8. Date_Generation Transform:
•Produces a series of dates with a specified increment
•From this generated sequence we can populate other fields in the time dimension (Such as day_of_week) using functions available in the query
•Data Inputs – none
•Data Outputs – A data set with a single column named DI_GENERATED_DATE containing the date sequence
•In the Date _generation editor the following details are to be provided.
9. Hierarchy Flattening Transform:
•The hierarchy flattening transform can analyze a parent-child relationship and provide a description of the hierarchy in a flattened format (vertically flattened/ horizontally flattened).
•Each row in the output will contain 1 parent-child relationship.
•If we had additional columns in the source table , that are associated with the Parent column, we could have added them to the Parent attribute List.
•Similarly , if we had additional columns in the source table , that are associated with the Child column, we could have added them to the Child attribute List
•consider the following reporting structure in an organization:
Hierarchy Flattening Vertical:
Hierarchy Flattening Horizontal:
10. Validation Transform:
•Qualifies a data set based on rules for input schema columns. Allows one validation rule per column.
•Filters out or replaces data that fails the criteria
•Outputs two schemas: Pass and Fail. The Pass output schema is identical to the input schema. It also adds two columns to the Fail output schema:
•The DI_ERRORACTION column indicates where Failed data was sent:
•B for “sent to both Pass and Fail outputs”
•F for “sent only to the Fail output”
•The DI_ERRORCOLUMNS column displays all error messages for columns with failed rules.