Workday New 2025 Workday-Prism-Analytics Sample Questions Reliable Workday-Prism-Analytics Test Engine [Q21-Q40]

Workday New 2025 Workday-Prism-Analytics Sample Questions Reliable Workday-Prism-Analytics Test Engine

Feel Workday Workday-Prism-Analytics Dumps PDF Will likely be The best Option

NEW QUESTION # 21
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?

A. To hide Prism-calculated fields used for interim processing.
B. To use computed values instead of base values.
C. To protect sensitive data.
D. To hide unpopulated or sparse data fields.

Answer: C

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, hiding a field is a common practice to control access to sensitive information while still allowing necessary analytics to be performed. According to the official Workday Prism Analytics study path documents, the primary reason for hiding a field like employee salary information is to protect sensitive data. Employee salary is considered personally identifiable information (PII) or sensitive data, and hiding the field ensures that individual salary details are not exposed to unauthorized users or in published data sources. However, by hiding the field, Prism data writers can still use it in calculations-such as computing the average salary by cost center-because hidden fields remain accessible for transformation and aggregation purposes within the dataset but are not visible in the final output or to end users of the published data source.
The other options do not align with the scenario:
* B. To hide Prism-calculated fields used for interim processing: The salary field is a base field, not a calculated field used for interim processing, so this reason does not apply.
* C. To hide unpopulated or sparse data fields: There is no indication that the salary field is unpopulated or sparse; the concern is about its sensitivity, not its data quality.
* D. To use computed values instead of base values: Hiding the field does not inherently involve replacing it with computed values; the goal is to restrict visibility while still allowing computations like averages.
Hiding the salary field protects sensitive data while enabling aggregated analytics, aligning with Prism's security and governance capabilities.
References:
Workday Prism Analytics Study Path Documents, Section: Security and Governance in Prism, Topic:
Managing Field Visibility for Data Protection
Workday Prism Analytics Training Guide, Module: Security and Governance in Prism, Subtopic: Handling Sensitive Data in Datasets

NEW QUESTION # 22
A Prism data administrator is ready to create a Prism data source. As data is updated in Prism, the goal is to update the data in the Prism data source concurrently, enabling immediate incremental updates. How should the administrator create the Prism data source?

A. Create a table and select the Enable for Analysis checkbox.
B. Create a table and select Publish.
C. Publish a derived dataset with the Prism: Default to Dataset Access Domain.
D. Set Data Source Security on a derived dataset and select Publish.

Answer: A

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, creating a Prism data source that supports immediate incremental updates as data is updated in Prism requires a specific configuration. According to the official Workday Prism Analytics study path documents, the administrator should create a table and select the Enable for Analysis checkbox (option A). The "Enable for Analysis" option, when selected during table creation, allows the table to be used directly as a Prism data source with real-time updates. This setting ensures that as data in the table is updated (e.g., through a Data Change task), the changes are immediately reflected in the Prism data source, enabling incremental updates without the need for republishing. This is particularly useful for scenarios requiring near- real-time data availability in reporting or analytics.
The other options do not achieve the goal of immediate incremental updates:
* B. Create a table and select Publish: Publishing a table creates a static Prism data source, but updates to the table require republishing, which does not support immediate incremental updates.
* C. Publish a derived dataset with the Prism: Default to Dataset Access Domain: Publishing a derived dataset creates a data source, but updates to the underlying data require republishing the dataset, which is not concurrent or incremental.
* D. Set Data Source Security on a derived dataset and select Publish: Setting security and publishing a derived dataset follows the same process as option C, requiring republishing for updates, which does not meet the requirement for immediate updates.
Selecting the "Enable for Analysis" checkbox when creating a table ensures the Prism data source supports concurrent, incremental updates as data changes in Prism.
References:
Workday Prism Analytics Study Path Documents, Section: Publishing and Visualizing Data, Topic: Creating Prism Data Sources with Real-Time Updates Workday Prism Analytics Training Guide, Module: Publishing and Visualizing Data, Subtopic: Configuring Tables for Incremental Updates

NEW QUESTION # 23
What task or report should you access to view a Prism data source?

