Workday-Prism-Analytics試験問題集合格させるのは2026年最新の認証済み試験問題 [Q27-Q44]

Workday-Prism-Analytics試験問題集合格させるのは2026年最新の認証済み試験問題

Workday-Prism-Analytics試験問題でリアルに更新された問題PDF

質問 # 27
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?

• A. Output Name
• B. Input Name
• C. Input Type
• D. Output Type

正解：D

解説：
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, the TO_DATE function in a calculated field is used to convert a string or compatible data type into a date. However, in this scenario, the field from Workday is numeric, and the TO_DATE function typically requires a string input (e.g., a numeric value like 20230101 needs to be converted to a string like "20230101" before applying TO_DATE). According to the official Workday Prism Analytics study path documents, to prepare the numeric field for use with the TO_DATE function, you must first use a Manage Fields stage to change the field's Output Type to Text. The Manage Fields stage allows you to modify the field's properties, and changing the Output Type from Numeric to Text converts the numeric values into a string format that the TO_DATE function can then process (e.g., TO_DATE ([Field_Name], "YYYYMMDD")).
The other options are not relevant:
* B. Output Name: Changing the Output Name renames the field but does not address the field type compatibility required for the TO_DATE function.
* C. Input Type: The Manage Fields stage does not modify an "Input Type"; it adjusts the Output Type to transform the field as it moves through the pipeline.
* D. Input Name: There is no "Input Name" property in the Manage Fields stage; this option is not applicable.
By changing the Output Type to Text in the Manage Fields stage, the numeric field is converted to a string, making it compatible with the TO_DATE function for creating a date field in the calculated field.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Field Type Transformations for Calculated Fields Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Using Manage Fields for Data Type Conversions

質問 # 28
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. Group By
• B. Manage Fields
• C. Unpivot
• D. Explode

正解：D

解説：
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

質問 # 29
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 only.
• B. At reimport into tables and republish of the datasource.
• C. At report runtime.
• D. At republish of the datasource only.

正解：B

解説：
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

質問 # 30
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?

• A. The table or dataset where the calculated field was created.
• B. Any dataset in the lineage.
• C. Any table in the lineage.
• D. The View Dataset Lineage report.

正解：D

解説：
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, calculated fields are defined within datasets, and their expressions dictate the logic used to compute their values. When issues like nil results arise, an administrator needs a centralized view to review and troubleshoot these expressions. According to the official Workday Prism Analytics study path documents, the View Dataset Lineage report is the tool that allows users to review the lineage of datasets, including the expressions of calculated fields, in bulk. This report provides a visual representation of the data lineage, showing the relationships between tables, datasets, and calculated fields, and allows users to drill into the details of each dataset to inspect the expressions of calculated fields across the lineage.
The other options are not as effective for this purpose:
A: The table or dataset where the calculated field was created: While you can review expressions in the specific dataset where a calculated field was created, this approach does not allow for a bulk review across multiple datasets in the lineage.
C: Any table in the lineage: Tables store raw data and do not contain calculated field expressions, which are defined in datasets.
D: Any dataset in the lineage: Reviewing datasets individually does not provide a bulk view of all calculated fields across the lineage, making it less efficient than the View Dataset Lineage report.
The View Dataset Lineage report is the most efficient way to review and troubleshoot calculated field expressions in bulk, enabling the administrator to identify and revise the problematic expressions causing nil results.
References:
Workday Prism Analytics Study Path Documents, Section: Datasets and Data Sources, Topic: Using View Dataset Lineage for Troubleshooting Workday Prism Analytics Training Guide, Module: Datasets and Data Sources, Subtopic: Managing Calculated Fields in Data Lineage

質問 # 31
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?

• A. The report definition will be copied and a new version will appear after republishing.
• B. The report definition will need to be edited to reflect changes.
• C. The report definition will need to be manually recreated.
• D. The report definition remains intact and will work after republishing.

