[2025] Workday-Prism-Analytics by Reporting and Analytics Actual Free Exam Practice Test
Free Reporting and Analytics Workday-Prism-Analytics Exam Question
NEW QUESTION # 10
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 stays the same and the original multi-instance field doesn't get dropped.
- D. The number of columns exponentially increases and the original multi-instance field gets 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 # 11
For a Prism use case, you have two datasets: one contains daily sales data, and the other contains monthly budget allocations. Before performing a join between these datasets, what transformation stage should you apply to the sales data to ensure it matches the granularity of the budget data?
- A. Union
- B. Filter
- C. Manage Fields
- D. Group By
Answer: D
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, joining datasets with different levels of granularity requires aligning their granularity to ensure a meaningful match. The sales data is at a daily level (one row per day), while the budget data is at a monthly level (one row per month). According to the official Workday Prism Analytics study path documents, to match the granularity of the monthly budget data, you should apply a Group By stage to the sales data (option B). The Group By stage aggregates the daily sales data into monthly totals (e.g., summing sales amounts by month), reducing the granularity from daily to monthly. This allows the sales data to be joined with the monthly budget data on a common key, such as the month.
For example, a Group By stage could group the sales data by a derived month field (e.g., using a function like EXTRACT(YEAR_MONTH, sale_date)) and aggregate the sales amounts using a function like SUM (sales_amount). The resulting dataset would have one row per month, matching the budget data's granularity.
The other options are incorrect:
* A. Union: A Union stage appends rows from one dataset to another but does not change granularity; it cannot aggregate daily data into monthly data.
* C. Manage Fields: The Manage Fields stage modifies field properties (e.g., type, name) but does not aggregate data to change granularity.
* D. Filter: A Filter stage removes rows based on conditions but does not aggregate data to align granularity levels.
The Group By stage is the appropriate transformation to align the sales data's granularity with the monthly budget data for a successful join.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Aligning Granularity for Joins in Prism Analytics Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Using Group By Stages for Data Aggregation
NEW QUESTION # 12
Using three different source files, you want to load rows of data into an empty table through a Data Change task. What needs to be the same about the three source files?
- A. Naming convention
- B. Source
- C. Size
- D. Schema
Answer: D
Explanation:
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.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Data Change Tasks and Schema Requirements Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Loading Data into Tables Using Data Change Tasks
NEW QUESTION # 13
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. Group By
- C. Unpivot
- D. Manage Fields
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 # 14
When using a window function to calculate averages in Prism, what field type must the function operate on?
- A. Date
- B. Numeric
- C. Text
- D. Boolean
Answer: B
Explanation:
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.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Window Functions and Field Type Requirements Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Using AVG in Window Functions
NEW QUESTION # 15
You have a number of Workday reports that use a Prism data source. When are the values of the Prism calculated fields in the Workday reports calculated?
- A. At report run time.
- B. At dataset creation time.
- C. At the calculated field creation time.
- D. At time of publishing.
Answer: D
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, calculated fields in a dataset are evaluated as part of the dataset's processing logic, and their values are materialized when the dataset is published as a Prism data source. According to the official Workday Prism Analytics study path documents, the values of Prism calculated fields are calculated at the time of publishing (option D). When a dataset is published, Prism processes all transformation stages, including calculated fields, and the resulting values are stored in the publisheddata source. Workday reports that use this Prism data source then retrieve these pre-calculated values, ensuring consistent and efficient reporting without recalculating the fields at report run time.
The other options are incorrect:
* A. At report run time: Calculated field values are not computed when the Workday report is run; they are pre-calculated and stored in the Prism data source during publishing.
* B. At dataset creation time: Dataset creation involves defining the transformation logic, but the actual computation of calculated fields occurs during publishing, not at creation.
* C. At the calculated field creation time: Creating a calculated field defines its expression, but the values are not computed until the dataset is processed during publishing.
The calculation of Prism calculated fields at the time of publishing ensures that Workday reports can efficiently access the results without additional computation overhead.
References:
Workday Prism Analytics Study Path Documents, Section: Integrating Prism with Workday Reports, Topic:
Calculated Fields in Prism Data Sources
Workday Prism Analytics Training Guide, Module: Publishing and Visualizing Data, Subtopic: Processing Calculated Fields During Publishing
NEW QUESTION # 16
An HR analyst is tasked to create custom reports for their company's performance reviews. The analyst uses both Workday and Prism for data analysis. What Workday-calculated field functions would the analyst be able to build off of their Prism object?