A. View Dataset Details report
B. Edit Data Source Security task
C. View Prism Data Source report
D. Edit Dataset Transformations task

Answer: C

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, a Prism data source represents the published dataset that is available for reporting and analytics within the Workday ecosystem. According to the official Workday Prism Analytics study path documents, the "View Prism Data Source" report is the specific task or report designed to allow users to view the details of a Prism data source. This report provides comprehensive information about the data source, including its metadata, structure, and associated attributes, enabling users to understand the data available for reporting purposes.
The other options do not serve this purpose. The "Edit Dataset Transformations task" is used to modify the transformation logic applied to a dataset, not to view a data source. The "Edit Data Source Security task" focuses on managing security settings for a data source, such as access permissions, rather than viewing its contents. Similarly, the "View Dataset Details report" provides information about a dataset (including its metadata and sample rows) but does not specifically address the published Prism data source, which is a distinct entity created after a dataset is published.
The "View Prism Data Source" report is the correct choice as it directly aligns with the need to inspect the properties and structure of a Prism data source, ensuring users can verify its suitability for reporting or integration with Workday reports.
References:
Workday Prism Analytics Study Path Documents, Section: Datasets and Data Sources, Topic: Managing and Viewing Prism Data Sources Workday Prism Analytics Training Guide, Module: Publishing and Visualizing Data, Subtopic: Viewing and Validating Data Sources

NEW QUESTION # 24
The Prism use case is to classify workers based on their pay. You must create a field that evaluates worker pay and returns a value that represents various pay ranges. How would you add this field for inclusion on the Prism data source?

A. Add the additional field to your raw data before you ingest into Prism.
B. Build a CASE calculated field function on the TBL directly to ease later transformation.
C. Build an Evaluate Expression calculated field on your final Prism business object to evaluate workers against their pay.
D. Create a derived dataset and build a CASE calculated field to classify workers against their pay.

Answer: D

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, classifying workers into pay ranges based on their pay requires creating a new field that evaluates the pay values and assigns them to defined ranges (e.g., "Low," "Medium," "High").
According to the official Workday Prism Analytics study path documents, the recommended approach is to create a derived dataset (DDS) and build a CASE calculated field to classify workers against their pay (option B). The CASE function in a calculated field allows users to define conditional logic (e.g., CASE WHEN pay
< 50000 THEN "Low" WHEN pay < 100000 THEN "Medium" ELSE "High" END), which is ideal for creating pay range classifications. This calculated field is added within a deriveddataset, which can then be published as a Prism data source, making the new field available for reporting and analytics.
The other options are not optimal:
* A. Add the additional field to your raw data before you ingest into Prism: Modifying raw data outside Prism is unnecessary and less flexible, as Prism's transformation capabilities (like CASE) are designed for such tasks.
* C. Build a CASE calculated field function on the TBL directly to ease later transformation: Calculated fields cannot be created directly on a table (TBL) in Prism Analytics; they must be defined in a derived dataset.
* D. Build an Evaluate Expression calculated field on your final Prism business object to evaluate workers against their pay: Prism Analytics does not use "Prism business objects" for calculated fields, and "Evaluate Expression" is not a standard function; this option is not applicable.
Using a CASE calculated field in a derived dataset provides a flexible and maintainable way to classify workers by pay ranges, ensuring the field is included in the final Prism data source.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Creating Calculated Fields with CASE Functions Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Classifying Data Using Calculated Fields in Derived Datasets

NEW QUESTION # 25
What is the primary purpose of window functions in Prism?

A. To perform calculations across a set of rows related to the current row while partitioning the data.
B. To manipulate strings and dates within a query.
C. To provide row-level access control.
D. To filter rows based on specified conditions.

Answer: A

Explanation:
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

NEW QUESTION # 26
When joining datasets, what items must match?

A. The level of detail in each dataset.
B. The field types for the Match Row fields.
C. The number of rows in each dataset.
D. The field names for the Match Row fields.

Answer: B

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, joining datasets requires that the fields used in the join condition (Match Row fields) are compatible to ensure accurate matching. According to the official Workday Prism Analytics study path documents, the field types for the Match Row fields must match (option A). For example, if the join condition is based on an Employee ID field, the field type (e.g., Text or Numeric) must be the same in both datasets. Mismatched field types (e.g., Text in one dataset and Numeric in another) can lead to join failures or incorrect results, as Prism cannot reliably compare values of different types. This often requires using a Manage Fields stage to align field types before the join.
The other options are incorrect:
* B. The number of rows in each dataset: The number of rows does not need to match; joins can handle datasets of different sizes, depending on the join type (e.g., Left Outer Join).
* C. The level of detail in each dataset: The level of detail (granularity) does not need to match; joins can combine datasets with different levels of detail as long as the Match Row fields are compatible.
* D. The field names for the Match Row fields: The field names do not need to be identical; the join condition maps fields between datasets, so different names can be used as long as the types and values are compatible.
Ensuring that the field types of the Match Row fields are the same is critical for a successful join operation in Prism Analytics.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic:
Requirements for Joining Datasets in Prism Analytics
Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Configuring Join Conditions for Datasets

NEW QUESTION # 27
You want to use a custom report containing prompts as a source connection for a table. What must you ensure to make this possible?