正解：D

解説：
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, deleting published rows from a Prism data source (PDS) is a step taken to correct errors in the published data, often followed by republishing the dataset with corrected data. According to the official Workday Prism Analytics study path documents, when you delete the published rows, the report definition remains intact and will work after republishing (option A). The custom report's definition, which is based on the Prism data source, is not affected by the deletion of published rows because the report definition references the data source's structure (e.g., fields and metadata), not the specific data rows. Once the dataset is republished with the corrected data, the report will automatically reflect the updated data without requiring any changes to the report definition, assuming the structure of the data source remains the same.
The other options are incorrect:
* B. The report definition will need to be manually recreated: The report definition is not deleted or invalidated by deleting published rows, so recreation is not necessary.
* C. The report definition will be copied and a new version will appear after republishing: Workday does not automatically copy or version report definitions when a data source is republished.
* D. The report definition will need to be edited to reflect changes: No edits are required unless the structure of the data source (e.g., field names or types) changes, which is not indicated in this scenario.
The report definition's integrity is maintained, and it will function as expected after republishing the corrected data.
References:
Workday Prism Analytics Study Path Documents, Section: Publishing and Visualizing Data, Topic: Impact of Data Source Updates on Reports Workday Prism Analytics Training Guide, Module: Publishing and Visualizing Data, Subtopic: Managing Data Corrections in Prism Data Sources

質問 # 32
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?

• A. Left Outer Join
• B. Full Outer Join
• C. Inner Join
• D. Right Outer Join

正解：A

解説：
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

質問 # 33
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?

• A. By adding a Manage Fields stage.
• B. By using Simple Filter conditions.
• C. By creating a Custom Example.
• D. By using Advanced Filter conditions.

正解：D

解説：
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

質問 # 34
You want to remove data within a Prism data source without deleting any dependent custom reports. What task can you use to do this?

• A. Unpublish Dataset
• B. Delete Dataset
• C. Delete Published Rows
• D. Inactivate Dataset

正解：C

解説：
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, removing data from a Prism data source (PDS) without affecting dependent custom reports requires a careful approach to preserve the data source's structure and dependencies.
According to the official Workday Prism Analytics study path documents, the task to use is Delete Published Rows (option D). This task removes the data rows within the Prism data source while keeping the data source' s metadata (e.g., field definitions) and structure intact. Since custom reports depend on the data source's structure rather than the specific data rows, deleting the published rows will not break the reports. After deleting the rows, you can republish the dataset with updated data, and the reports will continue to function with the new data, assuming the structure remains unchanged.
The other options are incorrect:
* A. Inactivate Dataset: Inactivating a dataset disables it but does not remove data from the published data source, and it may still affect reports by making the data source inaccessible.
* B. Delete Dataset: Deleting the dataset entirely will also delete the Prism data source, breaking any dependent custom reports.
* C. Unpublish Dataset: Unpublishing the dataset removes the Prism data source, which will break dependent reports until the dataset is republished.
The Delete Published Rows task ensures that data is removed from the Prism data source without impacting the dependent custom reports, allowing for seamless data updates.
References:
Workday Prism Analytics Study Path Documents, Section: Publishing and Visualizing Data, Topic: Managing Data in Prism Data Sources Workday Prism Analytics Training Guide, Module: Publishing and Visualizing Data, Subtopic: Removing Data Without Breaking Report Dependencies

質問 # 35
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?

• A. Select from the list of suggested BO values in the Explode stage configuration.
• B. Add a Manage Fields after the Explode stage and modify the business object.
• C. Click on the Related Actions next to the business object in the insight panel.
• D. Add a Manage Fields before the Explode stage and modify the business object.

正解：B

解説：
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

質問 # 36
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 custom report prompts have default values assigned on the report definition.
• B. The prompts are marked as required.
• C. The prompts are mapped at the data change task level.
• D. The report is built on an indexed data source.

正解：A

解説：
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

質問 # 37
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 the imported pipeline will have NULL values.
• B. The row will be omitted.
• C. A duplicate row will be generated.
• D. Included fields from both pipelines will have NULL values.

正解：A

解説：
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

質問 # 38
What report can you run to edit and maintain your Prism import and publish schedules?

