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Matthew Robinson Matthew Robinson

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Data-Cloud-Consultant資格問題対応 & Data-Cloud-Consultant資格認定試験

2025年ShikenPASSの最新Data-Cloud-Consultant PDFダンプおよびData-Cloud-Consultant試験エンジンの無料共有：https://drive.google.com/open?id=10ybLFR5Y3p_48wQe2dyVdMFd_mTk7PyN

ユーザーエクスペリエンスとクライアントのフィードバックを優先します。Data-Cloud-Consultant実践ガイドは、常にサービスを改善し、バージョンを更新してクライアントの利便性を高め、満足させるようにします。 Data-Cloud-Consultantトレーニング資料に関するクライアントの満足度は、前進を続ける原動力の源です。 Data-Cloud-Consultantガイド資料を理解できるようになりました。 Data-Cloud-Consultant認定に関する知識の主流の微妙な変更はすべてキャッチされ、利用可能なData-Cloud-Consultant学習資料リソースの検索に最善を尽くします。

時間は、私たちSalesforceがすべて計画に追いついていて、それでもなお便利な事項を踏んでいる場合に特に重要です。先延ばしに苦しみ、学習プロセス中に散発的な時間を十分に活用できない場合は、Data-Cloud-Consultantトレーニング資料を選択する理想的な方法です。学習の楽しさを享受できるだけでなく、Data-Cloud-Consultant認定を正常に取得できることを保証できます。 Data-Cloud-Consultant試験問題に挑戦した後、Data-Cloud-Consultantガイド急流について完全に理解できます。

>> Data-Cloud-Consultant資格問題対応 <<

Data-Cloud-Consultant資格認定試験 & Data-Cloud-Consultant日本語関連対策

当社の製品よりも高いプロファイルと低価格を備えた他の学習教材もあるかもしれませんが、Data-Cloud-Consultant学習教材の合格率は彼らのものよりもはるかに高いことを保証できます。そしてこれが最も重要です。以前のデータによると、Data-Cloud-Consultantトレーニング質問を使用する人の98％〜99％が試験に合格しました。あなたが私たちに信頼を与えてくれるなら、私たちはあなたに成功を与えます。

Salesforce Certified Data Cloud Consultant 認定 Data-Cloud-Consultant 試験問題 (Q67-Q72):

質問 # 67
How does Data Cloud handle an individual's Right to be Forgotten?

A. Deletes the specified Individual record and its Unified Individual Link record.
B. Deletes the specified Individual and records from any data model object/data lake object related to the Individual.
C. Deletes the specified Individual and records from any data source object mapped to the Individual data model object.
D. Deletes the records from all data source objects, and any downstream data model objects are updated at the next scheduled ingestion

正解：B

解説：
Data Cloud handles an individual's Right to be Forgotten by deleting the specified Individual and records from any data model object/data lake object related to the Individual. This means that Data Cloud removes all the data associated with the individual from the data space, including the data from the source objects, the unified individual profile, and any related objects. Data Cloud also deletes the Unified Individual Link record that links the individual to the source records. Data Cloud uses the Consent API to process the Right to be Forgotten requests, which are reprocessed at 30, 60, and 90 days to ensure a full deletion.
The other options are not correct descriptions of how Data Cloud handles an individual's Right to be Forgotten. Data Cloud does not delete the records from all data source objects, as this would affect the data integrity and availability of the source systems. Data Cloud also does not delete only the specified Individual record and its Unified Individual Link record, as this would leave the source records and the related records intact. Data Cloud also does not delete only the specified Individual and records from any data source object mapped to the Individual data model object, as this would leave the related records intact.
Reference:
Requesting Data Deletion or Right to Be Forgotten
Data Deletion for Data Cloud
Use the Consent API with Data Cloud
Data and Identity in Data Cloud

質問 # 68
A consultant wants to ensure that every segment managed by multiple brand teams adheres to the same set of exclusion criteria, that are updated on a monthly basis.
What is the most efficient option to allow for this capability?

A. Create a segment and copy it for each brand.
B. Create a reusable container block with common criteria.
C. Create, publish, and deploy a data kit.
D. Create a nested segment.

