Get Instant Access to Workday-Prism-Analytics Practice Exam Questions [Q29-Q51]

Q29. You accidentally delete a Prism calculated field that is used in other Prism calculated fields or conditions.
What is a possible outcome?

The system will automatically reverse the deletion because the field is referenced elsewhere.

Any calculated field referencing the deleted field defaults to zero.

Errors will result in any stage or calculated field that references the field.

The system will automatically adjust any dependencies accordingly.

Q30. You want to create a Prism calculated field to change the field type to date data using the TO_DATE function.
The field from Workday is numeric data and you will use the Manage Fields stage to prepare the data for use in the function. What will you need to change about the field in the Manage Fields stage?

Output Type

Output Name

Input Type

Input Name

Q31. Why should you include Workday instance field types in the Workday report that you use to import data into Prism?

The final Prism datasource can support drilling into Workday objects.

Performance is improved in the final Prism datasource when published.

Unions are more easily performed with instance field types.

Joins are more easily performed with instance field types.

Comprehensive and Detailed Explanation From Exact Extract:
When importing data into Workday Prism Analytics from a Workday report, including Workday instance field types in the report is critical for enabling specific functionality in the resulting Prism data source.
According to the official Workday Prism Analytics study path documents, including instance field types allows the final Prism data source to support drilling into Workday objects. Instance field types represent references to Workday business objects (e.g., Worker, Position, or Organization), and including them in the report ensures that the Prism data source retains the ability to navigate to these objects within Workday’s reporting and analytics framework. This enables users to perform drill-down actions, such as accessing detailed object data directly from Prism visualizations or reports.
The other options do not accurately reflect the primary benefit of including instance field types:
* B. Performance is improved in the final Prism datasource when published: Instance field types do not directly impact the performance of the published data source; performance is more influenced by data volume and indexing.
* C. Unions are more easily performed with instance field types: Unions depend on schema compatibility, not instance field types, which are specific to Workday object references.
* D. Joins are more easily performed with instance field types: While instance field types can be used in joins, their primary purpose is to enable object navigation, not to simplify join operations.
By including instance field types, the Prism data source gains enhanced interactivity, allowing users to leverage Workday’s object model for deeper analysis and navigation.
References:
Workday Prism Analytics Study Path Documents, Section: Integrating Prism with Workday Reports, Topic:
Workday Report Field Types and Prism Integration
Workday Prism Analytics Training Guide, Module: Publishing and Visualizing Data, Subtopic: Enabling Drill-Down Capabilities in Prism Data Sources

Q32. You are loading data into a table using the Data Change task. The field type in the source file is Numeric and the table field type is Text. What can you do to load the data?

Use a different source file, as the field types are incompatible.

Map the Numeric field to the table Text field.

Change the field type in the parsing stage from Numeric to Text.

Change the connection type for the data change task.

Q33. You apply an Explode stage to your derived dataset that contains information on your worker benefit elections. What happens in the resulting stage?

The number of columns stays the same and the original multi-instance field doesn’t get dropped.

The number of columns exponentially increases and the original multi-instance field gets dropped.

The number of rows stays the same and the original multi-instance field does not get dropped.

The number of rows exponentially increases and the original multi-instance field gets dropped.

Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, an Explode stage is used to transform a multi-instance field into multiple rows, creating a single-instance field for each instance. According to the official Workday Prism Analyticsstudy path documents, when an Explode stage is applied to a derived dataset containing worker benefit elections (a multi-instance field, e.g., a list of elected benefits per worker), the following occurs: the number of rows exponentially increases, and the original multi-instance field gets dropped (option D).
For example, if a worker has three benefit elections in a multi-instance field, the Explode stage will create three rows-one for each election-while the original multi-instance field (e.g., “Benefit Elections”) is replaced by a single-instance field containing one election per row. The number of rows increases based on the number of instances in the multi-instance field (e.g., a dataset with 100 workers, each with 3 elections on average, would grow from 100 rows to 300 rows). The term “exponentially” in the question reflects this potential for significant row growth, though the increase is technically linear per record based on the number of instances.
The other options are incorrect:
* A. The number of columns stays the same and the original multi-instance field doesn’t get dropped: The original multi-instance field is dropped and replaced by a single-instance field; the column count may change slightly due to this replacement.
* B. The number of columns exponentially increases and the original multi-instance field gets dropped:
The Explode stage does not increase the number of columns exponentially; it primarily affects rows, with minimal impact on columns.
* C. The number of rows stays the same and the original multi-instance field does not get dropped: The number of rows increases due to the explosion of multi-instance data, and the original field is dropped.
The Explode stage’s behavior of increasing rows and dropping the original multi-instance field aligns with its purpose of normalizing multi-instance data into a row-based structure.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Using the Explode Stage in Derived Datasets Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Handling Multi- Instance Fields with Explode Stages

Q34. 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.

Q35. You explode the Language Skills multi-instance field on your derived dataset and you want to change the business object that the new Language Skills Exploded instance field is mapped to. What steps should you take?

Select from the list of suggested BO values in the Explode stage configuration.

Click on the Related Actions next to the business object in the insight panel.

Add a Manage Fields before the Explode stage and modify the business object.

Add a Manage Fields after the Explode stage and modify the business object.

Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, the Explode stage transforms a multi-instance field (e.g., Language Skills) into multiple rows, creating a new single-instance field (e.g., Language Skills Exploded). The resulting field inherits the business object (BO) mapping from the original multi-instance field, but this mapping can be modified if needed. According to the official Workday Prism Analytics study path documents, to change the business object that the new Language Skills Exploded instance field is mapped to, you should add a Manage Fields stage after the Explode stage and modify the business object (option D).
The Manage Fields stage allows you to edit field properties, including the business object mapping, for the exploded field. After the Explode stage creates the new single-instance field, the Manage Fields stage can be used to reassign the business object by selecting a different Workday business object (e.g., changing from a generic object to a specific one like “Language”). This step ensures the field is mapped correctly for downstream reporting or integration with Workday reports.
The other options are incorrect:
* A. Select from the list of suggested BO values in the Explode stage configuration: The Explode stage does not provide an option to modify business object mappings during its configuration; it focuses on exploding the multi-instance field.
* B. Click on the Related Actions next to the business object in the insight panel: The insight panel provides metadata insights but does not allow direct modification of business object mappings for fields.
* C. Add a Manage Fields before the Explode stage and modify the business object: Modifying the business object before the Explode stage affects the original multi-instance field, but the Explode stage will still create the new field with the inherited mapping, so this does not achieve the goal.
Adding a Manage Fields stage after the Explode stage is the correct approach to modify the business object mapping of the new exploded field.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Managing Field Properties After Explode Stages Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Modifying Business Object Mappings in Derived Datasets

Q36. 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.

Q37. 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?

After the dataset is published.

At the end of the Primary Pipeline of a published dataset.

At the beginning of the Primary Pipeline of the derived dataset.

At the beginning of the primary pipeline of the Base Dataset.

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

Q38. A Prism data administrator notices that several of the Prism calculated fields on their lineage are producing nil results, so they need to revise the expressions for all of the affected calculated fields. Where can they review the expressions in bulk?

The table or dataset where the calculated field was created.

The View Dataset Lineage report.

Any table in the lineage.

Any dataset in the lineage.

Q39. 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.

Q40. 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

Q41. 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

Q42. 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.

Q43. 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

Q44. 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.

Q45. What window function returns the number of rows within a window?

MAX

SUM

COUNT

AVG

Q46. You have to blend two sources of data. Your matching field is Employee ID, which is a text-type field in Pipeline 1, but is numeric in Pipeline 2. How do you prepare your data for blending?

Add a Manage Fields to change the field type and then Union.

Add a Filter first and then a Manage Fields to change the field type.

Add first a Manage Fields to change the field type and then Join.

Add a Join first and then a Manage Fields to change the field type.

Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, blending two data sources typically involves joining them on a common field, such as Employee ID in this case. However, the Employee ID field is text in Pipeline 1 and numeric in Pipeline 2, which means the field types must be aligned before a join can be performed to avoid data mismatches or errors. According to the official Workday Prism Analytics study path documents, the correct approach is to first use a Manage Fields stage to change the field type of Employee ID in one of the pipelines to match the other (e.g., convert the numeric Employee ID in Pipeline 2 to text, as text can safely store numeric values without data loss), and then perform a Join stage to blend the data (option C). Converting from numeric to text is preferred because converting text to numeric risks data loss if the text field contains non- numeric characters.
The other options are not appropriate:
* A. Add a Manage Fields to change the field type and then Union: A Union appends rows vertically and does not blend data based on a matching field like Employee ID; blending typically requires a Join.
* B. Add a Filter first and then a Manage Fields to change the field type: Adding a Filter stage is unnecessary for preparing the field types for a join and does not address the blending requirement.
* D. Add a Join first and then a Manage Fields to change the field type: Performing the Join first will fail or produce incorrect results because the field types (text and numeric) are incompatible for joining; the types must be aligned before the Join.
By using a Manage Fields stage to change the field type first and then performing a Join, the data from both pipelines can be blended accurately on the Employee ID field.
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 for Data Blending

Q47. 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

Q48. You want to apply a Filter stage to your derived dataset to show only expense reports submitted in the current month and where the expense report total amount is higher than 2000 USD. What should you do?

Use a simple filter, two conditions, and “If All” operator.

Use a simple filter, two conditions, and “If Any” operator.

Use a simple filter, three conditions, and “If All” operator.

Use a simple filter, three conditions, and “If Any” operator.

Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, a Filter stage in a derived dataset is used to include only rows that meet specific criteria. The requirement here is to show expense reports that satisfy two conditions: (1) submitted in the current month, and (2) total amount higher than 2000 USD. According to the official Workday Prism Analytics study path documents, this can be achieved by using a simple filter with two conditions and the “If All” operator (option A).
The first condition would check the submission date, using a function like MONTH() to compare with the current month (e.g., MONTH(submission_date) = MONTH(CURRENT_DATE())). The second condition would compare the total amount (e.g., total_amount > 2000). The “If All” operator ensures that both conditions must be true for a row to be included, which aligns with the requirement that both criteria (current month AND amount > 2000 USD) must be met. A simple filter is sufficient because the logic involves straightforward comparisons without nested conditions.
The other options are incorrect:
* B. Use a simple filter, two conditions, and “If Any” operator: The “If Any” operator would include rows where either condition is true (e.g., submitted in the current month OR amount > 2000 USD), which does not meet the requirement for both conditions to be true.
* C. Use a simple filter, three conditions, and “If All” operator: Only two conditions are needed (submission month and amount), so three conditions are unnecessary.
* D. Use a simple filter, three conditions, and “If Any” operator: This combines the issues of option B (wrong operator) and option C (too many conditions).
Using a simple filter with two conditions and the “If All” operator ensures the dataset includes only the expense reports that meet both criteria.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Applying Filters in Derived Datasets Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Configuring Simple Filters with Multiple Conditions

Q49. 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

Get Instant Access to Workday-Prism-Analytics Practice Exam Questions [Q29-Q51]

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