[Sep-2025] Practice Workday Workday-Prism-Analytics exam. Online Exam Practice Tests with detailed explanations! Pass Workday-Prism-Analytics with confidence! [Q22-Q44]

NO.22 When joining datasets, what items must match?

The field types for the Match Row fields.

The number of rows in each dataset.

The level of detail in each dataset.

The field names for the Match Row fields.

NO.23 An HR analyst is tasked to create custom reports for their company’s performance reviews. The analyst uses both Workday and Prism for data analysis. What Workday-calculated field functions would the analyst be able to build off of their Prism object?

Extract Single Instance

Arithmetic Calculation

Lookup Related Value

Lookup Field with Prompts

Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, when integrating with Workday reports, a Prism object (i.e., a published Prism data source) can be used as the basis for custom reports, and certain Workday-calculated field functions can be applied to it. According to the official Workday Prism Analytics study path documents, the Arithmetic Calculation function (option B) is a supported Workday-calculated field function that can be built off a Prism object. This function allows the analyst to perform mathematical operations (e.g., addition, subtraction, multiplication) on numeric fields within the Prism data source, such as calculatinga performance review score by combining multiple metrics. Since Prism data sources often contain pre-processed data, arithmetic calculations can be applied to enhance the data for reporting purposes.
The other options are not supported for Prism objects:
* A. Extract Single Instance: This function is used to extract a single instance from a multi-instance field in Workday, but Prism objects typically contain single-instance fields after transformations (e.g., via an Explode stage), making this function inapplicable.
* C. Lookup Related Value: This function retrieves related values from other Workday business objects, but Prism objects do not support direct lookups to Workday objects in this manner; such relationships must be pre-built in the Prism dataset.
* D. Lookup Field with Prompts: This function involves interactive prompting, which is not supported for Prism objects in Workday reports, as Prism data sources are static snapshots of data.
The Arithmetic Calculation function provides the flexibility to perform numerical computations on Prism data, making it a suitable choice for enhancing performance review reports.
References:
Workday Prism Analytics Study Path Documents, Section: Integrating Prism with Workday Reports, Topic:
Using Calculated Fields with Prism Objects
Workday Prism Analytics Training Guide, Module: Integrating Prism with Workday Reports, Subtopic:
Supported Calculated Field Functions for Prism Data Sources

NO.24 What window function returns the number of rows within a window?

MAX

SUM

COUNT

AVG

NO.25 A Prism administrator wants to hide a field that contains employee salary information but still allow the Prism data writers to view average salaries for employees by cost center. What is the reason for hiding this field?

To protect sensitive data.

To hide Prism-calculated fields used for interim processing.

To hide unpopulated or sparse data fields.

To use computed values instead of base values.

NO.26 For a Prism use case, you have two datasets: one contains daily sales data, and the other contains monthly budget allocations. Before performing a join between these datasets, what transformation stage should you apply to the sales data to ensure it matches the granularity of the budget data?

Union

Group By

Manage Fields

Filter

NO.27 A custom report uses your recently published Prism data source, but you noticed a minor error in the published data. You need to delete the published rows to fix it. What happens to your custom report?

The report definition remains intact and will work after republishing.

The report definition will need to be manually recreated.

The report definition will be copied and a new version will appear after republishing.

The report definition will need to be edited to reflect changes.

NO.28 In a Prism project, you have a dataset containing customer purchase transactions, including the customer ID, purchase amount, and purchase date. You want to analyze the total purchase amount for each customer over the entire period. What transformation stage should you apply to calculate the total purchase amount for each customer?

Join

Union

Group By

Explode

NO.29 A Prism data administrator needs to add an Explode stage to a derived dataset to create a new single-instance type field. What is the only field type you can select in the Explode stage?

Numeric

Multi-Instance

Single-Instance

Text

NO.30 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 withthe current worker data.
Using current worker data as the primary pipeline, how can the historical worker data points be brought in?

Add a Join stage with a Right Outer Join.

Add a Union stage.

Add a Join stage with a Left Outer Join.

Add a Join stage with an Inner Join.

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

NO.31 A Prism data writer has two pipelines of data that need to be joined together:
* The primary pipeline includes point of sale data by sales agent.
* The secondary pipeline includes performance rating by sales agent.
The requirement is to keep all of the point of sale data from the primary pipeline and blend in performance rating data for the agents from the secondary pipeline where it exists. What Join type should be used to blend the data together?