A. The report is built on an indexed data source.
B. The prompts are mapped at the data change task level.
C. The custom report prompts have default values assigned on the report definition.
D. The prompts are marked as required.

Answer: C

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, when using a custom report with prompts as a source connection for a table, the custom report must be configured to ensure compatibility with the Prism data ingestion process. According to the official Workday Prism Analytics study path documents, the key requirement is that the custom report prompts have default values assigned in the report definition. This is necessary because Prism Analytics does not support interactive prompting during data ingestion. Default values ensure that the report can run automatically without requiring user input, allowing the Data Change task to retrieve the data consistently and load it into the target table.
The other options are not correct in this context:
* A. The report is built on an indexed data source: While indexed data sources can enhance performance for certain reports, they are not a requirement for using a custom report as a source for a Prism table.
* B. The prompts are mapped at the data change task level: Prompts are not mapped in the Data Change task; instead, the task relies on the report's default values to execute the data retrieval.
* D. The prompts are marked as required: Marking prompts as required does not address the need for automatic execution; default values are still needed to avoid manual intervention.
By assigning default values to prompts in the custom report definition, the report can be seamlessly integrated as a source connection for Prism Analytics, ensuring reliable data loading into the table.
References:
Workday Prism Analytics Study Path Documents, Section: Integrating Prism with Workday Reports, Topic:
Using Custom Reports as Data Sources
Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Configuring Custom Reports for Prism Integration

NEW QUESTION # 28
You accidentally delete a Prism calculated field that is used in other Prism calculated fields or conditions.
What is a possible outcome?

A. The system will automatically adjust any dependencies accordingly.
B. Any calculated field referencing the deleted field defaults to zero.
C. Errors will result in any stage or calculated field that references the field.
D. The system will automatically reverse the deletion because the field is referenced elsewhere.

Answer: C

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, calculated fields are often interdependent, with one calculated field referencing another in its expression or being used in conditions within a dataset's transformation stages. According to the official Workday Prism Analytics study path documents, if a calculated field is deleted while other calculated fields or conditions depend on it, the system does not automatically handle the dependency. Instead, this deletion will cause errors in any stage or calculated field that references the deleted field. These errors occur because the dependent calculations or conditions can no longer resolve the reference to the deleted field, leading to failures in the dataset's transformation pipeline or when the dataset is processed or published.
The other options are incorrect:
A: The system will automatically reverse the deletion because the field is referenced elsewhere: Prism Analytics does not have an automatic reversal mechanism for deletions; users must manually restore the field if needed.
B: Any calculated field referencing the deleted field defaults to zero: The system does not default to zero; it will instead throw an error due to the unresolved reference.
D: The system will automatically adjust any dependencies accordingly: Prism does not automatically adjust dependencies; the user must manually update the dependent fields or conditions to resolve the issue.
The resulting errors highlight the importance of carefully managing dependencies when deleting calculated fields, ensuring that all references are updated or removed to avoid disruptions in the dataset's transformation logic.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Managing Calculated Fields and Dependencies Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Impact of Deleting Calculated Fields on Dataset Transformations

NEW QUESTION # 29
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?

A. Mark field A as intermediate calculation.
B. Add a Manage Fields stage to the DDS and hide field B.
C. Delete field A from their DDS and just leave field B.
D. Add a Manage Fields stage to the DDS and hide field A.

