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Workday Pro Prism Analytics Exam Sample Questions (Q37-Q42):

NEW QUESTION # 37
You created a derived dataset that imports data from a table, which will become your Stage 1. What can you add to this dataset?

A. Up to two Manage Fields transformation stages.
B. As many transformation stages of any type as your scenario requires.
C. Up to five transformation stages.
D. As many transformation stages of any type as long as they are in a particular order.

Answer: B

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, a derived dataset (DDS) allows users to transform data by adding various transformation stages after the initial import stage (Stage 1). According to the official Workday Prism Analytics study path documents, you can add as many transformation stages of any type as your scenario requires (option A). Prism Analytics supports a variety of transformation stages, such as Join, Union, Filter, Manage Fields, and Calculate Field, among others. There are no strict limits on the number of stages or their types, and they can be added in any order that makes sense for the data transformation logic, as long as the stages are configured correctly to produce the desired output. This flexibility allows users to build complex transformation pipelines tailored to their specific use case.
The other options are incorrect:
* B. As many transformation stages of any type as long as they are in a particular order: While the order of stages matters for the transformation logic (e.g., a Filter before a Join), there is no predefined order requirement for all stages; the order depends on the scenario.
* C. Up to five transformation stages: There is no limit of five transformation stages in Prism Analytics; you can add more as needed.
* D. Up to two Manage Fields transformation stages: There is no restriction to only two Manage Fields stages; you can add as many as required.
The ability to add as many transformation stages as needed provides maximum flexibility in shaping the data within a derived dataset.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Building Transformation Pipelines in Derived Datasets Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Adding and Configuring Transformation Stages

NEW QUESTION # 38
You want to convert each instance of a multi-instance field and convert it to a single-instance field. What transformation stage can you use to do this?

A. Explode
B. Manage Fields
C. Group By
D. Unpivot

Answer: A

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, a multi-instance field contains multiple values for a single record (e.g., a list of skills for a worker). To convert each instance of a multi-instance field into a single-instance field, you need a transformation that expands the data into multiple rows, with each row containing one instance. According to the official Workday Prism Analytics study path documents, the Explode stage (option B) is the transformation stage designed for this purpose. The Explode stage takes a multi-instance field and creates a new row for each instance, transforming the multi-instance field into a single-instance field in the output. For example, if a worker has three skills in a multi-instance field, the Explode stage will create three rows, each with a single skill value in a single-instance field.
The other options are incorrect:
* A. Unpivot: Unpivot transforms columns into rows (e.g., converting wide data to long format), but it does not handle multi-instance fields, which are a specific Workday data type.
* C. Manage Fields: The Manage Fields stage modifies field properties (e.g., type, name) but cannot expand a multi-instance field into multiple rows.
* D. Group By: The Group By stage aggregates data (e.g., summing values by a key) but does not convert multi-instance fields into single-instance fields.
The Explode stage is the correct transformation to achieve the conversion of a multi-instance field into a single-instance field by expanding the data into multiple rows.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Handling Multi-Instance Fields with Explode Stages Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Converting Multi-Instance Fields to Single-Instance Fields

NEW QUESTION # 39
Why should you include Workday instance field types in the Workday report that you use to import data into Prism?

A. Joins are more easily performed with instance field types.
B. The final Prism datasource can support drilling into Workday objects.
C. Unions are more easily performed with instance field types.
D. Performance is improved in the final Prism datasource when published.

Answer: B

Explanation:
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.
References:
Workday Prism Analytics Study Path Documents, Section: Integrating Prism with Workday Reports, Topic:
Workday Report Field Types and Prism Integration
Workday Prism Analytics Training Guide, Module: Publishing and Visualizing Data, Subtopic: Enabling Drill-Down Capabilities in Prism Data Sources

NEW QUESTION # 40
You are loading data into a table using the Data Change task. The field type in the source file is Numeric and the table field type is Text. What can you do to load the data?

A. Use a different source file, as the field types are incompatible.
B. Map the Numeric field to the table Text field.
C. Change the field type in the parsing stage from Numeric to Text.
D. Change the connection type for the data change task.

Answer: B

Explanation:
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.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Field Type Mapping in Data Change Tasks Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Handling Field Type Conversions in Data Loading

NEW QUESTION # 41
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?

A. At the beginning of the primary pipeline of the Base Dataset.
B. After the dataset is published.
C. At the end of the Primary Pipeline of a published dataset.
D. At the beginning of the Primary Pipeline of the derived dataset.

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 # 42
......

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Workday Pro Prism Analytics Exam Sample Questions (Q37-Q42):

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