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Best Workday-Prism-Analytics Practice, Online Workday-Prism-Analytics Lab Simulation

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Workday Pro Prism Analytics Exam Sample Questions (Q36-Q41):

NEW QUESTION # 36
You apply an Explode stage to your derived dataset that contains information on your worker benefit elections. What happens in the resulting stage?

A. The number of rows stays the same and the original multi-instance field does not get dropped.
B. The number of rows exponentially increases and the original multi-instance field gets dropped.
C. The number of columns exponentially increases and the original multi-instance field gets dropped.
D. The number of columns stays the same and the original multi-instance field doesn't get dropped.

Answer: B

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, an Explode stage is used to transform a multi-instance field into multiple rows, creating a single-instance field for each instance. According to the official Workday Prism Analyticsstudy path documents, when an Explode stage is applied to a derived dataset containing worker benefit elections (a multi-instance field, e.g., a list of elected benefits per worker), the following occurs: the number of rows exponentially increases, and the original multi-instance field gets dropped (option D).
For example, if a worker has three benefit elections in a multi-instance field, the Explode stage will create three rows-one for each election-while the original multi-instance field (e.g., "Benefit Elections") is replaced by a single-instance field containing one election per row. The number of rows increases based on the number of instances in the multi-instance field (e.g., a dataset with 100 workers, each with 3 elections on average, would grow from 100 rows to 300 rows). The term "exponentially" in the question reflects this potential for significant row growth, though the increase is technically linear per record based on the number of instances.
The other options are incorrect:
* A. The number of columns stays the same and the original multi-instance field doesn't get dropped: The original multi-instance field is dropped and replaced by a single-instance field; the column count may change slightly due to this replacement.
* B. The number of columns exponentially increases and the original multi-instance field gets dropped:
The Explode stage does not increase the number of columns exponentially; it primarily affects rows, with minimal impact on columns.
* C. The number of rows stays the same and the original multi-instance field does not get dropped: The number of rows increases due to the explosion of multi-instance data, and the original field is dropped.
The Explode stage's behavior of increasing rows and dropping the original multi-instance field aligns with its purpose of normalizing multi-instance data into a row-based structure.
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 # 37
A Prism data administrator combined data from multiple sources down to a final derived dataset, including current worker data. There is a new requirement to append historical worker data to the dataset in a uniform layout. The historical worker data includes some, but not all, fields that align withthe current worker data.
Using current worker data as the primary pipeline, how can the historical worker data points be brought in?

A. Add a Union stage.
B. Add a Join stage with a Left Outer Join.
C. Add a Join stage with an Inner Join.
D. Add a Join stage with a Right Outer Join.

Answer: A

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, when the goal is to append data from one dataset to another in a uniform layout, such as combining current worker data with historical worker data, a Union stage is the appropriate transformation. According to the official Workday Prism Analytics study path documents, a Union stage is used to append rows from one pipeline to another, stacking the data vertically while aligning fields based on their names and types. In this scenario, the current worker data (primary pipeline) and historical worker data (secondary pipeline) share some fields, and a Union stage will combine the rows from both datasets into a single dataset. Fields that exist in one pipeline but not the other will have NULL values for the rows where they are not present, ensuring a uniform layout without losing data.
The other options are not suitable for this requirement:
* A. Add a Join stage with a Right Outer Join: A Right Outer Join would include all rows from the historical worker data and only matching rows from the current worker data, which does not align with the goal of appending all data in a uniform layout.
* C. Add a Join stage with a Left Outer Join: A Left Outer Join would include all rows from the current worker data and matching rows from the historical worker data, but this is not an append operation; it's a matching operation based on a join condition, which isn't specified here.
* D. Add a Join stage with an Inner Join: An Inner Join would only include rows where matches exist between the two datasets, potentially excluding non-matching historical or current worker data, which does not meet the requirement to append all data.
The Union stage is the correct approach to append historical worker data to the current worker data, ensuring all rows are included in a uniform layout, with NULLs filling in for missing fields.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Using Union Stages to Append Data in Prism Analytics Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Combining Datasets with Union Operations

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

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

Answer: B

Explanation:
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

NEW QUESTION # 39
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. The View Dataset Lineage report.
D. Any table in the lineage.

Answer: C

Explanation:
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

NEW QUESTION # 40
What is the primary purpose of window functions in Prism?

A. To perform calculations across a set of rows related to the current row while partitioning the data.
B. To filter rows based on specified conditions.
C. To provide row-level access control.
D. To manipulate strings and dates within a query.

Answer: A

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 # 41
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