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Salesforce Data-Cloud-Consultant 認定試験の出題範囲：

トピック	出題範囲
トピック 1	アイデンティティ解決: マッチングとそのルールセットの適用方法について説明します。さらに、データとそのルールセットの調整、アイデンティティ解決の結果、およびユースケースについても説明します。
トピック 2	データの取り込みとモデリング: このトピックでは、Data Cloud 内のさまざまな変換機能について説明します。さまざまなソースからのデータ取り込みのプロセスと考慮事項の説明、ID 解決に合わせたベストプラクティスを使用したデータの定義、マッピング、モデリングが含まれます。最後に、取り込まれたデータとモデリングされたデータを検査および検証するために利用可能なツールを使用する方法について説明します。
トピック 3	データに基づく行動: このトピックでは、アクティベーションとその基本的な使用例、属性と関連属性の使用、Data Cloud ライフサイクルに影響するタイミングの依存関係の特定と分析について説明します。また、アクティベーションに関する一般的な問題のトラブルシューティング、およびデータアクションの使用 (要件と想定される使用例を含む) にも重点を置いています。
トピック 4	データクラウドの概要: このトピックでは、データクラウドの機能、主要な用語、ビジネス価値、一般的な使用例、データクラウドのライフサイクル、依存関係、およびデータ倫理の原則について説明します。これらのサブトピックでは、データクラウドの機能とアプリケーションの概要を説明します。

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Salesforce Certified Data 360 Consultant (Data-Con-101) 認定 Data-Cloud-Consultant 試験問題 (Q24-Q29):

質問 # 24
A Data 360 Consultant is attempting to configure Data 360 in an existing Developer Pro sandbox that was refreshed prior to the organization purchasing Data 360 licenses. Although the consultant has the Data 360 Admin permission set assigned in production, they cannot see the Data 360 Setup menu or the Data Spaces configuration options in the sandbox. Which action should the consultant take to resolve this issue?

A. Update the Contract Management settings in the sandbox to toggle the Data 360 Features switch to enabled.
B. Navigate to Company Information in the sandbox and select Match Production Licenses.
C. Refresh the sandbox immediately to pull the new metadata and license counts from production.
D. Manually create the Data 360 Admin permission set in the sandbox to match the production configuration.

正解：B

解説：
The governance lens is least privilege, purpose limitation, and honoring privacy operations against the individual profile. Navigate to Company Information in the sandbox and select Match Production Licenses.
supports the governance requirement because Data 360 implementations should minimize unnecessary access, avoid over-collection, and process deletion or consent requests at the profile level where Salesforce expects them. The safest design is explicit, auditable, and limited to the business purpose. The distractors fall short because they either move the problem into the wrong system, add needless duplication, ignore Data 360 object relationships, or rely on a feature built for a different lifecycle stage. In a real implementation, those choices usually create brittle pipelines, stale data, security exposure, or segments that look correct on paper but fail when activated. Thinking like an architect, the selected option places the logic where Data 360 can govern it and reuse it reliably. This is the nuance exam questions often test: the platform capability must match both the technical layer and the business timing requirement, not just sound related to data.

質問 # 25
A user Is not seeing suggested values from newly-modeled data when building a segment.
What is causing this issue?

A. Value suggestion will only return results for the first 50 values of a specific attribute,
B. Value suggestion is still processing and takes up to 24 hours to be available.
C. Value suggestion requires Data Aware Specialist permissions at a minimum.
D. Value suggestion can only work on direct attributes and not related attributes.

正解：B

解説：
The most likely cause of this issue is that value suggestion is still processing and takes up to 24 hours to be available. Value suggestion is a feature that enables you to see suggested values for data model object (DMO) fields when creating segment filters. However, this feature needs to be enabled for each DMO field, and it can take up to 24 hours for the suggested values to appear after enabling the feature1. Therefore, if a user is not seeing suggested values from newly-modeled data, it could be that the data has not been processed yet by the value suggestion feature. Reference:
Use Value Suggestions in Segmentation

質問 # 26
Which statement about Data Cloud's Web and Mobile Application Connector is true?

A. The Tenant Specific Endpoint is auto-generated in Data Cloud when setting the connector.
B. Any data streams associated with the connector will be automatically deleted upon deleting the app from Data Cloud Setup.
C. The connector schema can be updated to delete an existing field.
D. A standard schema containing event, profile, and transaction data is created at the time the connector is configured.

正解：A

解説：
The Web and Mobile Application Connector allows you to ingest data from your websites and mobile apps into Data Cloud. To use this connector, you need to set up a Tenant Specific Endpoint (TSE) in Data Cloud, which is a unique URL that identifies your Data Cloud org. The TSE is auto-generated when you create a connector app in Data Cloud Setup. You can then use the TSE to configure the SDKs for your websites and mobile apps, which will send data to Data Cloud through the TSE. References: Web and Mobile Application Connector, Connect Your Websites and Mobile Apps, Create a Web or Mobile App Data Stream

質問 # 27
Which two dependencies prevent a data stream from being deleted?
Choose 2 answers

A. The underlying data lake object is used in segmentation.
B. The underlying data lake object is mapped to a data model object.
C. The underlying data lake object is used in a data transform.
D. The underlying data lake object is used in activation.

正解：B、C

解説：
To delete a data stream in Data Cloud, the underlying data lake object (DLO) must not have any dependencies or references to other objects or processes. The following two dependencies prevent a data stream from being deleted1:
Data transform: This is a process that transforms the ingested data into a standardized format and structure for the data model. A data transform can use one or more DLOs as input or output. If a DLO is used in a data transform, it cannot be deleted until the data transform is removed or modified2.
Data model object: This is an object that represents a type of entity or relationship in the data model. A data model object can be mapped to one or more DLOs to define its attributes and values. If a DLO is mapped to a data model object, it cannot be deleted until the mapping is removed or changed3.
Reference:
1: Delete a Data Stream article on Salesforce Help
2: [Data Transforms in Data Cloud] unit on Trailhead
3: [Data Model in Data Cloud] unit on Trailhead

質問 # 28
What is a reason to create a formula when ingesting a data stream?

A. To remove duplicate rows of data from the data stream
B. To concatenate files so they are ingested in the correct sequence
C. To transform is date time field into a dale field for use in data mapping
D. To add a unique external identifier to an existing ruleset

正解：C

質問 # 29
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