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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Act on Data | 18% | - Activation concepts and use cases - Attribute usage and management - Troubleshooting activations - Process automation and triggering |
| Topic 2: Identity Resolution | 14% | - Unified profile creation - Matching and reconciliation rules - Identity use cases - Conflict resolution |
| Topic 3: Data Ingestion and Modeling | 20% | - Data modeling best practices - Transformation and mapping - Data validation and inspection - Ingestion from various sources |
| Topic 4: Data Cloud Overview | 18% | - Business value and use cases - Core concepts and terminology - Architecture and ecosystem |
| Topic 5: Data Cloud Setup and Administration | 12% | - Monitoring and maintenance tools - Permissions and access control - Data spaces and configuration - Data streams and data bundles |
| Topic 6: Segmentation and Insights | 18% | - Insight implementation - Segment membership analysis - Calculated vs streaming insights - Segment creation and configuration |
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NEW QUESTION # 138
Which option allows an organization an easy way to ingest Marketing Cloud subscriber profile attributes into Data Cloud on a daily basis?
Answer: A
Explanation:
Thisoption allows an organization an easy way to ingest Marketing Cloud subscriber profile attributes into Data Cloud on a daily basis. You can use Automation Studio to export profile attributes to a data extension and use the Profile API to send them to DataCloud. References:https://help.salesforce.com/s/articleView?
id=sf.c360_a_data_cloud_marketing_cloud_data_foundation.htm&type=5
NEW QUESTION # 139
When setting up the data source object or schema for data ingestion, what are the three data categories to select from?
Answer: A,C,E
Explanation:
These are the three data categories to select from when setting up the data source object or schema for data ingestion. Engagement data includes information about how customers interact with a brand or product, such as clicks, views, likes, etc. Order data includes information about transactions or purchases made by customers, such as order ID, amount, date, etc. Profile data includes information about customers' attributes or preferences, such as name, email, gender, etc. Reference: [Data Categories]
NEW QUESTION # 140
Cumulus Financial created a segment called High Investment Balance Customers. This is a foundational segment that includes several segmentation criteria the marketing team should consistently use.
Which feature should the consultant suggest the marketing team use to ensure this consistency when creating future, more refined segments?
Answer: D
Explanation:
Nested segments are segments that include or exclude one or more existing segments. They allow the marketing team to reuse filters and maintain consistency in their data by using an existing segment to build a new one. For example, the marketing team can create a nested segment that includes High Investment Balance Customers and excludes customers who have opted out of email marketing. This way, they can leverage the foundational segment and apply additional criteria without duplicating the rules. The other options are not the best features to ensure consistency because:
B). A calculated insight is a data object that performs calculations on data lake objects or CRM data and returns a result. It is not a segment and cannot be used for activation or personalization.
C). A data kit is a bundle of packageable metadata that can be exported and imported across Data Cloud orgs.
It is not a feature for creating segments, but rather for sharing components.
D). Cloning a segment creates a copy of the segment with the same rules and filters. It does not allow the marketing team to add or remove criteria from the original segment, and it may create confusion and redundancy. References: Create a Nested Segment - Salesforce, Save Time with Nested Segments (Generally Available) - Salesforce, Calculated Insights - Salesforce, Create and Publish a Data Kit Unit | Salesforce Trailhead, Create a Segment in Data Cloud - Salesforce
NEW QUESTION # 141
Northern Trail Outfitters uploads new customer data to an Amazon S3 Bucket on a daily basis to be ingested in Data Cloud. In what order should each process be run to ensure that freshly imported data is ready and available to use for any segment?
Answer: A
Explanation:
The recommended order of processes for updating data in Data Cloud is as follows6:
Refresh Data Stream: This process updates the data from the source, such as Amazon S3, into Data Cloud.
Identity Resolution: This process runs the rulesets that link together multiple records of an individual into a unified profile.
Calculated Insight: This process calculates additional attributes based on existing data, such as lifetime value or churn risk.
NEW QUESTION # 142
Which of these is present in Identity Resolution Summary?
Answer: D
Explanation:
The Identity Resolution Summary page shows all the above information: Unified Individuals, Last Processing Status, and Matched Individuals. Unified Individuals are the profiles that Data Cloud creates by linking multiple source profiles based on match rules. Last Processing Status shows the date and time of the last identity resolution run and whether it was successful or not. Matched Individuals shows the number and percentage of source profiles that were matched to a unified individual profile. References: Identity Resolution Summary
NEW QUESTION # 143
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