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NEW QUESTION # 92
Northern Trail Outfitters uses B2C Commerce and is exploring implementing Data Cloud to get a unified view of its customers and all their order transactions.
What should the consultant keep in mind with regard to historical data ingesting order data using the B2C Commerce Order Bundle?
Answer: D
Explanation:
The B2C Commerce Order Bundle is a data bundle that creates a data stream to flow order data from a B2C Commerce instance to Data Cloud. However, this data bundle does not ingest any historical data and only ingests new orders from the time the data stream is created. Therefore, if a consultant wants to ingest historical order data, they need to use a different method, such as exporting the data from B2C Commerce and importing it to Data Cloud using a CSV file12. Reference:
Create a B2C Commerce Data Bundle
Data Access and Export for B2C Commerce and Commerce Marketplace
NEW QUESTION # 93
Which consideration related to the way Data Cloud ingests CRM data is true?
Answer: C
Explanation:
The correct answer is D. The CRM Connector allows standard fields to stream into Data Cloud in real time.
This means that any changes to the standard fields in the CRM data source are reflected in Data Cloud almost instantly, without waiting for the next scheduled synchronization. This feature enables Data Cloud to have the most up-to-date and accurate CRM data for segmentation and activation1.
The other options are incorrect for the following reasons:
A). CRM data can be manually refreshed at any time by clicking the Refresh button on the data stream detail page2. This option is false.
B). The CRM Connector's synchronization times can be customized to up to 60-minute intervals, not 15- minute intervals3. This option is false.
C). Formula fields are not refreshed at regular sync intervals, but only at the next full refresh4. A full refresh is a complete data ingestion process that occurs once every 24 hours or when manually triggered. This option is false.
1: Connect and Ingest Data in Data Cloud article on Salesforce Help
2: Data Sources in Data Cloud unit on Trailhead
3: Data Cloud for Admins module on Trailhead
4: [Formula Fields in Data Cloud] unit on Trailhead
[Data Streams in Data Cloud] unit on Trailhead
NEW QUESTION # 94
A consultant needs to package Data Cloud components from one
organization to another.
Which two Data Cloud components should the consultant include in a
data kit to achieve this goal?
Choose 2 answers
Answer: B,C
Explanation:
To package Data Cloud components from one organization to another, the consultant should include the following components in a data kit:
* Data model objects: These are the custom objects that define the data model for Data Cloud, such as Individual, Segment, Activity, etc. They store the data ingested from various sources and enable the creation of unified profiles and segments1.
* Identity resolution rulesets: These are the rules that determine how data from different sources are matched and merged to create unified profiles. They specify the criteria, logic, and priority for identity resolution2. References:
* 1: Data Model Objects in Data Cloud
* 2: Identity Resolution Rulesets in Data Cloud
NEW QUESTION # 95
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
Answer: A,B,E
Explanation:
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. References: Create a Segment in Data Cloud, Use Insights in Data Cloud, Data Cloud Data Model
NEW QUESTION # 96
Which two requirements must be met for a calculated insight to appear in the segmentation canvas?
Choose 2 answers
Answer: B,C
Explanation:
A calculated insight is a custom metric or measure that is derived from one or more data model objects or data lake objects in Data Cloud. A calculated insight can be used in segmentation to filter or group the data based on the calculated value. However, not all calculated insights can appear in the segmentation canvas. There are two requirements that must be met for a calculated insight to appear in the segmentation canvas:
The calculated insight must contain a dimension including the Individual or Unified Individual Id. A dimension is a field that can be used to categorize or group the data, such as name, gender, or location. The Individual or Unified Individual Id is a unique identifier for each individual profile in Data Cloud. The calculated insight must include this dimension to link the calculated value to the individual profile and to enable segmentation based on the individual profile attributes.
The primary key of the segmented table must be a dimension in the calculated insight. The primary key is a field that uniquely identifies each record in a table. The segmented table is the table that contains the data that is being segmented, such as the Customer or the Order table. The calculated insight must include the primary key of the segmented table as a dimension to ensure that the calculated value is associated with the correct record in the segmented table and to avoid duplication or inconsistency in the segmentation results.
Create a Calculated Insight, Use Insights in Data Cloud, Segmentation
NEW QUESTION # 97
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