- A. Extract Single Instance
- B. Lookup Related Value
- C. Arithmetic Calculation
- D. Lookup Field with Prompts
Answer: C
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, when integrating with Workday reports, a Prism object (i.e., a published Prism data source) can be used as the basis for custom reports, and certain Workday-calculated field functions can be applied to it. According to the official Workday Prism Analytics study path documents, the Arithmetic Calculation function (option B) is a supported Workday-calculated field function that can be built off a Prism object. This function allows the analyst to perform mathematical operations (e.g., addition, subtraction, multiplication) on numeric fields within the Prism data source, such as calculatinga performance review score by combining multiple metrics. Since Prism data sources often contain pre-processed data, arithmetic calculations can be applied to enhance the data for reporting purposes.
The other options are not supported for Prism objects:
* A. Extract Single Instance: This function is used to extract a single instance from a multi-instance field in Workday, but Prism objects typically contain single-instance fields after transformations (e.g., via an Explode stage), making this function inapplicable.
* C. Lookup Related Value: This function retrieves related values from other Workday business objects, but Prism objects do not support direct lookups to Workday objects in this manner; such relationships must be pre-built in the Prism dataset.
* D. Lookup Field with Prompts: This function involves interactive prompting, which is not supported for Prism objects in Workday reports, as Prism data sources are static snapshots of data.
The Arithmetic Calculation function provides the flexibility to perform numerical computations on Prism data, making it a suitable choice for enhancing performance review reports.
References:
Workday Prism Analytics Study Path Documents, Section: Integrating Prism with Workday Reports, Topic:
Using Calculated Fields with Prism Objects
Workday Prism Analytics Training Guide, Module: Integrating Prism with Workday Reports, Subtopic:
Supported Calculated Field Functions for Prism Data Sources
NEW QUESTION # 17
While viewing your lineage, you realize you have forgotten to add a description to some of your derived datasets. From the lineage, you double-click on a dataset to view the dataset details. What is the next step to add the missing descriptions?
- A. Select the pencil icon next to the dataset name and Edit Transformations.
- B. Select Related Actions next to the dataset name and Edit Transformations.
- C. Select Add Field from the dataset details to create a description.
- D. Select the pencil icon next to the Import stage to update the description.
Answer: B
Explanation:
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.
Reference: Workday Prism Analytics User Guide, "Concept: Dataset Workspace" section
NEW QUESTION # 18
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 Name
- D. Output Type
Answer: D
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 # 19
What security domain enables the ability to create a dataset?
- A. Prism Datasets: Publish
- B. Prism Datasets: Create
- C. Prism: Manage Data Source
- D. Prism: Tables Create
Answer: B
Explanation:
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.
References:
Workday Prism Analytics Study Path Documents, Section: Security and Governance in Prism Analytics, Topic: Security Domains and Permissions Workday Prism Analytics Training Guide, Module: Datasets and Data Sources, Subtopic: Creating Datasets and Associated Security
NEW QUESTION # 20
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 # 21
What is the primary purpose of window functions in Prism?
- A. To provide row-level access control.
- B. To perform calculations across a set of rows related to the current row while partitioning the data.
- C. To manipulate strings and dates within a query.
- D. To filter rows based on specified conditions.
Answer: B
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 # 22
You want to apply a Filter stage to your derived dataset to show only expense reports submitted in the current month and where the expense report total amount is higher than 2000 USD. What should you do?
- A. Use a simple filter, three conditions, and "If Any" operator.
- B. Use a simple filter, three conditions, and "If All" operator.
- C. Use a simple filter, two conditions, and "If All" operator.
- D. Use a simple filter, two conditions, and "If Any" operator.
Answer: C
Explanation:
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.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Applying Filters in Derived Datasets Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Configuring Simple Filters with Multiple Conditions
NEW QUESTION # 23
You want to use a custom report containing prompts as a source connection for a table. What must you ensure to make this possible?
- A. The prompts are marked as required.
- B. The report is built on an indexed data source.
- C. The prompts are mapped at the data change task level.
- D. The custom report prompts have default values assigned on the report definition.
