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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Segmentation and Insights | 18% | - Segment creation and configuration - Segment membership analysis - Insight implementation - Calculated vs streaming insights |
| Topic 2: Act on Data | 18% | - Activation concepts and use cases - Process automation and triggering - Troubleshooting activations - Attribute usage and management |
| Topic 3: Data Cloud Overview | 18% | - Architecture and ecosystem - Core concepts and terminology - Business value and use cases |
| Topic 4: Data Ingestion and Modeling | 20% | - Data validation and inspection - Ingestion from various sources - Data modeling best practices - Transformation and mapping |
| Topic 5: Identity Resolution | 14% | - Matching and reconciliation rules - Conflict resolution - Identity use cases - Unified profile creation |
| Topic 6: Data Cloud Setup and Administration | 12% | - Monitoring and maintenance tools - Permissions and access control - Data streams and data bundles - Data spaces and configuration |
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NEW QUESTION # 137
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?
Answer: C
Explanation:
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. Reference: https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_amazon_s3.htm&type=5
NEW QUESTION # 138
How does an administrator increase the consolidation rate for Identity Resolution?
Answer: C
Explanation:
Reducing the number of matching rules can increase the consolidation rate for Identity Resolution, because it reduces the chances of finding multiple matches for the same individual. Matching rules tell Data Cloud which profiles to unify during the identity resolution process. If there are too many matching rules, Data Cloud might find more than one match for a given profile, resulting in a lower consolidation rate. Reference: Identity Resolution Match Rules
NEW QUESTION # 139
What is a unique requirement of a Streaming Insight query?
Answer: B
Explanation:
A window function is a unique requirement of a Streaming Insight query. It defines the time interval for the query to run on the streaming data and the frequency of the query execution. Reference: https://help.salesforce.com/s/articleView?id=sf.c360_a_streaming_insights.htm&type=5
NEW QUESTION # 140
What happens if no file name is specified in AWS S3 data stream during ingestion?
Answer: C
Explanation:
If no file name is specified in AWS S3 data stream during ingestion, the system does not fetch any file and the data stream shows an error. AWS S3 data stream is a feature that allows you to stream data from Amazon Web Services Simple Storage Service (AWS S3) to Data Cloud in near real time. You need to specify the file name or prefix of the files that you want to ingest from your S3 bucket. If you leave this field blank, the system cannot find any matching files and returns an error message. Reference: AWS S3 Data Stream
NEW QUESTION # 141
A user wants to be able to create a multi-dimensional metric to identify unified individual lifetime value (LTV).
Which sequence of data model object (DMO) joins is necessary within the calculated Insight to enable this calculation?
Answer: D
Explanation:
To create a multi-dimensional metric to identify unified individual lifetime value (LTV), the sequence of data model object (DMO) joins that is necessary within the calculated Insight is Unified Individual > Unified Link Individual > Sales Order. This is because the Unified Individual DMO represents the unified profile of an individual or entity that is created by identity resolution1. The Unified Link Individual DMO represents the link between a unified individual and an individual from a source system2. The Sales Order DMO represents the sales order information from a source system3. By joining these three DMOs, you can calculate the LTV of a unified individual based on the sales order data from different source systems. The other options are incorrect because they do not join the correct DMOs to enable the LTV calculation. Option B is incorrect because the Individual DMO represents the source profile of an individual or entity from a source system, not the unified profile4. Option C is incorrect because the join order is reversed, and you need to start with the Unified Individual DMO to identify the unified profile. Option D is incorrect because it is missing the Unified Link Individual DMO, which is needed to link the unified profile with the source profile. References: Unified Individual Data Model Object, Unified Link Individual Data Model Object, Sales Order Data Model Object, Individual Data Model Object
NEW QUESTION # 142
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