Pass the Workday Reporting and Analytics Workday-Prism-Analytics Questions and answers with CertsForce

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:

When importing data into Workday Prism Analytics from a Workday report, including Workday instance field types in the report is critical for enabling specific functionality in the resulting Prism data source. According to the official Workday Prism Analytics study path documents, including instance field types allows the final Prism data source to support drilling into Workday objects. Instance field types represent references to Workday business objects (e.g., Worker, Position, or Organization), and including them in the report ensures that the Prism data source retains the ability to navigate to these objects within Workday’s reporting and analytics framework. This enables users to perform drill-down actions, such as accessing detailed object data directly from Prism visualizations or reports.

The other options do not accurately reflect the primary benefit of including instance field types:

B. Performance is improved in the final Prism datasource when published: Instance field types do not directly impact the performance of the published data source; performance is more influenced by data volume and indexing.

C. Unions are more easily performed with instance field types: Unions depend on schema compatibility, not instance field types, which are specific to Workday object references.

D. Joins are more easily performed with instance field types: While instance field types can be used in joins, their primary purpose is to enable object navigation, not to simplify join operations.

By including instance field types, the Prism data source gains enhanced interactivity, allowing users to leverage Workday’s object model for deeper analysis and navigation.

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 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.