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| Section | Objectives |
|---|---|
| Salesforce Data Cloud Fundamentals | - Core concepts and architecture - Data Cloud value and use cases |
| Identity Resolution and Unification | - Unified customer profile concepts - Identity resolution rules |
| Data Ingestion and Data Modeling | - Data model objects and harmonization - Data sources and ingestion methods |
| Segmentation and Activation | - Segmentation logic and audience building - Activation to Salesforce and external systems |
| Data Governance and Privacy | - Data privacy and compliance concepts - Security and data access controls |
>> Salesforce-Data-Cloud最新対策問題 <<
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質問 # 40
A Data Cloud customer wants to adjust their identity resolution rules to increase their accuracy of matches. Rather than matching on email address, they want to review a rule that joins their CRM Contacts with their Marketing Contacts, where both use the CRM ID as their primary key.
Which two steps should the consultant take to address this new use case?
Choose 2 answers
正解：A、D
解説：
To address this new use case, the consultant should map the primary key from the two systems to Party Identification, using CRM ID as the identification name for both, and create a matching rule based on party identification that matches on CRM ID as the party identification name. This way, the consultant can ensure that the CRM Contacts and Marketing Contacts are matched based on their CRM ID, which is a unique identifier for each individual. By using Party Identification, the consultant can also leverage the benefits of this attribute, such as being able to match across different entities and sources, and being able to handle multiple values for the same individual. The other options are incorrect because they either do not use the CRM ID as the primary key, or they do not use Party Identification as the attribute type. References: Configure Identity Resolution Rulesets, Identity Resolution Match Rules, Data Cloud Identity Resolution Ruleset, Data Cloud Identity Resolution Config Input
質問 # 41
Which data model subject area should be used for any Organization, Individual, or Member in the Customer 360 data model?
正解：D
解説：
The party subject area should be used for any organization, individual, or member in the Customer 360 data model. It includes information such as name, address, email, phone, and loyalty membership. Reference: https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_party.htm&type=5
質問 # 42
To import campaign members into a campaign in CRM a user wants to export the segment to Amazon S3. The resulting file needs to include CRM Campaign ID in the name. How can this outcome be achieved?
正解：A
解説：
You can use the filename specification option in the Amazon S3 activation to customize the name of the file that is exported. You can use variables such as {campaignId} to include the CRM campaign ID in the file name. References:
https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_amazon_s3.htm&type=5
質問 # 43
The recruiting team at Cumulus Financial wants to identify which candidates have browsed the jobs page on its website at least twice within the last 24 hours. They want the information about these candidates to be available for segmentation in Data Cloud and the candidates added to their recruiting system.
Which feature should a consultant recommend to achieve this goal?
正解：B
解説：
A streaming insight is a feature that allows users to create and monitor real-time metrics from streaming data sources, such as web and mobile events. A streaming insight can also trigger data actions, such as sending notifications, creating records, or updating fields, based on the metric values and conditions. Therefore, a streaming insight is the best feature to achieve the goal of identifying candidates who have browsed the jobs page on the website at least twice within the last 24 hours, and adding them to the recruiting system. The other options are incorrect because:
A streaming data transform is a feature that allows users to transform and enrich streaming data using SQL expressions, such as filtering, joining, aggregating, or calculating values. However, a streaming data transform does not provide the ability to monitor metrics or trigger data actions based on conditions.
A calculated insight is a feature that allows users to define and calculate multidimensional metrics from data using SQL expressions, such as LTV, CSAT, or average order value. However, a calculated insight is not suitable for real-time data analysis, as it runs on a scheduled basis and does not support data actions.
A batch data transform is a feature that allows users to create and schedule complex data transformations using a visual editor, such as joining, aggregating, filtering, or appending data. However, a batch data transform is not suitable for real-time data analysis, as it runs on a scheduled basis and does not support data actions. References: Streaming Insights, Create a Streaming Insight, Use Insights in Data Cloud, Learn About Data Cloud Insights, Data Cloud Insights Using SQL, Streaming Data Transforms, Get Started with Batch Data Transforms in Data Cloud, Transformations for Batch Data Transforms, Batch Data Transforms in Data Cloud: Quick Look, Salesforce Data Cloud: AI CDP.
質問 # 44
How many days of historical data is loaded when B2C Commerce Data Stream is created from the Order Bundle?
正解：D
解説：
When B2C Commerce Data Stream is created from the Order Bundle, 30 days of historical data is loaded. The Order Bundle is a preconfigured data bundle that contains order-related data from B2C Commerce Cloud. Data Stream is a feature that allows you to stream data from B2C Commerce Cloud to Data Cloud in near real time. Reference: B2C Commerce Data Stream
質問 # 45
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