Comprehensive and Detailed Explanation From Exact Extract:
Window functions in Workday Prism Analytics are a powerful feature used in dataset transformations to perform advanced calculations. According to the official Workday Prism Analytics study path documents, the primary purpose of window functions is to perform calculations across a set of rows related to the current row while partitioning the data. These functions allow users to compute values such as running totals, rankings, or aggregations (e.g., SUM, COUNT, RANK) within a defined “window” of rows, which can be partitioned by specific columns and ordered as needed. Window functions operate withoutcollapsing the dataset (unlike group-by aggregations), preserving the original row structure while adding calculated results.
The other options do not describe the purpose of window functions:
A. To provide row-level access control: Row-level access control is managed through security domains and policies, not window functions.
B. To manipulate strings and dates within a query: String and date manipulations are handled by other functions (e.g., CONCAT, DATEADD), not window functions.
C. To filter rows based on specified conditions: Filtering is achieved using WHERE clauses or filter stages, not window functions.
Window functions are essential for complex analytical calculations, such as ranking employees within a department or calculating cumulative totals, making them a key tool in Prism’s data transformation capabilities.
[References:, , Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Using Window Functions in Dataset Transformations, Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Advanced Calculations with Window Functions]