Answer: D

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, when a data writer creates an intermediary calculated field (e.g., field A) solely to derive a final calculated field (e.g., field B) in a Derived Dataset (DDS), they may want to exclude the intermediary field from the published output to keep the dataset clean and focused. According to the official Workday Prism Analytics study path documents, the recommended approach is to add a Manage Fields stage to the DDS and hide field A. The Manage Fields stage allows users to control the visibility of fields in the dataset, enabling them to hide fields that are not needed in the final output while retaining their calculations for internal use within the dataset's transformation logic. By hiding field A, field B can still leverage field A's calculations, and only field B will be visible in the published dataset or data source.
The other options are not suitable:
A: Mark field A as intermediate calculation: There is no specific feature in Prism Analytics to "mark" a field as an intermediate calculation; this is not a supported action.
C: Add a Manage Fields stage to the DDS and hide field B: Hiding field B would defeat the purpose, as field B is the intended output to be published.
D: Delete field A from their DDS and just leave field B: Deleting field A would break the calculation of field B, as field B depends on field A, making this option infeasible.
Using the Manage Fields stage to hide field A ensures that the dataset remains functional while presenting only the necessary fields in the final output, aligning with best practices for data transformation and publishing.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Managing Fields in Derived Datasets Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Configuring Field Visibility in Datasets

NEW QUESTION # 30
You want to import a Workday custom report into the data catalog. You have already enabled it as a web service and enabled it for Prism Analytics. What other configuration is required?

A. It must be imported via sFTP.
B. It must be tagged with a Prism Analytics report tag.
C. It must be built as a matrix report.
D. It must be shared with or owned by the user importing the report.

Answer: D

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
To import a Workday custom report into the Prism Analytics Data Catalog, specific configurations are required to ensure the report is accessible and usable. According to the official Workday Prism Analytics study path documents, in addition to enabling the report as a web service and enabling it for Prism Analytics, the report must be shared with or owned by the user who is performing the import. This security requirement ensures that only authorized users can access and import the report into the Data Catalog, aligning with Workday's configurable security model. The user must either be the owner of the report or have it shared with them through appropriate security permissions (e.g., via a security group or direct sharing).
The other options are incorrect:
* A. It must be imported via sFTP: Custom reports are imported directly through Workday's web service integration, not via sFTP, which is typically used for file-based data sources.
* B. It must be built as a matrix report: There is no requirement for the report to be a matrix report; Prism Analytics supports various report types, including advanced and simple reports, as long as they are properly configured.
* D. It must be tagged with a Prism Analytics report tag: Tagging is not a mandatory step for importing a report into the Data Catalog, though it may be used for organizational purposes.
Ensuring that the report is shared with or owned by the importing user is a critical step to maintain security and governance during the integration process.
References:
Workday Prism Analytics Study Path Documents, Section: Integrating Prism with Workday Reports, Topic:
Importing Custom Reports into the Data Catalog
Workday Prism Analytics Training Guide, Module: Datasets and Data Sources, Subtopic: Security Requirements for Report Integration

NEW QUESTION # 31
When using a window function to calculate averages in Prism, what field type must the function operate on?

A. Date
B. Numeric
C. Text
D. Boolean

Answer: B

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, window functions are used to perform calculations across a set of rows, such as calculating averages with a function like AVG. According to the official Workday Prism Analytics study path documents, the AVG window function, which computes the average, must operate on a fieldof type Numeric.
This is because averaging requires numerical values to perform arithmetic operations (e.g., summing the values and dividing by the count of rows). Non-numeric field types, such as Text or Date, cannot be averaged, and Boolean fields (true/false) are not suitable for this type of calculation. For example, a window function like AVG(salary) OVER (PARTITION BY department) would calculate the average salary per department, where "salary" must be a Numeric field.
The other options are incorrect:
* A. Text: Text fields cannot be used for arithmetic operations like averaging.
* B. Boolean: Boolean fields (true/false) are not suitable for calculating averages.
* D. Date: Date fields cannot be directly averaged; they require conversion to a numeric representation (e.
g., days since a reference date) first.
The requirement for a Numeric field type ensures that the AVG window function can perform the necessary mathematical computations accurately.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Window Functions and Field Type Requirements Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Using AVG in Window Functions

NEW QUESTION # 32
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 derived dataset with the PDS suffix.
C. Create a table without the Enable for Analysis checkbox selected.
D. Add a Group By stage to the final derived dataset to add summary calculations.

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 # 33
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?

