an Parse stage.
If you're new to Workday, you don't have access to create or edit base datasets. |
Explode | Use an Explode stage to convert a multi-instance field into an instance field. Workday takes each instance value in the multi-instance field and creates a new record for each value.
For details, see Reference: Explode Stages. |
Filter | Use a Filter stage to constrain the number records in the dataset based on a filter condition.
For details, see: Reference: Filter Stages. |
Group By | Use a Group By stage to aggregate records of data into groups.
For details, see: Reference: Group By Stages. |
Join | Use a Join stage to join the data in this dataset with the data that you import from another dataset or table based on the relationship between a field in each set of data.
Deleting a Join stage disconnects but keeps the stage's pipeline. If you don't want to keep the disconnected pipeline, delete it or use it in another Join stage. For details, see: Reference: Join Stages. |
Manage Fields | Use a Manage Fields stage to view field changes, hide fields, or edit fields.
For details, see: Manage Dataset Fields. |
Union | Use a Union stage to combine the records from this dataset with the records from another dataset or table that you import.
Deleting a Union stage disconnects but keeps the stage's pipeline. If you don't want to keep the disconnected pipeline, delete it or use it in another Union stage. For details, see: Reference: Union Stages. |
Unpivot | Use an Unpivot stage to convert fields (columns) to records (rows) in the dataset.
|
Validation | Use the Validation stage to ensure data integrity in your data pipeline. This stage uses predefined rules to catch duplicates or errors before they reach your production reports. For details, see Reference: Validation Stages. |