[Data Prep and Transformation] A Prism data administrator combined data from multiple sources down to a final derived dataset, including current…

The requirement is to "append" historical worker data to the existing current worker dataset. In data transformation, appending means adding rows from one dataset to another, effectively stacking them vertically. The Union stage in Workday Prism Analytics is specifically designed for this operation. It combines rows from two or more datasets into a single dataset. The Union stage also creates a unified schema, which accommodates datasets where columns do not perfectly align by including all columns from all inputs and populating non-matching fields with null values, thus creating the required "uniform layout."

A. A Join stage with a Right Outer Join combines datasets horizontally by adding columns based on a key, not by appending rows vertically.
C. A Join stage with a Left Outer Join also combines datasets horizontally by adding columns, not by appending rows.
D. A Join stage with an Inner Join combines datasets horizontally and only retains rows with matching keys in both datasets, which is not the goal here.

1. Workday Prism Analytics Documentation, "Prepare Data". Section: Union Stage. This section details how the Union stage is used to combine rows from multiple datasets. It explicitly states, "Use a Union stage to combine rows from 2 or more datasets into a single dataset... The output dataset contains all columns from all input datasets." This directly supports the use of Union for appending data with potentially misaligned columns.

2. Workday Prism Analytics Documentation, "Prepare Data". Section: Join Stage. This documentation describes the function of a Join stage as combining columns from two datasets based on a common key. It outlines the different join types (Inner, Left Outer, Right Outer, Full Outer), all of which perform horizontal data merging, contrasting with the vertical merging (appending) required by the question.

3. Workday Training Courseware, "Prism Analytics: Data Preparation and Transformation". Module: Combining Datasets. This training material differentiates between joining and unioning data. It presents a use case for the Union stage that mirrors the question's scenario: combining datasets with similar structures but from different time periods (e.g., Q1 sales and Q2 sales) into a single, comprehensive dataset.