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Workday-Prism-Analytics is the Workday exam Workday Pro Prism Analytics Exam.
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- Exam code
- Workday-Prism-Analytics
- Vendor
- Workday
- Practice questions
- Not available yet
- Free sample questions
- 7
- Question bank last updated
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Taken from the free sample set for Workday-Prism-Analytics.
Question 1
What window function returns the number of rows within a window?
- AOption A:
- BOption B:
SUM
- COption C:
- DOption D:
AVG
Show answer and explanation
Correct answer: C
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, window functions are used to perform calculations over a defined set of rows (a “window”). According to the official Workday Prism Analytics study path documents, the COUNT window function is used to return the number of rows within a specified window. When applied in a dataset transformation, the COUNT function counts the rows that fall within the window, which can be defined by partitioning (e.g., by a specific column) and ordering criteria. For example, COUNT(*) OVER (PARTITION BY department) would return the number of rows for each department in the dataset.
The other options serve different purposes:
A. MAX: Returns the maximum value within the window, not the number of rows.
B. SUM: Calculates the sum of a numeric field across the window, not the row count.
D. AVG: Computes the average of a numeric field within the window, not the row count.
The COUNT function is specifically designed to provide the row count, making it the correct choice for this purpose in Prism Analytics transformations.
[References:, , Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Window Functions and Their Applications, Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Using COUNT in Window Functions]
Question 2
A Prism data administrator combined data from multiple sources down to a final derived dataset, including current worker data. There is a new requirement to append historical worker data to the dataset in a uniform layout. The historical worker data includes some, but not all, fields that align with the current worker data. Using current worker data as the primary pipeline, how can the historical worker data points be brought in?
- AOption A:
Add a Join stage with a Right Outer Join.
- BOption B:
- COption C:
Add a Join stage with a Left Outer Join.
- DOption D:
Add a Join stage with an Inner Join.
Show answer and explanation
Correct answer: B
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, when the goal is to append data from one dataset to another in a uniform layout, such as combining current worker data with historical worker data, a Union stage is the appropriate transformation. According to the official Workday Prism Analytics study path documents, a Union stage is used to append rows from one pipeline to another, stacking the data vertically while aligning fields based on their names and types. In this scenario, the current worker data (primary pipeline) and historical worker data (secondary pipeline) share some fields, and a Union stage will combine the rows from both datasets into a single dataset. Fields that exist in one pipeline but not the other will have NULL values for the rows where they are not present, ensuring a uniform layout without losing data.
The other options are not suitable for this requirement:
A. Add a Join stage with a Right Outer Join: A Right Outer Join would include all rows from the historical worker data and only matching rows from the current worker data, which does not align with the goal of appending all data in a uniform layout.
C. Add a Join stage with a Left Outer Join: A Left Outer Join would include all rows from the current worker data and matching rows from the historical worker data, but this is not an append operation; it’s a matching operation based on a join condition, which isn’t specified here.
D. Add a Join stage with an Inner Join: An Inner Join would only include rows where matches exist between the two datasets, potentially excluding non-matching historical or current worker data, which does not meet the requirement to append all data.
The Union stage is the correct approach to append historical worker data to the current worker data, ensuring all rows are included in a uniform layout, with NULLs filling in for missing fields.
[References:, Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Using Union Stages to Append Data in Prism Analytics, Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Combining Datasets with Union Operations, ]
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