Workday Workday Pro Prism Analytics Exam Workday-Prism-Analytics Exam Dumps: Updated Questions & Answers (October 2025)

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.

Comprehensive and Detailed Explanation From Exact Extract:

In Workday Prism Analytics, a Stage Alert in the View Dataset Lineage report indicates an issue with the dataset’s transformation pipeline, such as a disconnected pipeline resulting from changing the imported pipeline in a Join stage. According to the official Workday Prism Analytics study path documents, a disconnected pipeline occurs when a pipeline (e.g., a table or dataset) is no longer referenced by any transformation stage, often after modifying the Join stage to use a different imported pipeline. To resolve this alert, the recommended action is to delete the disconnected pipeline (option D). By removing the disconnected pipeline from the dataset, the lineage is updated to reflect only the active pipelines, and the Stage Alert will disappear, indicating that the dataset’s configuration is now valid.

The other options are not appropriate:

A. Add a Manage Fields stage and re-attach the pipeline: A Manage Fields stage modifies field properties and cannot re-attach a disconnected pipeline to the Join stage.

B. Publish the derived dataset: Publishing the dataset does not resolve the issue of a disconnected pipeline; the alert will persist until the pipeline is addressed.

C. Change the imported pipeline to a different one: This does not address the disconnected pipeline; it only changes the Join stage’s configuration again, potentially causing further issues.

Deleting the disconnected pipeline ensures the dataset’s lineage is clean and free of errors, resolving the Stage Alert in the View Dataset Lineage report.

To add or update the description of a derived dataset in Workday Prism Analytics, you should access the Edit Dataset Transformations task. This can be done by selecting the Related Actions next to the dataset name and choosing Edit Transformations. This method allows you to modify various aspects of the dataset, including its description.

This process is outlined in the Workday Prism Analytics User Guide, which states:

"If you have permission to edit a dataset, you can access the Edit Dataset Transformations task using these methods:

• Right-click the dataset name on the Data Catalog report and select Edit Transformations.

• Select Edit Transformations from the Quick Actions on the View Dataset Details report.

• Access the Edit Dataset task and select the dataset name that you want to edit."

Once in the Edit Dataset Transformations task, you can update the dataset's description by clicking on the configuration icon (often represented as a gear or pencil icon) and editing the description field.

Comprehensive and Detailed Explanation From Exact Extract:

In Workday Prism Analytics, a Filter stage in a derived dataset is used to include only rows that meet specific criteria. The requirement here is to show expense reports that satisfy two conditions: (1) submitted in the current month, and (2) total amount higher than 2000 USD. According to the official Workday Prism Analytics study path documents, this can be achieved by using a simple filter with two conditions and the "If All" operator (option A).

The first condition would check the submission date, using a function like MONTH() to compare with the current month (e.g., MONTH(submission_date) = MONTH(CURRENT_DATE())). The second condition would compare the total amount (e.g., total_amount > 2000). The "If All" operator ensures that both conditions must be true for a row to be included, which aligns with the requirement that both criteria (current month AND amount > 2000 USD) must be met. A simple filter is sufficient because the logic involves straightforward comparisons without nested conditions.

The other options are incorrect:

B. Use a simple filter, two conditions, and "If Any" operator: The "If Any" operator would include rows where either condition is true (e.g., submitted in the current month OR amount > 2000 USD), which does not meet the requirement for both conditions to be true.

C. Use a simple filter, three conditions, and "If All" operator: Only two conditions are needed (submission month and amount), so three conditions are unnecessary.

D. Use a simple filter, three conditions, and "If Any" operator: This combines the issues of option B (wrong operator) and option C (too many conditions).

Using a simple filter with two conditions and the "If All" operator ensures the dataset includes only the expense reports that meet both criteria.

Comprehensive and Detailed Explanation From Exact Extract:

In Workday Prism Analytics, calculating the total purchase amount for each customer requires aggregating data by customer ID. According to the official Workday Prism Analytics study path documents, the appropriate transformation stage for this task is a Group By stage (option C). The Group By stage allows you to group the dataset by a specific field (e.g., customer ID) and apply aggregation functions, such as SUM, to calculate the total purchase amount for each customer. For example, you would group by customer ID and use SUM(purchase_amount) to compute the total. This stage reduces the dataset to one row per customer, with the aggregated total purchase amount, enabling the desired analysis over the entire period.

The other options are incorrect:

A. Join: A Join stage combines data from two datasets based on a matching condition, but it does not aggregate data to calculate totals.

B. Union: A Union stage appends rows from one dataset to another, which does not help with calculating totals per customer.

D. Explode: An Explode stage transforms multi-instance fields into multiple rows, which is unrelated to aggregating purchase amounts.

The Group By stage is the correct choice to aggregate purchase amounts by customer, facilitating the analysis of totals over the entire period.

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.

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.

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.

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.

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.