Inner Join

Right Outer Join

Left Outer Join

Full Outer Join

Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, the requirement to keep all data from the primary pipeline (point of sale data by sales agent) and blend in matching data from the secondary pipeline (performance rating by sales agent) where it exists indicates the need for a specific type of join. According to the official Workday Prism Analytics study path documents, a Left Outer Join (option C) is the appropriate join type for this scenario. A Left Outer Join includes all rows from the primary pipeline and matches them with rows from the secondary pipeline based on the join condition (e.g., sales agent ID). If no match is found in the secondary pipeline, the fields from the secondary pipeline will have NULL values, but the primary pipeline’s data is fully retained, meeting the requirement to keep all point of sale data while blending in performance ratings where available.
The other options do not meet the requirement:
* A. Inner Join: An Inner Join only includes rows where matches exist in both pipelines, which would exclude point of sale data for sales agents without performance ratings, violating the requirement to keep all primary pipeline data.
* B. Right Outer Join: A Right Outer Join includes all rows from the secondary pipeline and matching rows from the primary pipeline, which prioritizes the secondary pipeline and may exclude some point of sale data, not meeting the requirement.
* D. Full Outer Join: A Full Outer Join includes all rows from both pipelines, with NULLs for non- matching rows, but this is broader than the requirement, which only needs all data from the primary pipeline, not necessarily all data from the secondary pipeline.
A Left Outer Join ensures that all point of sale data is retained while blending in performance ratings where they exist, aligning with the stated requirement.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Join Types and Their Applications in Prism Analytics Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Blending Data Using Join Stages

NO.32 You want to convert each instance of a multi-instance field and convert it to a single-instance field. What transformation stage can you use to do this?

Unpivot

Explode

Manage Fields

Group By

NO.33 What report can you run to edit and maintain your Prism import and publish schedules?

Scheduled Future Processes

Prism Management Console

Prism Activities Monitor

Prism Usage

NO.34 What is the primary purpose of window functions in Prism?

To provide row-level access control.

To manipulate strings and dates within a query.

To filter rows based on specified conditions.

To perform calculations across a set of rows related to the current row while partitioning the data.

NO.35 You had to change the imported pipeline in a Join stage and your View Dataset Lineage report shows a Stage Alert regarding the disconnected pipeline. How can you fix this and make the alert disappear?

Add a Manage Fields stage and re-attach the pipeline.

Publish the derived dataset.

Change the imported pipeline to a different one.

Delete the disconnected pipeline.

NO.36 A Prism data writer has to create an intermediary Prism calculated field A, used only to achieve a final result in Prism calculated field B and they only need to publish out field B. What should they do?

Mark field A as intermediate calculation.

Add a Manage Fields stage to the DDS and hide field A.

Add a Manage Fields stage to the DDS and hide field B.

Delete field A from their DDS and just leave field B.

NO.37 You have a number of Workday reports that use a Prism data source. When are the values of the Prism calculated fields in the Workday reports calculated?

At the calculated field creation time.

At report run time.

At time of publishing.

At dataset creation time.

NO.38 While viewing your lineage, you realize you have forgotten to add a description to some of your derived datasets. From the lineage, you double-click on a dataset to view the dataset details. What is the next step to add the missing descriptions?

Select the pencil icon next to the dataset name and Edit Transformations.

Select the pencil icon next to the Import stage to update the description.

Select Related Actions next to the dataset name and Edit Transformations.

Select Add Field from the dataset details to create a description.

NO.39 You want to delete a Prism data source, but you are unable to complete the dataset unpublish. You have deleted the Report Writer reports. What else must you delete, if present?

Upstream tables

Published rows

Discovery board visualizations

Upstream datasets

NO.40 You want your derived dataset to only show rows that meet the following criteria: Agent ID is not null AND Location is Dallas OR Location is Montreal. How can you achieve this?

By adding a Manage Fields stage.

By using Simple Filter conditions.

By using Advanced Filter conditions.

By creating a Custom Example.

Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, filtering a derived dataset to meet specific criteria involving multiple conditions with mixed logical operators (AND, OR) requires careful configuration. The criteria here are: Agent ID is not null AND (Location is Dallas OR Location is Montreal). According to the official Workday Prism Analytics study path documents, this can be achieved by using Advanced Filter conditions (option C).
A Simple Filter in Prism Analytics allows for basic conditions with a single operator (“If All” for AND, “If Any” for OR), but it cannot handle nested logic like AND combined with OR in a single filter. For example, a Simple Filter with “If All” would require all conditions to be true (Agent ID is not null AND Location is Dallas AND Location is Montreal), which is too restrictive. A Simple Filter with “If Any” would include rows where any condition is true (Agent ID is not null OR Location is Dallas OR Location is Montreal), which is too broad. The Advanced Filter, however, allows for complex expressions with nested logic, such as ISNOTNULL(Agent_ID) AND (Location = “Dallas” OR Location = “Montreal”), ensuring the correct rows are included.
The other options are incorrect:
* A. By adding a Manage Fields stage: The Manage Fields stage modifies field properties (e.g., type, visibility) but does not filter rows based on conditions.
* B. By using Simple Filter conditions: As explained, a Simple Filter cannot handle the combination of AND and OR logic required for this criteria.
* D. By creating a Custom Example: Custom Examples are used to provide sample data for testing, not to filter rows in a dataset.
Using Advanced Filter conditions allows for the precise application of the required logic to filter the dataset accurately.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Filtering Data in Derived Datasets Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Using Advanced Filters for Complex Conditions

NO.41 You have two tables. One with employee data from Workday and another with learner data from an external system. Both tables have an Employee ID field.
In the Employee Data TBL, Employee ID is text.

In the Learner Data TBL, Employee ID is numeric.

How can you prepare to join these tables, without the potential loss of data?

Import the Employee Data TBL into a DDS and change the field type of Employee ID from text to numeric using a Manage Fields stage.

Change the field type of Employee ID directly on the Employee Data TBL from text to numeric.

Change the field type of Employee ID directly on the Learner Data TBL from Numeric to Text.

Import the Learner Data TBL into a DDS and change the field type of Employee ID from numeric to text using a Manage Fields stage.

In Workday Prism Analytics, joining two tables requires that the fields used in the join condition have compatible data types to avoid data mismatches or loss. The Employee Data TBL has an Employee ID field as text, while the Learner Data TBL has an Employee ID field as numeric. According to the official Workday Prism Analytics study path documents, to join these tables without potential data loss, the best approach is to convert the numeric Employee ID in the Learner Data TBL to text, as text fields can safely store numeric values as strings, but converting text to numeric risks data loss if the text field contains non-numeric characters (e.g., leading zeros or special characters).
The correct method is to import the Learner Data TBL into a Derived Dataset (DDS) and use a Manage Fields stage to change the field type of Employee ID from numeric to text (option D). This ensures that the Employee ID field in both tables is text, enabling a safe and accurate join without losing data. The Manage Fields stage in a DDS allows for field type transformations, which is the recommended approach for preparing data for joins in Prism Analytics.
The other options are less suitable:
* A. Import the Employee Data TBL into a DDS and change the field type of Employee ID from text to numeric using a Manage Fields stage: Converting text to numeric risks data loss if the text field contains non-numeric values, which could lead to errors or missing records during the join.
* B. Change the field type of Employee ID directly on the Employee Data TBL from text to numeric:
Direct field type changes on tables are not supported in Prism Analytics, and even if possible, this approach risks data loss for the same reason as option A.
* C. Change the field type of Employee ID directly on the Learner Data TBL from Numeric to Text:
Direct field type changes on tables are not supported; field type transformations must be done in a DDS using a Manage Fields stage.
By converting the numeric Employee ID to text in a DDS, the join can be performed safely, preserving all data from both tables.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Preparing Data for Joins in Prism Analytics Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Field Type Transformations Using Manage Fields Stage

NO.42 Using three different source files, you want to load rows of data into an empty table through a Data Change task. What needs to be the same about the three source files?

Schema

Source

Naming convention

Size

[Sep-2025] Practice Workday Workday-Prism-Analytics exam. Online Exam Practice Tests with detailed explanations! Pass Workday-Prism-Analytics with confidence! [Q22-Q44]

[Sep-2025] Practice Workday Workday-Prism-Analytics exam. Online Exam Practice Tests with detailed explanations! Pass Workday-Prism-Analytics with confidence! [Q22-Q44]

TrainingDump

Leave a Reply
Cancel reply

Leave a Reply

[Sep-2025] Practice Workday Workday-Prism-Analytics exam. Online Exam Practice Tests with detailed explanations! Pass Workday-Prism-Analytics with confidence! [Q22-Q44]

TrainingDump

Leave a Reply Cancel reply

Leave a Reply

Leave a Reply
Cancel reply