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| Section | Objectives |
|---|---|
| Activation | - Describe activation use cases - Configure activations to various targets |
| Segmentation and Calculated Insights | - Explain calculated insights - Create and manage segments |
| Data Ingestion and Modeling | - Describe data streams and data sources - Explain data modeling concepts including Data Model Objects (DMOs) |
| Data Cloud Reporting and Analytics | - Utilize Data Cloud reports and dashboards |
| Data Cloud Setup and Administration | - Configure Data Cloud settings - Manage Data Cloud permissions and security |
| Identity Resolution | - Describe matching and reconciliation rules - Explain the purpose and configuration of Identity Resolution |
| Data Cloud Overview | - Explain the purpose and functionality of Data Cloud - Describe the Data Cloud ecosystem and how it fits into the Salesforce platform |
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NEW QUESTION # 141
Northern Trail Outfitters wants to be able to calculate each customer's lifetime value (LTV) but also create breakdowns of the revenue sourced by website, mobile app, and retail channels. How should this use case be addressed in Data Cloud?
Answer: D
Explanation:
This feature can help Northern Trail Outfitters calculate each customer's lifetime value (LTV) and create breakdowns of the revenue sourced by different channels. Streaming data transformations allow you to transform and enrich streaming data from different sources using formulas and operators. Reference: https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_streaming_data_transform.htm&type=5
NEW QUESTION # 142
Which two common use cases can be addressed with Data Cloud?
Answer: C,D
Explanation:
Data Cloud can address these two common use cases by providing a platform that allows customers to ingest, map, enrich, and activate data from various sources using the Customer 360 data model, and by enabling customers to create segments, insights, and activations based on their customer data. Reference: [Data Cloud Overview], [Customer 360 Data Model], [Data Activation]
NEW QUESTION # 143
Cumulus Financial wants to be able to track the daily transaction volume of each of its customers in real time and send out a notification as soon as it detects volume outside a customer's normal range.
What should a consultant do to accommodate this request?
Answer: B
Explanation:
A streaming insight is a type of insight that analyzes streaming data in real time and triggers actions based on predefined conditions. A data action is a type of action that executes a flow, a data action target, or a data action script when an insight is triggered. By using a streaming insight paired with a data action, a consultant can accommodate Cumulus Financial's request to track the daily transaction volume of each customer and send out a notification when the volume is outside the normal range. A calculated insight is a type of insight that performs calculations on data in a data space and stores the results in a data extension. A streaming data transform is a type of data transform that applies transformations to streaming data in real time and stores the results in a data extension. A flow is a type of automation that executes a series of actions when triggered by an event, a schedule, or another flow. None of these options can achieve the same functionality as a streaming insight paired with a data action. References: Use Insights in Data Cloud Unit, Streaming Insights and Data Actions Use Cases, Streaming Insights and Data Actions Limits and Behaviors
NEW QUESTION # 144
Which three actions can be applied to a previously created segment?
Answer: A,B,C
Explanation:
These three actions can be applied to apreviously created segment. You can export a segment to a CSV file, delete a segment from Data Cloud, or copy a segment to create a duplicate segment with the same criteria.
References:https://help.salesforce.com/s/articleView?id=sf.c360_a_segmentation_actions.htm&type=5
NEW QUESTION # 145
A consultant is planning the ingestion of a data stream that has profile information including a mobile phone number.
To ensure that the phone number can be used for future SMS campaigns, they need to confirm the phone number field is in the proper E164 Phone Number format. However, the phone numbers in the file appear to be in varying formats.
What is the most efficient way to guarantee that the various phone number formats are standardized?
Answer: B
Explanation:
The most efficient way to guarantee that the various phone number formats are standardized is to assign the PhoneNumber field type when creating the data stream. The PhoneNumber field type is a special field type that automatically converts phone numbers into the E164 format, which is the international standard for phone numbers. The E164 format consists of a plus sign (+), the country code, and the national number. For example, +1-202-555-1234 is the E164 format for a US phone number. By using the PhoneNumber field type, the consultant can ensure that the phone numbers are consistent and can be used for future SMS campaigns.
The other options are either more time-consuming, require manual intervention, or do not address the formatting issue. References: Data Stream Field Types, E164 Phone Number Format, Salesforce Data Cloud Exam Questions
NEW QUESTION # 146
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