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Workday Workday-Prism-Analytics試験の準備方法｜信頼できるWorkday-Prism-Analytics対策学習試験｜素晴らしいWorkday Pro Prism Analytics Exam最新な問題集

あなたは彼と同じような仕事の能力を持っていると思うかもしれませんし、あなたも一生懸命働いているので、誰かが突然昇進していることに気付きましたか？（Workday-Prism-Analytics信頼できる試験ダンプ）有効なWorkday認定が鍵になるかもしれません。あなたの会社がこの大企業のプロジェクトに応募する場合、有用な認定はプロジェクトマネージャーの地位にとって大きな利点になります。 Workday-Prism-Analytics信頼できる試験ダンプは、試験に合格し、貴重な変更を取得するのに役立ちます。 heしないでください。時は金なり。当社のWorkday-Prism-Analytics信頼できる試験ダンプは、近年、数千人の受験者が試験をクリアするのに役立ちました。

WorkdayのWorkday-Prism-Analytics認定試験に受かる勉強サイトを探しているのなら、Japancertはあなたにとって一番良い選択です。Japancertがあなたに差し上げられるのはIT業種の最先端のスキルを習得したこととWorkdayのWorkday-Prism-Analytics認定試験に合格したことです。この試験は本当に難しいことがみんなは良く知っていますが、試験に受かるのは不可能ではないです。自分に向いている勉強ツールを選べますから。Japancert のWorkdayのWorkday-Prism-Analytics試験問題集と解答はあなたにとって一番良い選択です。Japancertのトレーニング資料は完全だけでなく、カバー率も高くて、高度なシミュレーションを持っているのです。これはさまざまな試験の実践の検査に合格したもので、WorkdayのWorkday-Prism-Analytics認定試験に合格したかったら、Japancertを選ぶのは絶対正しいことです。

>> Workday-Prism-Analytics対策学習 <<

Workday-Prism-Analytics最新な問題集、Workday-Prism-Analytics模擬トレーリング

Workday-Prism-Analytics模擬試験は、緊急の課題に対処するための最適な選択および有用なツールとなります。 10年以上の努力により、当社のWorkday-Prism-Analyticsトレーニング資料は、業界で最も広く称賛され、待望の製品になりました。革新メカニズムを近代化し、専門家の強力なプールを育成することにより、Workday-Prism-Analytics試験問題の3つのバージョンがあります。したがって、Workday-Prism-Analytics模擬テストの計画と設計において、プロのエリートからの完全な技術サポートをご安心ください。

Workday Pro Prism Analytics Exam 認定 Workday-Prism-Analytics 試験問題 (Q25-Q30):

質問 # 25
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. Group By
B. Unpivot
C. Manage Fields
D. Explode

正解：D

解説：
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

質問 # 26
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. Group By
B. Filter
C. Manage Fields
D. Union

正解：A

解説：
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

質問 # 27
You want to remove data within a Prism data source without deleting any dependent custom reports. What task can you use to do this?

A. Inactivate Dataset
B. Delete Dataset
C. Delete Published Rows
D. Unpublish Dataset

正解：C

解説：
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.
References:
Workday Prism Analytics Study Path Documents, Section: Publishing and Visualizing Data, Topic: Managing Data in Prism Data Sources Workday Prism Analytics Training Guide, Module: Publishing and Visualizing Data, Subtopic: Removing Data Without Breaking Report Dependencies

質問 # 28
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. Size
B. Schema
C. Naming convention
D. Source

正解：B

解説：
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

質問 # 29
Why should you include Workday instance field types in the Workday report that you use to import data into Prism?

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

正解：D

解説：
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

質問 # 30
......

JapancertのWorkday-Prism-Analytics問題集は実際のWorkday-Prism-Analytics認定試験と同じです。この問題集は実際試験の問題をすべて含めることができるだけでなく、問題集のソフト版はWorkday-Prism-Analytics試験の雰囲気を完全にシミュレートすることもできます。Japancertの問題集を利用してから、試験を受けるときに簡単に対処し、楽に高い点数を取ることができます。

Workday-Prism-Analytics最新な問題集: https://www.japancert.com/Workday-Prism-Analytics.html

Workday-Prism-Analyticsの実際の学習ガイド資料は、より良いレビューを得るのに役立ちます、Workday-Prism-Analyticsガイド資料を理解できるようになりました、顧客は当社を支援するのを感謝するから、当社から販売されるWorkday-Prism-Analytics試験学習資料のすべてのバージョンは無料アップデットサービスを提供します、そして我々のサイトには“本番試験の問題はほぼWorkday-Prism-Analytics関連勉強資料と同じ”という顧客からのコメントも次々来ます、上記のすべてのWorkday-Prism-Analytics学習資料は、不定期の割引を提供します、Workday Workday-Prism-Analytics対策学習これは、当社が他の企業のリーダーであるだけでなく、忠実なユーザーもいるからです、楽しい学習シーンと鮮明な説明をシミュレートすることにより、ユーザーは資格のあるWorkday-Prism-Analytics試験に合格する自信が大きくなります。

ぼくはプロだからさ、すこし腫れた下唇が痛い、Workday-Prism-Analyticsの実際の学習ガイド資料は、より良いレビューを得るのに役立ちます、Workday-Prism-Analyticsガイド資料を理解できるようになりました、顧客は当社を支援するのを感謝するから、当社から販売されるWorkday-Prism-Analytics試験学習資料のすべてのバージョンは無料アップデットサービスを提供します。

実際的なWorkday-Prism-Analytics対策学習 & 合格スムーズWorkday-Prism-Analytics最新な問題集 | 検証するWorkday-Prism-Analytics模擬トレーリング Workday Pro Prism Analytics Exam

そして我々のサイトには“本番試験の問題はほぼWorkday-Prism-Analytics関連勉強資料と同じ”という顧客からのコメントも次々来ます、上記のすべてのWorkday-Prism-Analytics学習資料は、不定期の割引を提供します。

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Tom Moore Tom Moore

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