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| Section | Objectives |
|---|---|
| Topic 1: Data Ingestion and Data Modeling | - Data ingestion methods and connectors - Data spaces and object modeling concepts - Data mapping and transformation |
| Topic 2: Segmentation and Activation | - Activation to downstream systems - Segment creation and audience building |
| Topic 3: Identity Resolution | - Identity resolution rules and matching strategies - Profile unification and resolution process |
| Topic 4: Data Cloud Fundamentals | - Data model and architecture overview - Core concepts of Salesforce Data Cloud |
| Topic 5: Data Governance and Compliance | - Data privacy and compliance considerations - Data access controls and permissions |
| Topic 6: Data Cloud Implementation and Use Cases | - Common business use cases and solutions - Integration with Salesforce ecosystem |
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質問 # 12
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?
正解：D
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.
References:
* Create a Container Block
* Create a Segment in Data Cloud
* Create and Publish a Data Kit
* Create a Nested Segment
質問 # 13
Northern Trail Outfitters (NTO) asks its Data Cloud consultant for a list of contacts who fit within a certain segment for a mailing campaign.
How should the consultant provide this list to NTO?
正解：B
質問 # 14
The Salesforce CRM Connector is configured and the Case object data stream is set up. Subsequently, a new custom field named Business Priority is created on the Case object in Salesforce CRM. However, the new field is not available when trying to add it to the data stream.
Which statement addresses the cause of this issue?
正解：D
解説：
Explanation
The Salesforce CRM Connector uses the Salesforce Integration User to access the data from the Salesforce CRM org. The Integration User must have the Read permission on the fields that are included in the data stream. If the Integration User does not have the Read permission on the newly created field, the field will not be available for selection in the data stream configuration. To resolve this issue, the administrator should assign the Read permission on the new field to the Integration User profile or permission set. References: Create a Salesforce CRM Data Stream, Edit a Data Stream, Salesforce Data Cloud Full Refresh for CRM, SFMC, or Ingestion API Data Streams
質問 # 15
A consultant wants to build a new audience in Data Cloud.
Which three criteria can the consultant include when building a segment?
Choose 3 answers
正解：A、D、E
解説：
A segment is a subset of individuals who meet certain criteria based on their attributes and behaviors. A consultant can use different types of criteria when building a segment in Data Cloud, such as:
Direct attributes: These are attributes that describe the characteristics of an individual, such as name, email, gender, age, etc. These attributes are stored in the Profile data model object (DMO) and can be used to filter individuals based on their profile data.
Calculated Insights: These are insights that perform calculations on data in a data space and store the results in a data extension. These insights can be used to segment individuals based on metrics or scores derived from their data, such as customer lifetime value, churn risk, loyalty tier, etc.
Related attributes: These are attributes that describe the relationships of an individual with other DMOs, such as Email, Engagement, Order, Product, etc. These attributes can be used to segment individuals based on their interactions or transactions with different entities, such as email opens, clicks, purchases, etc.
The other two options are not valid criteria for building a segment in Data Cloud. Data stream attributes are attributes that describe the streaming data that is ingested into Data Cloud from various sources, such as Marketing Cloud, Commerce Cloud, Service Cloud, etc. These attributes are not directly available for segmentation, but they can be transformed and stored in data extensions using streaming data transforms. Streaming insights are insights that analyze streaming data in real time and trigger actions based on predefined conditions. These insights are not used for segmentation, but for activation and personalization. Reference: Create a Segment in Data Cloud, Use Insights in Data Cloud, Data Cloud Data Model
質問 # 16
A consultant is building a segment to announce a new product launch for customers that have previously purchased black pants.
How should the consultant place attributes for product color and product type from the Order Product object to meet this criteria?
正解：C
解説：
Explanation
To create a segment based on the product color and product type from the Order Product object, the consultant should place the attributes for product color and product type in a single container. This way, the segment will include only the customers who have purchased black pants, and not those who have purchased black shirts or blue pants. A container is a grouping of attributes that defines a segment of individuals based on a logical AND operation. Placing the attributes in separate containers would result in a segment that includes customers who have purchased any black product or any pants product, which is not the desired criteria. Placing an attribute for the "black" calculated insight would not work, because calculated insights are based on aggregated data and not individual-level data. Placing the attributes as direct attributes would not work, because direct attributes are used to filter individuals based on their profile data, not their order data. References:
* Create a Segment in Data Cloud
* Learn About Segmentation Tools
* Salesforce Launches: Data Cloud Consultant Certification
質問 # 17
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