Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, joining datasets requires that the fields used in the join condition (Match Row fields) are compatible to ensure accurate matching. According to the official Workday Prism Analytics study path documents, the field types for the Match Row fields must match (option A). For example, if the join condition is based on an Employee ID field, the field type (e.g., Text or Numeric) must be the same in both datasets. Mismatched field types (e.g., Text in one dataset and Numeric in another) can lead to join failures or incorrect results, as Prism cannot reliably compare values of different types. This often requires using a Manage Fields stage to align field types before the join.
The other options are incorrect:
B. The number of rows in each dataset: The number of rows does not need to match; joins can handle datasets of different sizes, depending on the join type (e.g., Left Outer Join).
C. The level of detail in each dataset: The level of detail (granularity) does not need to match; joins can combine datasets with different levels of detail as long as the Match Row fields are compatible.
D. The field names for the Match Row fields: The field names do not need to be identical; the join condition maps fields between datasets, so different names can be used as long as the types and values are compatible.
Ensuring that the field types of the Match Row fields are the same is critical for a successful join operation in Prism Analytics.
[References:, Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Requirements for Joining Datasets in Prism Analytics, Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Configuring Join Conditions for Datasets, ]
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