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Salesforce Data-Cloud-Consultantクラムメディア、Data-Cloud-Consultant認定デベロッパー

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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

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 2

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 3

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 4

Data Cloud のセットアップと管理: このトピックには、Data Cloud の権限、権限セット、組織全体の設定の適用が含まれます。データストリームの種類とデータバンドルについて説明し、構成します。さらに、データスペースの使用例、データスペースの作成、レポート、ダッシュボード、フロー、パッケージ化、データキットを使用した Data Cloud の管理、Data Explorer、Profile Explorer、API を使用したデータの診断と探索についても説明します。

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Salesforce Certified Data Cloud Consultant 認定 Data-Cloud-Consultant 試験問題 (Q156-Q161):

質問 # 156
A Data Cloud consultant tries to save a new 1-to-l relationship between the Account DMO and Contact Point Address DMO but gets an error.
What should the consultant do to fix this error?

A. Map additional fields to the Contact Point Address DMO.
B. Map Account to Contact Point Email and Contact Point Phone also.
C. Make sure that the total account records are high enough for Identity resolution.
D. Change the cardinality to many-to-one to accommodate multiple contacts per account.

正解：D

解説：
* Relationship Cardinality: In Salesforce Data Cloud, defining the correct relationship cardinality between data model objects (DMOs) is crucial for accurate data representation and integration.
* 1-to-1 Relationship Error: The error occurs because the relationship between Account DMO and Contact Point Address DMO is set as 1-to-1, which implies that each account can only have one contact point address.
* Solution:
Change Cardinality: Modify the relationship cardinality to many-to-one. This allows multiple contact point addresses to be associated with a single account, reflecting real-world scenarios more accurately.
Steps:
Go to the data model configuration in Data Cloud.
Locate the relationship between Account DMO and Contact Point Address DMO.
Change the relationship type from 1-to-1 to many-to-one.
* Benefits:
Accurate Representation: Accommodates real-world data scenarios where an account may have multiple contact points.
Error Resolution: Resolves the error and ensures smooth data integration.
* Reference:
Salesforce Data Cloud Documentation: Relationships
Salesforce Help: Data Modeling in Data Cloud

質問 # 157
What should a user do to pause a segment activation with the intent of using that segment again?

A. Stop the publish schedule.
B. Deactivate the segment.
C. Delete the segment.
D. Skip the activation.

正解：B

解説：
The correct answer is A. Deactivate the segment. If a segment is no longer needed, it can be deactivated through Data Cloud and applies to all chosen targets. A deactivated segment no longer publishes, but it can be reactivated at any time1. This option allows the user to pause a segment activation with the intent of using that segment again.
The other options are incorrect for the following reasons:
B . Delete the segment. This option permanently removes the segment from Data Cloud and cannot be undone2. This option does not allow the user to use the segment again.
C . Skip the activation. This option skips the current activation cycle for the segment, but does not affect the future activation cycles3. This option does not pause the segment activation indefinitely.
D . Stop the publish schedule. This option stops the segment from publishing to the chosen targets, but does not deactivate the segment4. This option does not pause the segment activation completely.
Reference:
1: Deactivated Segment article on Salesforce Help
2: Delete a Segment article on Salesforce Help
3: Skip an Activation article on Salesforce Help
4: Stop a Publish Schedule article on Salesforce Help

質問 # 158
Northern Trail Outfitters (NTO) is configuring an identity resolution ruleset based on Fuzzy Name and Normalized Email.
What should NTO do to ensure the best email address is activated?

A. Set the default reconciliation rule to Last Updated.
B. Use the source priority order in activations to make sure a contact point from the desired source is delivered to the activation target.
C. Include Contact Point Email object Is Active field as a match rule.
D. Ensure Marketing Cloud is prioritized as the first data source in the Source Priority reconciliation rule.

正解：B

解説：
NTO is using Fuzzy Name and Normalized Email as match rules to link together data from different sources into a unified individual profile. However, there might be cases where the same email address is available from more than one source, and NTO needs to decide which one to use for activation. For example, if Rachel has the same email address in Service Cloud and Marketing Cloud, but prefers to receive communications from NTO via Marketing Cloud, NTO needs to ensure that the email address from Marketing Cloud is activated. To do this, NTO can use the source priority order in activations, which allows them to rank the data sources in order of preference for activation. By placing Marketing Cloud higher than Service Cloud in the source priority order, NTO can make sure that the email address from Marketing Cloud is delivered to the activation target, such as an email campaign or a journey. This way, NTO can respect Rachel's preference and deliver a better customer experience. References: Configure Activations, Use Source Priority Order in Activations

質問 # 159
A company wants to include certain personalized fields in an email by including related attributes during the activation in Data Cloud. It notices that some values, such as purchased product names, do not have consistent casing in Marketing Cloud Engagement. For example, purchased product names appear as follows: Jacket, jacket, shoes, SHOES. The company wants to normalize all names to proper case and replace any null values with a default value.
How should a consultant fulfill this requirement within Data Cloud?

