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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Segmentation and Insights | 18% | - Segment creation and configuration - Calculated vs streaming insights - Segment membership analysis - Insight implementation |
| Topic 2: Act on Data | 18% | - Activation concepts and use cases - Attribute usage and management - Process automation and triggering - Troubleshooting activations |
| Topic 3: Data Cloud Setup and Administration | 12% | - Data spaces and configuration - Monitoring and maintenance tools - Permissions and access control - Data streams and data bundles |
| Topic 4: Identity Resolution | 14% | - Unified profile creation - Identity use cases - Conflict resolution - Matching and reconciliation rules |
| Topic 5: Data Ingestion and Modeling | 20% | - Data validation and inspection - Transformation and mapping - Ingestion from various sources - Data modeling best practices |
| Topic 6: Data Cloud Overview | 18% | - Core concepts and terminology - Architecture and ecosystem - Business value and use cases |
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NEW QUESTION # 43
What does the Ignore Empty Value option do in identity resolution?
Answer: A
Explanation:
The Ignore Empty Value option in identity resolution allows customers to ignore empty fields when running reconciliation rules. Reconciliation rules are used to determine the final value of an attribute for a unified individual profile, based on the values from different sources. The Ignore Empty Value option can be set to true or false for each attribute in a reconciliation rule. If set to true, the reconciliation rule will skip any source that has an empty value for that attribute and move on to the next source in the priority order. If set to false, the reconciliation rule will consider any source that has an empty value for that attribute as a valid source and use it to populate the attribute value for the unified individual profile.
The other options are not correct descriptions of what the Ignore Empty Value option does in identity resolution. The Ignore Empty Value option does not affect the custom match rules or the standard match rules, which are used to identify and link individuals across different sources based on their attributes. The Ignore Empty Value option also does not ignore individual object records with empty fields when running identity resolution rules, as identity resolution rules operate on the attribute level, not the record level.
Data Cloud Identity Resolution Reconciliation Rule Input
Configure Identity Resolution Rulesets
Data and Identity in Data Cloud
NEW QUESTION # 44
How does Data Cloud handle an individual's Right to be Forgotten?
Answer: C
Explanation:
Data Cloud handles an individual's Right to be Forgotten by deleting the specified Individual and records from any data model object/data lake object related to the Individual. This means that Data Cloud removes all the data associated with the individual from the data space, including the data from the source objects, the unified individual profile, and any related objects. Data Cloud also deletes the Unified Individual Link record that links the individual to the source records. Data Cloud uses the Consent API to process the Right to be Forgotten requests, which are reprocessed at 30, 60, and 90 days to ensure a full deletion.
The other options are not correct descriptions of how Data Cloud handles an individual's Right to be Forgotten. Data Cloud does not delete the records from all data source objects, as this would affect the data integrity and availability of the source systems. Data Cloud also does not delete only the specified Individual record and its Unified Individual Link record, as this would leave the source records and the related records intact. Data Cloud also does not delete only the specified Individual and records from any data source object mapped to the Individual data model object, as this would leave the related records intact.
Requesting Data Deletion or Right to Be Forgotten
Data Deletion for Data Cloud
Use the Consent API with Data Cloud
Data and Identity in Data Cloud
NEW QUESTION # 45
A customer wants to use the transactional data from their data warehouse in Data Cloud.
They are only able to export the data via an SFTP site.
How should the file be brought into Data Cloud?
Answer: B
Explanation:
The SFTP Connector is a data source connector that allows Data Cloud to ingest data from an SFTP server.
The customer can use the SFTP Connector to create a data stream from their exported file and bring it into Data Cloud as a data lake object. The other options are not the best ways to bring the file into Data Cloud because:
B). The Cloud Storage Connector is a data source connector that allows Data Cloud to ingest data from cloud storage services such as Amazon S3, Azure Storage, or Google Cloud Storage. The customer does not have their data in any of these services, but only on an SFTP site.
C). The Data Import Wizard is a tool that allows users to import data for many standard Salesforce objects, such as accounts, contacts, leads, solutions, and campaign members. It is not designed to import data from an SFTP site or for custom objects in Data Cloud.
D). The Dataloader is an application that allows users to insert, update, delete, or export Salesforce records. It is not designed to ingest data from an SFTP site or into Data Cloud. References: SFTP Connector - Salesforce, Create Data Streams with the SFTP Connector in Data Cloud - Salesforce, Data Import Wizard - Salesforce, Salesforce Data Loader
NEW QUESTION # 46
Which two applications automatically create activation targets at the time the application is connected to Data Cloud?
Answer: B,C
Explanation:
These two applications automatically create activation targets when they are connected to Data Cloud. You can use these targets to activate segments or calculated insights to these applications. References:
https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_activation.htm&type=5
NEW QUESTION # 47
What is a DMO called if it inherits the name, shape, and semantics of the reference object?
Answer: C
Explanation:
Explanation
A Data Model Object (DMO) that inherits the name, shape, and semantics of the reference object is called a Standard DMO. A reference object is a predefined object in the Data Cloud data model that represents a common entity or concept, such as Individual, Order, or Product. A Standard DMO is a copy of a reference object that you can use to ingest data from a specific source without modifying the original reference object. A Standard DMO has the same fieldsand relationships as the reference object, but you can add custom fields or relationships to it if needed. References: Data Model Objects
NEW QUESTION # 48
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