Answer: D
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, when using a custom report with prompts as a source connection for a table, the custom report must be configured to ensure compatibility with the Prism data ingestion process. According to the official Workday Prism Analytics study path documents, the key requirement is that the custom report prompts have default values assigned in the report definition. This is necessary because Prism Analytics does not support interactive prompting during data ingestion. Default values ensure that the report can run automatically without requiring user input, allowing the Data Change task to retrieve the data consistently and load it into the target table.
The other options are not correct in this context:
* A. The report is built on an indexed data source: While indexed data sources can enhance performance for certain reports, they are not a requirement for using a custom report as a source for a Prism table.
* B. The prompts are mapped at the data change task level: Prompts are not mapped in the Data Change task; instead, the task relies on the report's default values to execute the data retrieval.
* D. The prompts are marked as required: Marking prompts as required does not address the need for automatic execution; default values are still needed to avoid manual intervention.
By assigning default values to prompts in the custom report definition, the report can be seamlessly integrated as a source connection for Prism Analytics, ensuring reliable data loading into the table.
References:
Workday Prism Analytics Study Path Documents, Section: Integrating Prism with Workday Reports, Topic:
Using Custom Reports as Data Sources
Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Configuring Custom Reports for Prism Integration
NEW QUESTION # 24
What is a feature of using an sFTP connection on a data change task?
- A. You can copy sFTP connections.
- B. You can reuse an sFTP connection in multiple data change tasks.
- C. You can select multiple target tables in the data change task.
- D. You can import an XLSX file from an sFTP server.
Answer: B
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, a secure File Transfer Protocol (sFTP) connection can be configured as a source for a Data Change task to import data into a table. According to the official Workday Prism Analytics study path documents, a key feature of using an sFTP connection is that it can be reused across multiple Data Change tasks. Once an sFTP connection is defined in the Prism Analytics environment, it is stored and can be selected as the source connection for different Data Change tasks, promoting efficiency and consistency in data ingestion workflows. This reusability reduces the need to redefine connection parameters for each task, streamlining the configuration process.
The other options are not accurate:
* A. You can copy sFTP connections: While connections can be managed, there is no specific feature in Prism Analytics to "copy" sFTP connections as a distinct action.
* C. You can import an XLSX file from an sFTP server: While sFTP connections support various file formats (e.g., CSV), the ability to import XLSX files is not guaranteed and depends on the system's configuration, making this option less definitive.
* D. You can select multiple target tables in the data change task: A Data Change task is designed to load data into a single target table, not multiple tables simultaneously, regardless of the connection type.
The ability to reuse an sFTP connection across multiple Data Change tasks is a core feature that enhances the flexibility and scalability of data import processes in Prism Analytics.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Configuring Data Change Tasks with sFTP Connections Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Managing Source Connections for Data Ingestion
NEW QUESTION # 25
You just imported your table on worker compensation into a derived dataset but before adding any transformation you want to make sure you have no NULL values for the Worker ID field. How can you get this insight?
- A. Create a Prism calculated field.
- B. Join on the Worker ID field.
- C. Click on the field name and check the stage statistics.
- D. Add a Manage Fields stage.
Answer: C
Explanation:
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.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Data Quality Checks in Derived Datasets Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Inspecting Data Using Stage Statistics
NEW QUESTION # 26
You want to delete a Prism data source, but you are unable to complete the dataset unpublish. You have deleted the Report Writer reports. What else must you delete, if present?
- A. Discovery board visualizations
- B. Upstream tables
- C. Published rows
- D. Upstream datasets
Answer: A
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, unpublishing a dataset to delete a Prism data source requires removing all dependencies that reference the data source. According to the official Workday Prism Analytics study path documents, if you have already deleted Report Writer reports but are still unable to unpublish the dataset, you must also delete any discovery board visualizations that reference the Prism data source (option C). Discovery boards in Workday allow users to create visualizations based on Prism data sources, and these visualizations create a dependency on the data source. If such visualizations exist, the system prevents the dataset from being unpublished until they are removed, ensuring that no downstream dependencies are broken.
The other options are incorrect:
* A. Upstream tables: Upstream tables are the source of data for the dataset, but they are not dependencies of the published data source and do not need to be deleted to unpublish the dataset.
* B. Published rows: Published rows are part of the data source itself and are removed when the dataset is unpublished; they are not a separate dependency to delete.