A. Published rows
B. Discovery board visualizations
C. Upstream tables
D. Upstream datasets

Answer: B

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, unpublishing a dataset to delete a Prism data source requires removing all dependencies that reference the data source. According to the official Workday Prism Analytics study path documents, if you have already deleted Report Writer reports but are still unable to unpublish the dataset, you must also delete any discovery board visualizations that reference the Prism data source (option C). Discovery boards in Workday allow users to create visualizations based on Prism data sources, and these visualizations create a dependency on the data source. If such visualizations exist, the system prevents the dataset from being unpublished until they are removed, ensuring that no downstream dependencies are broken.
The other options are incorrect:
* A. Upstream tables: Upstream tables are the source of data for the dataset, but they are not dependencies of the published data source and do not need to be deleted to unpublish the dataset.
* B. Published rows: Published rows are part of the data source itself and are removed when the dataset is unpublished; they are not a separate dependency to delete.
* D. Upstream datasets: Upstream datasets may feed into the dataset being unpublished, but they are not dependencies of the published data source and do not prevent unpublishing.
Deleting discovery board visualizations ensures all dependencies are cleared, allowing the dataset to be unpublished and the Prism data source to be deleted.
References:
Workday Prism Analytics Study Path Documents, Section: Publishing and Visualizing Data, Topic:
Unpublishing Prism Data Sources
Workday Prism Analytics Training Guide, Module: Publishing and Visualizing Data, Subtopic: Managing Dependencies for Data Source Deletion

NEW QUESTION # 34
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?

A. Manage Fields
B. Explode
C. Group By
D. Unpivot

Answer: B

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, a multi-instance field contains multiple values for a single record (e.g., a list of skills for a worker). To convert each instance of a multi-instance field into a single-instance field, you need a transformation that expands the data into multiple rows, with each row containing one instance. According to the official Workday Prism Analytics study path documents, the Explode stage (option B) is the transformation stage designed for this purpose. The Explode stage takes a multi-instance field and creates a new row for each instance, transforming the multi-instance field into a single-instance field in the output. For example, if a worker has three skills in a multi-instance field, the Explode stage will create three rows, each with a single skill value in a single-instance field.
The other options are incorrect:
* A. Unpivot: Unpivot transforms columns into rows (e.g., converting wide data to long format), but it does not handle multi-instance fields, which are a specific Workday data type.
* C. Manage Fields: The Manage Fields stage modifies field properties (e.g., type, name) but cannot expand a multi-instance field into multiple rows.
* D. Group By: The Group By stage aggregates data (e.g., summing values by a key) but does not convert multi-instance fields into single-instance fields.
The Explode stage is the correct transformation to achieve the conversion of a multi-instance field into a single-instance field by expanding the data into multiple rows.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Handling Multi-Instance Fields with Explode Stages Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Converting Multi-Instance Fields to Single-Instance Fields

NEW QUESTION # 35
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?

A. Use a different source file, as the field types are incompatible.
B. Change the field type in the parsing stage from Numeric to Text.
C. Change the connection type for the data change task.
D. Map the Numeric field to the table Text field.

Answer: D

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, the Data Change task is used to load data from a source file into a table, and it supports flexible field type mapping to accommodate differences between source and target field types.
According to the official Workday Prism Analytics study path documents, when the source file has a Numeric field type and the target table has a Text field type, you can map the Numeric field to the Text field in the Data Change task. Workday Prism Analytics automatically handles the conversion of Numeric values to Text during the data loading process, as Text fields can store Numeric values as strings without data loss.
The other options are not necessary or appropriate:
* A. Use a different source file, as the field types are incompatible: The field types are not incompatible; Prism supports mapping Numeric to Text, making a new source file unnecessary.
* C. Change the field type in the parsing stage from Numeric to Text: The parsing stage defines how the source file is interpreted, but changing the source field type is not required since the mapping handles the conversion.
* D. Change the connection type for the data change task: The connection type (e.g., file upload or Workday report) is unrelated to field type compatibility and does not address the issue.
By mapping the Numeric field to the Text field in the Data Change task, the data can be successfully loaded, leveraging Prism's built-in type conversion capabilities to ensure compatibility.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Field Type Mapping in Data Change Tasks Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Handling Field Type Conversions in Data Loading

NEW QUESTION # 36
The Prism use case is to classify workers based on their pay. You must create a field that evaluates worker pay and returns a value that represents various pay ranges. How would you add this field for inclusion on the Prism data source?

A. Add the additional field to your raw data before you ingest into Prism.
B. Build a CASE calculated field function on the TBL directly to ease later transformation.
C. Build an Evaluate Expression calculated field on your final Prism business object to evaluate workers against their pay.
D. Create a derived dataset and build a CASE calculated field to classify workers against their pay.

Answer: D

NEW QUESTION # 37
You have published a derived dataset to build a Prism data source. For reports using this Prism data source, when is data updated?