A. Create one batch data transform per data stream.
B. Create a streaming insight with a data action.
C. Create one batch data transform that creates a new DLO.
D. Use formula fields when ingesting at the data stream level.

正解：C

解説：
To normalize purchased product names (e.g., converting casing to proper case and replacing null values with a default value) within Salesforce Data Cloud, the best approach is to create a batch data transform that generates a new DLO. Here's the detailed explanation:
Understanding the Problem :
The company wants to ensure that product names in Marketing Cloud Engagement are consistent and properly formatted. The inconsistencies in casing (e.g., "Jacket," "jacket," "shoes," "SHOES") and the presence of null values need to be addressed before activation.
Why Batch Data Transform?
A batch data transform allows you to process large volumes of data in bulk, making it ideal for cleaning and normalizing datasets.
By creating a new DLO, you ensure that the original data remains intact while providing a clean, transformed dataset for downstream use cases like email personalization.
Steps to Implement This Solution :
Step 1: Navigate to the Data Streams section in Salesforce Data Cloud and identify the data stream containing the purchased product names.
Step 2: Create a new batch data transform by selecting the relevant data stream as the source.
Step 3: Use transformation functions to normalize the product names:
Apply the PROPER() function to convert all product names to proper case.
Use the COALESCE() function to replace null values with a default value (e.g., "Unknown Product").
Step 4: Configure the batch data transform to output the results into a new DLO . This ensures that the transformed data is stored separately from the original dataset.
Step 5: Activate the new DLO for use in Marketing Cloud Engagement. Ensure that the email templates pull product names from the transformed DLO instead of the original dataset.
Why Not Other Options?
A . Create a streaming insight with a data action: Streaming insights are designed for real-time processing and are not suitable for bulk transformations like normalizing casing or replacing null values.
B . Use formula fields when ingesting at the data stream level: Formula fields are useful for simple calculations but are limited in scope and cannot handle complex transformations like null value replacement. Additionally, modifying the ingestion process may not be feasible if the data stream is already in use.
C . Create one batch data transform per data stream: This approach is inefficient and redundant. Instead of creating multiple transforms, a single batch transform can handle all the required changes and output a unified, clean dataset.
By creating a batch data transform that generates a new DLO, the company ensures that the product names are consistently formatted and ready for use in personalized emails, improving the overall customer experience.

質問 # 160
To import campaign members into a campaign in Salesforce CRM, a user wants to export the segment to Amazon S3. The resulting file needs to include the Salesforce CRM Campaign ID in the name.
What are two ways to achieve this outcome?
Choose 2 answers

A. Hard code the campaign identifier as a new attribute in the campaign activation.
B. Include campaign identifier in the segment name.
C. Include campaign identifier in the activation name.
D. Include campaign identifier in the filename specification.

正解：C、D

解説：
The two ways to achieve this outcome are A and C. Include campaign identifier in the activation name and include campaign identifier in the filename specification. These two options allow the user to specify the Salesforce CRM Campaign ID in the name of the file that is exported to Amazon S3. The activation name and the filename specification are both configurable settings in the activation wizard, where the user can enter the campaign identifier as a text or a variable. The activation name is used as the prefix of the filename, and the filename specification is used as the suffix of the filename. For example, if the activation name is
"Campaign_123" and the filename specification is "{segmentName}_{date}", the resulting file name will be
"Campaign_123_SegmentA_2023-12-18.csv". This way, the user can easily identify the file that corresponds to the campaign and import it into Salesforce CRM.
The other options are not correct. Option B is incorrect because hard coding the campaign identifier as a new attribute in the campaign activation is not possible. The campaign activation does not have any attributes, only settings. Option D is incorrect because including the campaign identifier in the segment name is not sufficient. The segment name is not used in the filename of the exported file, unless it is specified in the filename specification. Therefore, the user will not be able to see the campaign identifier in the file name.

質問 # 161
......

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