* D. Upstream datasets: Upstream datasets may feed into the dataset being unpublished, but they are not dependencies of the published data source and do not prevent unpublishing.
Deleting discovery board visualizations ensures all dependencies are cleared, allowing the dataset to be unpublished and the Prism data source to be deleted.
References:
Workday Prism Analytics Study Path Documents, Section: Publishing and Visualizing Data, Topic:
Unpublishing Prism Data Sources
Workday Prism Analytics Training Guide, Module: Publishing and Visualizing Data, Subtopic: Managing Dependencies for Data Source Deletion
NEW QUESTION # 27
What task or report should you access to view a Prism data source?
- A. Edit Dataset Transformations task
- B. View Prism Data Source report
- C. Edit Data Source Security task
- D. View Dataset Details report
Answer: B
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, a Prism data source represents the published dataset that is available for reporting and analytics within the Workday ecosystem. According to the official Workday Prism Analytics study path documents, the "View Prism Data Source" report is the specific task or report designed to allow users to view the details of a Prism data source. This report provides comprehensive information about the data source, including its metadata, structure, and associated attributes, enabling users to understand the data available for reporting purposes.
The other options do not serve this purpose. The "Edit Dataset Transformations task" is used to modify the transformation logic applied to a dataset, not to view a data source. The "Edit Data Source Security task" focuses on managing security settings for a data source, such as access permissions, rather than viewing its contents. Similarly, the "View Dataset Details report" provides information about a dataset (including its metadata and sample rows) but does not specifically address the published Prism data source, which is a distinct entity created after a dataset is published.
The "View Prism Data Source" report is the correct choice as it directly aligns with the need to inspect the properties and structure of a Prism data source, ensuring users can verify its suitability for reporting or integration with Workday reports.
References:
Workday Prism Analytics Study Path Documents, Section: Datasets and Data Sources, Topic: Managing and Viewing Prism Data Sources Workday Prism Analytics Training Guide, Module: Publishing and Visualizing Data, Subtopic: Viewing and Validating Data Sources
NEW QUESTION # 28
A Prism data writer needs to create a new Prism calculated field on a derived dataset using the CASE function. When creating a calculated field, what symbol do you use to view a list of fields that you can select from in the dataset?
- A. [
- B. {
- C. #
- D. (
Answer: A
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Workday Prism Analytics, when creating a calculated field in a derived dataset, users often need to reference existing fields in the dataset within their expressions, such as in a CASE function. According to the official Workday Prism Analytics study path documents, to view and select from a list of available fields in the dataset while building a calculated field expression, the user types the [ symbol (left square bracket). This symbol triggers a dropdown list of all fields in the dataset, allowing the user to select the desired field without manually typing its name, reducing the risk of errors. For example, typing [ and selecting a field like
"Employee_ID" will insert [Employee_ID] into the expression, which can then be used in the CASE function logic.
The other symbols do not serve this purpose:
* B. (: Parentheses are used for grouping expressions or defining function parameters, not for field selection.
* C. #: The hash symbol is not used in Prism Analytics for field selection; it may be associated with other functionalities in different contexts.
* D. {: Curly braces are not used for field selection in Prism Analytics; they may be used in other systems for different purposes, such as templating.
The use of the [ symbol ensures an efficient and accurate way to reference fields in a calculated field expression, streamlining the creation process in Prism Analytics.
References:
Workday Prism Analytics Study Path Documents, Section: Data Prep and Transformation, Topic: Creating Calculated Fields in Derived Datasets Workday Prism Analytics Training Guide, Module: Data Prep and Transformation, Subtopic: Using the Expression Editor for Calculated Fields
NEW QUESTION # 29
You have a number of Workday reports that use a Prism data source. When are the values of the Prism calculated fields in the Workday reports calculated?
- A. At report run time.
- B. At dataset creation time.
- C. At the calculated field creation time.
- D. At time of publishing.
Answer: D
NEW QUESTION # 30
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 View Dataset Lineage report.
- B. Any table in the lineage.
- C. Any dataset in the lineage.
- D. The table or dataset where the calculated field was created.
Answer: A
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 # 31
......
Workday Workday-Prism-Analytics Actual Questions and Braindumps: https://getfreedumps.passreview.com/Workday-Prism-Analytics-exam-questions.html