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Workday Pro Prism Analytics Exam Sample Questions (Q31-Q36):

NEW QUESTION # 31
What window function returns the number of rows within a window?

A. MAX
B. SUM
C. AVG
D. COUNT

Answer: D

Explanation:
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

NEW QUESTION # 32
A Prism data writer needs to create a new Prism calculated field on a derived dataset using the CASE function. When creating a calculated field, what symbol do you use to view a list of fields that you can select from in the dataset?

A. #
B. [
C. {
D. (

Answer: B

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, when creating a calculated field in a derived dataset, users often need to reference existing fields in the dataset within their expressions, such as in a CASE function. According to the official Workday Prism Analytics study path documents, to view and select from a list of available fields in the dataset while building a calculated field expression, the user types the [ symbol (left square bracket). This symbol triggers a dropdown list of all fields in the dataset, allowing the user to select the desired field without manually typing its name, reducing the risk of errors. For example, typing [ and selecting a field like
"Employee_ID" will insert [Employee_ID] into the expression, which can then be used in the CASE function logic.
The other symbols do not serve this purpose:
* B. (: Parentheses are used for grouping expressions or defining function parameters, not for field selection.
* C. #: The hash symbol is not used in Prism Analytics for field selection; it may be associated with other functionalities in different contexts.
* D. {: Curly braces are not used for field selection in Prism Analytics; they may be used in other systems for different purposes, such as templating.
The use of the [ symbol ensures an efficient and accurate way to reference fields in a calculated field expression, streamlining the creation process in Prism Analytics.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Creating Calculated Fields in Derived Datasets Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Using the Expression Editor for Calculated Fields

NEW QUESTION # 33
The final derived dataset in a Prism pipeline is complete and ready to publish. What should be done prior to publishing?

A. Edit the Dataset API Name to reflect in the name of the Prism data source.
B. Create a table without the Enable for Analysis checkbox selected.
C. Add a Group By stage to the final derived dataset to add summary calculations.
D. Create a derived dataset with the PDS suffix.

Answer: A

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, before publishing a derived dataset as a Prism data source (PDS), it's important to ensure that the dataset is properly configured for downstream use. According to the official Workday Prism Analytics study path documents, one key step to take prior to publishing is to edit the Dataset API Name to reflect in the name of the Prism data source (option D). The Dataset API Name determines the name of the published Prism data source, which is used in reporting, discovery boards, and integrations. Setting a meaningful and descriptive API name (e.g., "Expense_Reports_by_Location") ensures that the data source is easily identifiable and aligns with naming conventions, improving usability and manageability in the Workday ecosystem. This step is a best practice to avoid confusion and ensure clarity for report writers and analysts.
The other options are not required or relevant:
* A. Add a Group By stage to the final derived dataset to add summary calculations: Adding a Group By stage is not mandatory unless the use case specifically requires summarizations, which is not indicated here.
* B. Create a table without the Enable for Analysis checkbox selected: Creating a new table is unnecessary, as the dataset is already complete, and the "Enable for Analysis" checkbox is relevant for real-time updates, not a requirement for publishing a derived dataset.
* C. Create a derived dataset with the PDS suffix: Creating a new dataset is not needed, as the final derived dataset is already prepared, and adding a "PDS" suffix is not a required step for publishing.
Editing the Dataset API Name ensures the Prism data source has a clear and meaningful name, facilitating its use in reporting and analytics.
References:
Workday Prism Analytics Study Path Documents, Section: Publishing and Visualizing Data, Topic: Best Practices for Publishing Prism Data Sources Workday Prism Analytics Training Guide, Module: Publishing and Visualizing Data, Subtopic: Configuring Dataset API Names Before Publishing

NEW QUESTION # 34
You are adding a Join stage and choose Join type of Left Outer Join, causing Workday to search for a matching row in the imported pipeline. What happens if no matching rows exist?

A. Included fields from both pipelines will have NULL values.
B. Included fields from the imported pipeline will have NULL values.
C. A duplicate row will be generated.
D. The row will be omitted.

Answer: B

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, a Left Outer Join in a Join stage includes all rows from the primary pipeline (the left pipeline) and attempts to match them with rows from the imported pipeline (the right pipeline) based on the join condition. According to the official Workday Prism Analytics study path documents, if no matching rows exist in the imported pipeline for a given row in the primary pipeline, the row from the primary pipeline is still included in the output, but the fields from the imported pipeline will have NULL values. This behavior ensures that all data from the primary pipeline is retained, while the absence of a match in the imported pipeline is represented by NULLs for the corresponding fields.
The other options are incorrect:
* A. A duplicate row will be generated: A Left Outer Join does not generate duplicate rows; duplicates would occur only if multiple matches exist in the imported pipeline, which is not the case here.
* B. The row will be omitted: In a Left Outer Join, rows from the primary pipeline are never omitted, even if no match is found; this behavior is specific to an Inner Join.
* D. Included fields from both pipelines will have NULL values: Only the fields from the imported pipeline will have NULL values; the fields from the primary pipeline retain their original values.
This behavior of Left Outer Join ensures that all records from the primary pipeline are preserved, with NULLs indicating the absence of matching data from the imported pipeline.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Join Types and Their Behaviors in Prism Analytics Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Configuring Join Stages in Derived Datasets

NEW QUESTION # 35
You are a new Prism customer and you want to ensure the correct set of fields is brought into a derived dataset. When should you apply a Manage Fields stage?

A. At the beginning of the Primary Pipeline of the derived dataset.
B. At the beginning of the primary pipeline of the Base Dataset.
C. After the dataset is published.
D. At the end of the Primary Pipeline of a published dataset.

Answer: A

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, a Manage Fields stage is used to control the fields in a dataset by renaming, hiding, or changing field types, among other actions. According to the official Workday Prism Analytics study path documents, to ensure the correct set of fields is brought into a derived dataset (DDS), the Manage Fields stage should be applied at the beginning of the Primary Pipeline of the derived dataset (option C).
Placing the Manage Fields stage early in the pipeline-right after the initial import stage (Stage 1)-allows you to define the field structure upfront, ensuring that subsequent transformationstages (e.g., Join, Filter, Calculate Field) operate on the desired set of fields. This approach helps maintain consistency and avoids unnecessary processing of fields that are not needed in later stages.
The other options are not optimal:
* A. After the dataset is published: You cannot add transformation stages like Manage Fields after a dataset is published; transformations must be applied during the dataset's creation or editing.
* B. At the end of the Primary Pipeline of a published dataset: Similar to option A, you cannot modify a published dataset's pipeline, and placing Manage Fields at the end would not prevent unnecessary fields from being processed in earlier stages.
* D. At the beginning of the primary pipeline of the Base Dataset: A Base Dataset does not have a transformation pipeline; it is a direct import of a table, so Manage Fields stages can only be applied in a Derived Dataset.
Applying the Manage Fields stage at the beginning of the derived dataset's Primary Pipeline ensures efficient data preparation and transformation.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Using Manage Fields in Derived Datasets Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Best Practices for Field Management in Pipelines

NEW QUESTION # 36
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