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| Section | Objectives |
|---|---|
| Data Ingestion and Data Modeling | - Data model objects and harmonization - Data sources and ingestion methods |
| Data Governance and Privacy | - Security and data access controls - Data privacy and compliance concepts |
| Salesforce Data Cloud Fundamentals | - Core concepts and architecture - Data Cloud value and use cases |
| Segmentation and Activation | - Segmentation logic and audience building - Activation to Salesforce and external systems |
| Identity Resolution and Unification | - Unified customer profile concepts - Identity resolution rules |
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NEW QUESTION # 128
Northern Trail Outfitters has the following customer data to ingest into Data Cloud and use for segmentation.
1. Propensity to purchase
2. Has active membership
3. Work email address
Which data types should the consultant use when ingesting this data?
Answer: A
Explanation:
When ingesting customer data into Data Cloud, it is critical to use the correct data types to ensure proper segmentation and usage. Here's how the consultant should handle the provided data points:
Propensity to Purchase :
This represents a likelihood or probability value, typically expressed as a percentage (e.g., 75%).
The appropriate data type for this field is Percent , which allows for easy interpretation and use in segmentation.
Has Active Membership :
This is a binary value indicating whether a customer has an active membership (e.g., "Yes" or "No").
The correct data type for this field is Boolean , which supports true/false values.
Work Email Address :
This is a standard email address field.
The appropriate data type is Email , which ensures proper validation and formatting.
Why Not Other Options?
A). Number, Text, URL: These data types are incorrect because "Propensity to Purchase" should be a percentage, not a generic number. Similarly, "Work Email Address" should be an email type, not a URL.
C). Number, Boolean, Text: While "Number" could work for propensity scores, it lacks the semantic meaning of a percentage. Additionally, "Text" is not suitable for email addresses.
D). Percent, Number, Email: Using "Number" for "Has Active Membership" is incorrect because it is a binary value, not a numeric one.
By selecting Percent, Boolean, Email , the consultant ensures that the data is correctly formatted and ready for segmentation and analysis.
NEW QUESTION # 129
Northern Trail Outfitters (NTO) is configuring an identity resolution ruleset based on Fuzzy Name and Normalized Email.
What should NTO do to ensure the best email address is activated?
Answer: B
Explanation:
NTO is using Fuzzy Name and Normalized Email as match rules to link together data from different sources into a unified individual profile. However, there might be cases where the same email address is available from more than one source, and NTO needs to decide which one to use for activation. For example, if Rachel has the same email address in Service Cloud and Marketing Cloud, but prefers to receive communications from NTO via Marketing Cloud, NTO needs to ensure that the email address from Marketing Cloud is activated. To do this, NTO can use the source priority order in activations, which allows them to rank the data sources in order of preference for activation. By placing Marketing Cloud higher than Service Cloud in the source priority order, NTO can make sure that the email address from Marketing Cloud is delivered to the activation target, such as an email campaign or a journey. This way, NTO can respect Rachel's preference and deliver a better customer experience. References: Configure Activations, Use Source Priority Order in Activations
NEW QUESTION # 130
A customer has requested that their personal data be deleted. Which action should be performed to accommodate this request in Data Cloud?
Answer: D
Explanation:
This action should be performed to accommodate the request to delete personal data in Data Cloud. The Consent API allows you to set a consent flag for an individual that prevents further processing of their data and deletes their records from source data streams. References:
https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_consent_api.htm&type=5
NEW QUESTION # 131
What can be customized in the Data Cloud canonical model?
Answer: C
Explanation:
Explanation
You can customize the Data Cloud canonical model by adding, editing, or deleting objects, fields, and relationships. You can also modify the properties, labels, and descriptions of these components.
References:https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_canonical_model.htm&type=5
NEW QUESTION # 132
An administrator has configured the Salesforce CRM connector and set up a data stream for the Case object.
A new custom field called "Business Priority" was created on the Case object. However, that field is not available when trying to add it in the data stream. What could be causing this issue?
Answer: A
Explanation:
One possible reason why a new custom field is not available inthe data stream is that the Salesforce Integration User, which is used to connect to the CRM source, does not have "Read"permissions on that field2. To fix this issue, the administrator needs to grant the appropriate permissions to the Integration User profile or permission set.
NEW QUESTION # 133
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