A. At reimport into tables and republish of the datasource.
B. At republish of the datasource only.
C. At report runtime.
D. At reimport into tables only.

Answer: A

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, a published Prism data source (PDS) contains a snapshot of data from a derived dataset at the time of publishing. According to the official Workday Prism Analytics study path documents, for reports using a Prism data source, the data is updated at reimport into tables and republish of the datasource (option B). A derived dataset typically sources data from underlying tables (via import stages), and any updates to the source data require two steps: (1) reimporting the updated data into the tables (e.g., via a Data Change task), and (2) republishing the derived dataset to refresh the Prism data source with the new data.
Reports using the PDS will reflect the updated data only after both steps are completed, as the data source is a static snapshot until republished.
The other options are incorrect:
* A. At republish of the datasource only: Republishing alone does not update the data if the underlying tables have not been reimported with new data; both steps are necessary.
* C. At reimport into tables only: Reimporting into tables updates the source data, but the PDS remains unchanged until the dataset is republished.
* D. At report runtime: Reports do not dynamically update the PDS at runtime; they use the data as it exists in the PDS at the time of the last publish.
The combination of reimporting into tables and republishing the data source ensures that reports reflect the most current data.
References:
Workday Prism Analytics Study Path Documents, Section: Publishing and Visualizing Data, Topic: Data Update Process for Prism Data Sources Workday Prism Analytics Training Guide, Module: Publishing and Visualizing Data, Subtopic: Refreshing Data in Prism Data Sources for Reporting

NEW QUESTION # 38
You just imported your table on worker compensation into a derived dataset but before adding any transformation you want to make sure you have no NULL values for the Worker ID field. How can you get this insight?

A. Click on the field name and check the stage statistics.
B. Join on the Worker ID field.
C. Add a Manage Fields stage.
D. Create a Prism calculated field.

Answer: A

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, after importing a table into a derived dataset (DDS), you can inspect the data for quality issues, such as NULL values, before proceeding with transformations. According to the official Workday Prism Analytics study path documents, to check for NULL values in a specific field like Worker ID, the most direct method is to click on the field name and check the stage statistics. When viewing a dataset in the Prism Analytics interface, clicking on a field name (e.g., Worker ID) in the dataset preview displays stage statistics, which include metrics such as the count of NULL values, distinct values, and other data quality indicators. This feature allows users to quickly assess the presence of NULLs without modifying the dataset or adding unnecessary stages.
The other options are not the best approach for this task:
* A. Add a Manage Fields stage: The Manage Fields stage is used to modify field properties (e.g., type, visibility), not to inspect data for NULL values.
* C. Create a Prism calculated field: While a calculated field could be used to flag NULLs (e.g., using ISNULL), this is an indirect and unnecessary step compared to checking stage statistics.
* D. Join on the Worker ID field: Joining with another dataset does not help identify NULL values in the Worker ID field and is irrelevant to this task.
Using stage statistics by clicking on the field name provides a straightforward and efficient way to gain insight into NULL values in the Worker ID field.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Data Quality Checks in Derived Datasets Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Inspecting Data Using Stage Statistics

NEW QUESTION # 39
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?

A. Numeric
B. Text
C. Single-Instance
D. Multi-Instance

Answer: D

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, an Explode stage is used in a derived dataset to transform a multi-instance field into multiple rows, effectively creating single-instance fields for each instance. According to the official Workday Prism Analytics study path documents, the only field type you can select in the Explode stage is Multi-Instance (option B). A multi-instance field, often sourced from Workday data, contains multiple values for a single record (e.g., a list of certifications for a worker). The Explode stage "explodes" this field into separate rows, one for each instance, while converting the multi-instance fieldinto a single-instance field in the output. For example, if a worker has three certifications in a multi-instance field, the Explode stage would create three rows, each with a single certification value.
The other options are incorrect:
* A. Numeric: Numeric fields are single-instance by nature and cannot be exploded, as they do not contain multiple values.
* C. Single-Instance: Single-instance fields contain one value per record and cannot be used in an Explode stage, which requires a multi-instance field to operate.
* D. Text: While a Text field can be single or multi-instance, the Explode stage specifically requires a Multi-Instance field, not just any Text field.
The requirement for a Multi-Instance field in the Explode stage ensures that the transformation can properly expand the data into multiple rows as intended.
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

NEW QUESTION # 40
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