正解：B

解説：
The most efficient option to allow for this capability is to create a reusable container block with common criteria. A container block is a segment component that can be reused across multiple segments. A container block can contain any combination of filters, nested segments, and exclusion criteria. A consultant can create a container block with the exclusion criteria that apply to all the segments managed by multiple brand teams, and then add the container block to each segment. This way, the consultant can update the exclusion criteria in one place and have them reflected in all the segments that use the container block.
The other options are not the most efficient options to allow for this capability. Creating, publishing, and deploying a data kit is a way to share data and segments across different data spaces, but it does not allow for updating the exclusion criteria on a monthly basis. Creating a nested segment is a way to combine segments using logical operators, but it does not allow for excluding individuals based on specific criteria. Creating a segment and copying it for each brand is a way to create multiple segments with the same exclusion criteria, but it does not allow for updating the exclusion criteria in one place.
Reference:
Create a Container Block
Create a Segment in Data Cloud
Create and Publish a Data Kit
Create a Nested Segment

質問 # 69
A user needs permissions to access Data Cloud to create, manage, and activate segments, However, the user should not be allowed to created reports or manage data sources.
Which permission set should the consultant assign?

A. Data Cloud user
B. Data Cloud Marketing Specialist
C. Data Cloud Data Aware Specialist
D. Data Cloud Marketing Manager

正解：B

質問 # 70
Every day, Northern Trail Outfitters uploads a summary of the last 24 hours of store transactions to a new file in an Amazon S3 bucket, and files older than seven days are automatically deleted. Each file contains a timestamp in a standardized naming convention.
Which two options should a consultant configure when ingesting this data stream?
Choose 2 answers

A. Ensure the refresh mode is set to "Upsert".
B. Ensure the filename contains a wildcard to a accommodate the timestamp.
C. Ensure that deletion of old files is enabled.
D. Ensure the refresh mode is set to "Full Refresh.''

正解：A、B

解説：
When ingesting data from an Amazon S3 bucket, the consultant should configure the following options:
The refresh mode should be set to "Upsert", which means that new and updated records will be added or updated in Data Cloud, while existing records will be preserved. This ensures that the data is always up to date and consistent with the source.
The filename should contain a wildcard to accommodate the timestamp, which means that the file name pattern should include a variable part that matches the timestamp format. For example, if the file name is store_transactions_2023-12-18.csv, the wildcard could be store_transactions_*.csv. This ensures that the ingestion process can identify and process the correct file every day.
The other options are not necessary or relevant for this scenario:
Deletion of old files is a feature of the Amazon S3 bucket, not the Data Cloud ingestion process. Data Cloud does not delete any files from the source, nor does it require the source files to be deleted after ingestion.
Full Refresh is a refresh mode that deletes all existing records in Data Cloud and replaces them with the records from the source file. This is not suitable for this scenario, as it would result in data loss and inconsistency, especially if the source file only contains the summary of the last 24 hours of transactions. Reference: Ingest Data from Amazon S3, Refresh Modes

質問 # 71
If a data source does not have a field that can be designated as a primary key, what should the consultant do?

A. Remove duplicates from the data source and then select a primary key.
B. Select a field as a primary key and then add a key qualifier.
C. Use the default primary key recommended by Data Cloud.
D. Create a composite key by combining two or more source fields through a formula field.

正解：D

解説：
* Understanding Primary Keys in Salesforce Data Cloud:
A primary key is a unique identifier for records in a data source. It ensures that each record can be uniquely identified and accessed.
Reference:
* Challenges with Missing Primary Keys:
Some data sources may lack a natural primary key, making it difficult to uniquely identify records.
* Solution: Creating a Composite Key:
Composite Key Definition: A composite key is created by combining two or more fields to generate a unique identifier.
Formula Fields: Using a formula field, different fields can be concatenated to create a unique composite key.
Example: If "Email" and "Phone Number" together uniquely identify a record, a formula field can concatenate these values to form a composite key.
* Steps to Create a Composite Key:
Identify fields that, when combined, can uniquely identify each record.
Create a formula field that concatenates these fields.
Use this composite key as the primary key for the data source in Data Cloud.

質問 # 72
......

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Data-Cloud-Consultantガイド資料を理解できるようになりました。

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