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NEW QUESTION # 42
You want to remove data within a Prism data source without deleting any dependent custom reports. What task can you use to do this?
Answer: A
Explanation:
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
NEW QUESTION # 43
You are a new Prism customer and you want to ensure the correct set of fields is brought into a derived dataset. When should you apply a Manage Fields stage?
Answer: D
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, a Manage Fields stage is used to control the fields in a dataset by renaming, hiding, or changing field types, among other actions. According to the official Workday Prism Analytics study path documents, to ensure the correct set of fields is brought into a derived dataset (DDS), the Manage Fields stage should be applied at the beginning of the Primary Pipeline of the derived dataset (option C).
Placing the Manage Fields stage early in the pipeline-right after the initial import stage (Stage 1)-allows you to define the field structure upfront, ensuring that subsequent transformationstages (e.g., Join, Filter, Calculate Field) operate on the desired set of fields. This approach helps maintain consistency and avoids unnecessary processing of fields that are not needed in later stages.
The other options are not optimal:
* A. After the dataset is published: You cannot add transformation stages like Manage Fields after a dataset is published; transformations must be applied during the dataset's creation or editing.
* B. At the end of the Primary Pipeline of a published dataset: Similar to option A, you cannot modify a published dataset's pipeline, and placing Manage Fields at the end would not prevent unnecessary fields from being processed in earlier stages.
* D. At the beginning of the primary pipeline of the Base Dataset: A Base Dataset does not have a transformation pipeline; it is a direct import of a table, so Manage Fields stages can only be applied in a Derived Dataset.
Applying the Manage Fields stage at the beginning of the derived dataset's Primary Pipeline ensures efficient data preparation and transformation.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Using Manage Fields in Derived Datasets Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Best Practices for Field Management in Pipelines
NEW QUESTION # 44
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?
Answer: B
Explanation:
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
NEW QUESTION # 45
You want to configure access to a published Prism data source to use it in reporting and discovery boards.
What action must you take?
Answer: B
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, configuring access to a published Prism data source for use in reporting and discovery boards requires managing its security settings. According to the official Workday Prism Analytics study path documents, the necessary action is to edit the data source security and select a domain (option A).
After a dataset is published as a Prism data source, access is controlled through security domains. By editing the data source security and assigning it to an appropriate security domain (e.g., a domain that grants access to specific user groups like report writers or analysts), you ensure that authorized users can access the data source for reporting and discovery boards. This aligns with Workday's configurable security framework, ensuring that only users with the appropriate permissions can view or use the data source.
The other options are incorrect:
* B. Share the dataset with appropriate users: Sharing the dataset itself does not grant access to the published Prism data source; access to the data source is controlled through its security settings, not the dataset's sharing settings.
* C. Share the imported Workday report to provide users with access to the published Prism data source:
Sharing an imported Workday report does not affect access to the Prism data source; the data source's security must be configured directly.
* D. Schedule the recurring publish process: Scheduling a recurring publish process ensures the data source is updated regularly, but it does not configure access for reporting or discovery boards.
Editing the data source security and selecting a domain is the critical step to enable access for reporting and discovery boards.
References:
Workday Prism Analytics Study Path Documents, Section: Security and Governance in Prism, Topic:
Configuring Access to Prism Data Sources
Workday Prism Analytics Training Guide, Module: Security and Governance in Prism, Subtopic: Managing Data Source Security for Reporting
NEW QUESTION # 46
You have to blend two sources of data. Your matching field is Employee ID, which is a text-type field in Pipeline 1, but is numeric in Pipeline 2. How do you prepare your data for blending?
Answer: D
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, blending two data sources typically involves joining them on a common field, such as Employee ID in this case. However, the Employee ID field is text in Pipeline 1 and numeric in Pipeline 2, which means the field types must be aligned before a join can be performed to avoid data mismatches or errors. According to the official Workday Prism Analytics study path documents, the correct approach is to first use a Manage Fields stage to change the field type of Employee ID in one of the pipelines to match the other (e.g., convert the numeric Employee ID in Pipeline 2 to text, as text can safely store numeric values without data loss), and then perform a Join stage to blend the data (option C). Converting from numeric to text is preferred because converting text to numeric risks data loss if the text field contains non- numeric characters.
The other options are not appropriate:
* A. Add a Manage Fields to change the field type and then Union: A Union appends rows vertically and does not blend data based on a matching field like Employee ID; blending typically requires a Join.
* B. Add a Filter first and then a Manage Fields to change the field type: Adding a Filter stage is unnecessary for preparing the field types for a join and does not address the blending requirement.
* D. Add a Join first and then a Manage Fields to change the field type: Performing the Join first will fail or produce incorrect results because the field types (text and numeric) are incompatible for joining; the types must be aligned before the Join.
By using a Manage Fields stage to change the field type first and then performing a Join, the data from both pipelines can be blended accurately on the Employee ID field.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Preparing Data for Joins in Prism Analytics Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Field Type Transformations for Data Blending
NEW QUESTION # 47
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