• A. Prism Management Console
• B. Scheduled Future Processes
• C. Prism Activities Monitor
• D. Prism Usage

正解：B

解説：
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, managing schedules for importing data into tables or publishing datasets as Prism data sources is a key administrative task. According to the official Workday Prism Analytics study path documents, the Scheduled Future Processes report (option A) is the tool used to edit and maintain Prism import and publish schedules. This report provides a centralized view of all scheduled processes in Workday, including Prism-related tasks such as Data Change tasks (for imports) and dataset publish schedules. Users can access this report to view, edit, or cancel scheduled processes, ensuring that data imports and publishes occur at the desired frequency and time.
The other options are incorrect:
* B. Prism Management Console: The Prism Management Console provides an overview of Prism activities and resources but does not allow for editing or maintaining schedules.
* C. Prism Activities Monitor: This report monitors the status of Prism activities (e.g., running or completed tasks) but does not manage schedules.
* D. Prism Usage: The Prism Usage report tracks usage metrics for Prism Analytics but does not handle scheduling tasks.
The Scheduled Future Processes report is the correct tool for managing Prism import and publish schedules, ensuring efficient data updates.
References:
Workday Prism Analytics Study Path Documents, Section: Publishing and Visualizing Data, Topic: Managing Import and Publish Schedules Workday Prism Analytics Training Guide, Module: Publishing and Visualizing Data, Subtopic: Using Scheduled Future Processes for Prism Tasks

質問 # 39
When joining datasets, what items must match?

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

正解：A

解説：
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

質問 # 40
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 built as a matrix report.
• B. It must be tagged with a Prism Analytics report tag.
• C. It must be imported via sFTP.
• D. It must be shared with or owned by the user importing the report.

正解：D

解説：
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

質問 # 41
You created a derived dataset that imports data from a table, which will become your Stage 1. What can you add to this dataset?

• A. Up to two Manage Fields transformation stages.
• B. Up to five transformation stages.
• C. As many transformation stages of any type as your scenario requires.
• D. As many transformation stages of any type as long as they are in a particular order.

正解：C

解説：
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, a derived dataset (DDS) allows users to transform data by adding various transformation stages after the initial import stage (Stage 1). According to the official Workday Prism Analytics study path documents, you can add as many transformation stages of any type as your scenario requires (option A). Prism Analytics supports a variety of transformation stages, such as Join, Union, Filter, Manage Fields, and Calculate Field, among others. There are no strict limits on the number of stages or their types, and they can be added in any order that makes sense for the data transformation logic, as long as the stages are configured correctly to produce the desired output. This flexibility allows users to build complex transformation pipelines tailored to their specific use case.
The other options are incorrect:
* B. As many transformation stages of any type as long as they are in a particular order: While the order of stages matters for the transformation logic (e.g., a Filter before a Join), there is no predefined order requirement for all stages; the order depends on the scenario.
* C. Up to five transformation stages: There is no limit of five transformation stages in Prism Analytics; you can add more as needed.
* D. Up to two Manage Fields transformation stages: There is no restriction to only two Manage Fields stages; you can add as many as required.
The ability to add as many transformation stages as needed provides maximum flexibility in shaping the data within a derived dataset.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Building Transformation Pipelines in Derived Datasets Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Adding and Configuring Transformation Stages

質問 # 42
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?

• A. Change the field type of Employee ID directly on the Employee Data TBL from text to numeric.
• B. Change the field type of Employee ID directly on the Learner Data TBL from Numeric to Text.
• C. 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.
• D. 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.

正解：D

解説：
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

質問 # 43
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?

• A. Naming convention
• B. Source
• C. Schema
• D. Size

正解：C

解説：
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, a Data Change task is used to load or update data into a table, which can involve importing data from multiple source files. According to the official Workday Prism Analytics study path documents, when loading rows from multiple source files into an empty table, the source files must share the same schema. The schema defines the structure of the data, including the column names, data types, and their order, which ensures that the data from all source files can be consistently mapped and loaded into the target table without errors.
The schema is critical because the Data Change task relies on a predefined table structure to process the incoming data. If the schemas of the source files differ (e.g., different column names or data types), the task will fail due to inconsistencies in data mapping. The other options are not required to be the same:
* Source: The source files can originate from different systems or locations (e.g., Workday, external systems, or file uploads) as long as the schema aligns.
* Naming convention: The names of the source files do not need to follow a specific convention for the Data Change task to process them.
* Size: The size of the source files (e.g., number of rows or file size) can vary, as the task processes the data based on the schema, not the volume.
Thus, the requirement for the source files to have the same schema ensures seamless data loading into the table, maintaining data integrity and consistency during the transformation process.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Data Change Tasks and Schema Requirements Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Loading Data into Tables Using Data Change Tasks

質問 # 44
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