LATEST WORKDAY-PRISM-ANALYTICS DUMPS FREE | WORKDAY-PRISM-ANALYTICS KNOWLEDGE POINTS

Latest Workday-Prism-Analytics Dumps Free | Workday-Prism-Analytics Knowledge Points

Latest Workday-Prism-Analytics Dumps Free | Workday-Prism-Analytics Knowledge Points

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Workday-Prism-Analytics Knowledge Points & New Workday-Prism-Analytics Braindumps Questions

Hundreds of candidates want to get the Workday Pro Prism Analytics Exam (Workday-Prism-Analytics) certification exam because it helps them in accelerating their Workday careers. Cracking the Workday-Prism-Analytics exam of this credential is vital when it comes to the up gradation of their resume. The Workday-Prism-Analytics Certification Exam helps students earn from online work and it also benefits them in order to get a job in any good tech company.

Workday Pro Prism Analytics Exam Sample Questions (Q43-Q48):

NEW QUESTION # 43
The final derived dataset in a Prism pipeline is complete and ready to publish. What should be done prior to publishing?

  • A. Add a Group By stage to the final derived dataset to add summary calculations.
  • B. Create a table without the Enable for Analysis checkbox selected.
  • C. Create a derived dataset with the PDS suffix.
  • D. Edit the Dataset API Name to reflect in the name of the Prism data source.

Answer: D

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, before publishing a derived dataset as a Prism data source (PDS), it's important to ensure that the dataset is properly configured for downstream use. According to the official Workday Prism Analytics study path documents, one key step to take prior to publishing is to edit the Dataset API Name to reflect in the name of the Prism data source (option D). The Dataset API Name determines the name of the published Prism data source, which is used in reporting, discovery boards, and integrations. Setting a meaningful and descriptive API name (e.g., "Expense_Reports_by_Location") ensures that the data source is easily identifiable and aligns with naming conventions, improving usability and manageability in the Workday ecosystem. This step is a best practice to avoid confusion and ensure clarity for report writers and analysts.
The other options are not required or relevant:
* A. Add a Group By stage to the final derived dataset to add summary calculations: Adding a Group By stage is not mandatory unless the use case specifically requires summarizations, which is not indicated here.
* B. Create a table without the Enable for Analysis checkbox selected: Creating a new table is unnecessary, as the dataset is already complete, and the "Enable for Analysis" checkbox is relevant for real-time updates, not a requirement for publishing a derived dataset.
* C. Create a derived dataset with the PDS suffix: Creating a new dataset is not needed, as the final derived dataset is already prepared, and adding a "PDS" suffix is not a required step for publishing.
Editing the Dataset API Name ensures the Prism data source has a clear and meaningful name, facilitating its use in reporting and analytics.
References:
Workday Prism Analytics Study Path Documents, Section: Publishing and Visualizing Data, Topic: Best Practices for Publishing Prism Data Sources Workday Prism Analytics Training Guide, Module: Publishing and Visualizing Data, Subtopic: Configuring Dataset API Names Before Publishing


NEW QUESTION # 44
You want to create a Prism calculated field to change the field type to date data using the TO_DATE function.
The field from Workday is numeric data and you will use the Manage Fields stage to prepare the data for use in the function. What will you need to change about the field in the Manage Fields stage?

  • A. Input Type
  • B. Input Name
  • C. Output Type
  • D. Output Name

Answer: C

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, the TO_DATE function in a calculated field is used to convert a string or compatible data type into a date. However, in this scenario, the field from Workday is numeric, and the TO_DATE function typically requires a string input (e.g., a numeric value like 20230101 needs to be converted to a string like "20230101" before applying TO_DATE). According to the official Workday Prism Analytics study path documents, to prepare the numeric field for use with the TO_DATE function, you must first use a Manage Fields stage to change the field's Output Type to Text. The Manage Fields stage allows you to modify the field's properties, and changing the Output Type from Numeric to Text converts the numeric values into a string format that the TO_DATE function can then process (e.g., TO_DATE ([Field_Name], "YYYYMMDD")).
The other options are not relevant:
* B. Output Name: Changing the Output Name renames the field but does not address the field type compatibility required for the TO_DATE function.
* C. Input Type: The Manage Fields stage does not modify an "Input Type"; it adjusts the Output Type to transform the field as it moves through the pipeline.
* D. Input Name: There is no "Input Name" property in the Manage Fields stage; this option is not applicable.
By changing the Output Type to Text in the Manage Fields stage, the numeric field is converted to a string, making it compatible with the TO_DATE function for creating a date field in the calculated field.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Field Type Transformations for Calculated Fields Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Using Manage Fields for Data Type Conversions


NEW QUESTION # 45
In a Prism project, you have a dataset containing customer purchase transactions, including the customer ID, purchase amount, and purchase date. You want to analyze the total purchase amount for each customer over the entire period. What transformation stage should you apply to calculate the total purchase amount for each customer?

  • A. Group By
  • B. Join
  • C. Explode
  • D. Union

Answer: A

Explanation:
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.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic:
Aggregating Data with Group By Stages
Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Using Group By for Summarization


NEW QUESTION # 46
A Prism data administrator needs to add an Explode stage to a derived dataset to create a new single-instance type field. What is the only field type you can select in the Explode stage?

  • A. Text
  • B. Single-Instance
  • C. Multi-Instance
  • D. Numeric

Answer: C

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, an Explode stage is used in a derived dataset to transform a multi-instance field into multiple rows, effectively creating single-instance fields for each instance. According to the official Workday Prism Analytics study path documents, the only field type you can select in the Explode stage is Multi-Instance (option B). A multi-instance field, often sourced from Workday data, contains multiple values for a single record (e.g., a list of certifications for a worker). The Explode stage "explodes" this field into separate rows, one for each instance, while converting the multi-instance fieldinto a single-instance field in the output. For example, if a worker has three certifications in a multi-instance field, the Explode stage would create three rows, each with a single certification value.
The other options are incorrect:
* A. Numeric: Numeric fields are single-instance by nature and cannot be exploded, as they do not contain multiple values.
* C. Single-Instance: Single-instance fields contain one value per record and cannot be used in an Explode stage, which requires a multi-instance field to operate.
* D. Text: While a Text field can be single or multi-instance, the Explode stage specifically requires a Multi-Instance field, not just any Text field.
The requirement for a Multi-Instance field in the Explode stage ensures that the transformation can properly expand the data into multiple rows as intended.
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 # 47
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 five transformation stages.
  • B. As many transformation stages of any type as long as they are in a particular order.
  • C. As many transformation stages of any type as your scenario requires.
  • D. Up to two Manage Fields transformation stages.

Answer: C

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 # 48
......

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