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NEW QUESTION # 25
When joining datasets, what items must match?
- A. The field names for the Match Row fields.
- B. The level of detail in each dataset.
- C. The field types for the Match Row fields.
- D. The number of rows in each dataset.
Answer: C
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 # 26
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 manually recreated.
- C. The report definition remains intact and will work after republishing.
- D. The report definition will need to be edited to reflect changes.
Answer: C
Explanation:
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
NEW QUESTION # 27
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 Advanced Filter conditions.
- C. By creating a Custom Example.
- D. By using Simple Filter conditions.
Answer: B
Explanation:
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
NEW QUESTION # 28
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. Create a Prism calculated field.
- C. Join on the Worker ID field.
- D. Add a Manage Fields stage.
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 # 29
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. Build an Evaluate Expression calculated field on your final Prism business object to evaluate workers against their pay.
- B. Build a CASE calculated field function on the TBL directly to ease later transformation.
- C. Add the additional field to your raw data before you ingest into Prism.
- 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 # 30
What is the primary purpose of window functions in Prism?
- A. To manipulate strings and dates within a query.
- B. To provide row-level access control.
- C. To perform calculations across a set of rows related to the current row while partitioning the data.
- D. To filter rows based on specified conditions.
Answer: C
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 # 31
What task or report should you access to view a Prism data source?
- A. Edit Dataset Transformations task
- B. Edit Data Source Security task
- C. View Dataset Details report
- D. View Prism Data Source report
Answer: D
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 # 32
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?
- A. Extract Single Instance
- B. Arithmetic Calculation
- C. Lookup Field with Prompts
- D. Lookup Related Value
Answer: B
Explanation:
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
NEW QUESTION # 33
You have a number of Workday reports that use a Prism data source. When are the values of the Prism calculated fields in the Workday reports calculated?
- A. At dataset creation time.
- B. At the calculated field creation time.
- C. At time of publishing.
- D. At report run time.
Answer: C
NEW QUESTION # 34
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. Add a Manage Fields stage to the DDS and hide field B.
- B. Delete field A from their DDS and just leave field B.
- C. Mark field A as intermediate calculation.
- 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 # 35
For a Prism use case, you have two datasets: one contains daily sales data, and the other contains monthly budget allocations. Before performing a join between these datasets, what transformation stage should you apply to the sales data to ensure it matches the granularity of the budget data?
- A. Union
- B. Filter
- C. Group By
- D. Manage Fields
Answer: C
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, joining datasets with different levels of granularity requires aligning their granularity to ensure a meaningful match. The sales data is at a daily level (one row per day), while the budget data is at a monthly level (one row per month). According to the official Workday Prism Analytics study path documents, to match the granularity of the monthly budget data, you should apply a Group By stage to the sales data (option B). The Group By stage aggregates the daily sales data into monthly totals (e.g., summing sales amounts by month), reducing the granularity from daily to monthly. This allows the sales data to be joined with the monthly budget data on a common key, such as the month.
For example, a Group By stage could group the sales data by a derived month field (e.g., using a function like EXTRACT(YEAR_MONTH, sale_date)) and aggregate the sales amounts using a function like SUM (sales_amount). The resulting dataset would have one row per month, matching the budget data's granularity.
The other options are incorrect:
* A. Union: A Union stage appends rows from one dataset to another but does not change granularity; it cannot aggregate daily data into monthly data.
* C. Manage Fields: The Manage Fields stage modifies field properties (e.g., type, name) but does not aggregate data to change granularity.
* D. Filter: A Filter stage removes rows based on conditions but does not aggregate data to align granularity levels.
The Group By stage is the appropriate transformation to align the sales data's granularity with the monthly budget data for a successful join.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Aligning Granularity for Joins in Prism Analytics Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Using Group By Stages for Data Aggregation
NEW QUESTION # 36
What window function returns the number of rows within a window?
- A. AVG
- B. MAX
- C. SUM
- D. COUNT
Answer: D
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, window functions are used to perform calculations over a defined set of rows (a
"window"). According to the official Workday Prism Analytics study path documents, the COUNT window function is used to return the number of rows within a specified window. When applied in a dataset transformation, the COUNT function counts the rows that fall within the window, which can be defined by partitioning (e.g., by a specific column) and ordering criteria. For example, COUNT(*) OVER (PARTITION BY department) would return the number of rows for each department in the dataset.
The other options serve different purposes:
A: MAX: Returns the maximum value within the window, not the number of rows.
B: SUM: Calculates the sum of a numeric field across the window, not the row count.
D: AVG: Computes the average of a numeric field within the window, not the row count.
The COUNT function is specifically designed to provide the row count, making it the correct choice for this purpose in Prism Analytics transformations.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Window Functions and Their Applications Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Using COUNT in Window Functions
NEW QUESTION # 37
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. Build an Evaluate Expression calculated field on your final Prism business object to evaluate workers against their pay.
- B. Build a CASE calculated field function on the TBL directly to ease later transformation.
- C. Add the additional field to your raw data before you ingest into Prism.
- 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 # 38
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. Single-Instance
- B. Numeric
- C. Multi-Instance
- D. Text
Answer: C
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 # 39
What security domain enables the ability to create a dataset?
- A. Prism Datasets: Publish
- B. Prism: Tables Create
- C. Prism: Manage Data Source
- D. Prism Datasets: Create
Answer: D
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, the ability to create a dataset is governed by specific security domains within the Prism Analytics functional area. According to the official Workday Prism Analytics study path documents, the security domain that explicitly enables users to create datasets is the "Prism Datasets: Create" domain.
This domain grants users the necessary permissions to initiate the creation of both base and derived datasets within the Prism Analytics Data Catalog.
The process of creating a dataset involves defining the metadata and processing logic to manipulate data, which can include Workday or external (non-Workday) data sources. The "Prism Datasets: Create" domain ensures that only authorized users, such as Prism data analysts or administrators, can perform this task, aligning with Workday's configurable security framework. Other domains, such as "Prism Datasets: Publish," are responsible for publishing datasets to make them available as Prism Data Sources for reporting, while
"Prism: Manage Data Source" pertains to managing the data sources themselves, not creating datasets.
Similarly, "Prism: Tables Create" is related to creating tables, which is a distinct entity from datasets in Prism Analytics.
This distinction is critical, as datasets and tables serve different purposes in the data management workflow.
Datasets include metadata and a subset of example rows, while tables contain metadata and all data rows. The
"Prism Datasets: Create" domain is specifically designed to control access to dataset creation, ensuring secure and governed data preparation.
References:
Workday Prism Analytics Study Path Documents, Section: Security and Governance in Prism Analytics, Topic: Security Domains and Permissions Workday Prism Analytics Training Guide, Module: Datasets and Data Sources, Subtopic: Creating Datasets and Associated Security
NEW QUESTION # 40
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. Click on the Related Actions next to the business object in the insight panel.
- B. Add a Manage Fields after the Explode stage and modify the business object.
- C. Add a Manage Fields before the Explode stage and modify the business object.
- D. Select from the list of suggested BO values in the Explode stage configuration.
Answer: B
Explanation:
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
NEW QUESTION # 41
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 # 42
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. Upstream tables
- C. Upstream datasets
- D. Discovery board visualizations
Answer: D
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 # 43
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