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| Section | Weight | Objectives |
|---|---|---|
| Data Cloud Overview and Licensing | 7% | - Describe Data Cloud setup and configuration - Describe the business value of Data Cloud - Explain licensing model and capacity |
| Calculated Insights | 8% | - Define metrics and measurements - Create and configure calculated insights - Use formulas and functions in calculations - Publish insights to Data Cloud |
| Data Sharing and Security | 8% | - Implement row-level security - Understand data governance requirements - Configure data sharing settings - Manage user access and permissions |
| Data Cloud Monitoring and Troubleshooting | 22% | - Debug common configuration errors - Troubleshoot data quality issues - Analyze identity resolution results - Manage data retention and cleanup - Monitor data ingestion and sync status - Use Data Cloud analytics and reports |
| Data Model Setup and Configuration | 15% | - Describe Harmonized Data Model concepts - Configure custom objects, fields, and relationships - Set up and configure Data Lake objects - Map source data to harmonized data model - Understand data types and field mapping |
| Data Ingestion | 15% | - Troubleshoot ingestion issues - Configure data sync and refresh schedules - Set up and manage data connectors - Configure streaming data ingestion - Configure batch data ingestion |
| Data Actions | 8% | - Configure data sync to external systems - Set up segmentation and target audiences - Configure data actions for activation - Create and manage data bundles |
| Identity Resolution and Data Unification | 17% | - Understand unified records creation - Configure match rules and strategies - Manage data overlap and deduplication - Configure contact and account matching - Configure identity resolution rules |
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NEW QUESTION # 78
A user has built a segment in Data Cloud and is in the process of creating an activation. When selecting related attributes, they cannot find a specific set of attributes they know to be related to the individual.
Which statement explains why these attributes are not available?
Answer: B
Explanation:
The correct answer is C, the desired attributes reside on different related paths. When creating an activation in Data Cloud, you can select related attributes from data model objects that are linked to the segment entity.
However, not all related attributes are available for every activation. The availability of related attributes depends on the container path, which is the sequence of data model objects that connects the segment entity to the related entity. For example, if you segment on the Unified Individual entity, you can select related attributes from the Order Product entity, but only if the container path is Unified Individual > Order > Order Product. If the container path is Unified Individual > Order Line Item > Order Product, then the related attributes from Order Product are not available for activation. This is because Data Cloud only supports one-to-many relationships for related attributes, and Order Line Item is a many-to-many junction object between Order and Order Product. Therefore, you need to ensure that the desired attributes reside on the same related path as the segment entity, and that the path does not include any many-to-many junction objects. The other options are incorrect because they do not explain why the related attributes are not available. The segment entity can be any data model object, not just profile data. The attributes are not restricted by being used in another activation. Activations can include one-to-many attributes, not just one-to-one attributes. References:
* Related Attributes in Activation
* Considerations for Selecting Related Attributes
* Salesforce Launches: Data Cloud Consultant Certification
* Create a Segment in Data Cloud
NEW QUESTION # 79
How does Data Cloud handle an individual's Right to be Forgotten?
Answer: D
Explanation:
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.
References:
* 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 # 80
A user needs permissions to access Data Cloud to create, manage, and activate segments, However, the user should not be allowed to created reports or manage data sources.
Which permission set should the consultant assign?
Answer: D
Explanation:
To grant a user permissions to create, manage, and activate segments without allowing them to create reports or manage data sources, the consultant should assign the Data Cloud Marketing Specialist permission set. Here's why:
Understanding the Role Requirements :
The user needs access to segment creation, management, and activation.
The user should not have permissions to create reports or manage data sources, which are higher-level administrative tasks.
Why Data Cloud Marketing Specialist?
The Data Cloud Marketing Specialist permission set provides access to segment-related functionalities, including creating, managing, and activating segments.
It excludes permissions for creating reports or managing data sources, aligning perfectly with the stated requirements.
Steps to Assign the Permission Set :
Step 1: Navigate to Setup > Users > Permission Sets in Salesforce.
Step 2: Locate and assign the Data Cloud Marketing Specialist permission set to the user.
Step 3: Verify that the user has the required permissions by testing their access in Data Cloud.
Why Not Other Options?
B . Data Cloud Marketing Manager: This permission set includes broader permissions, such as managing campaigns and audiences, which are not required for this role.
C . Data Cloud Data Aware Specialist: This role focuses on data ingestion and transformation, not segment management.
D . Data Cloud User: This is a basic permission set that provides limited access and does not include segment management capabilities.
By assigning the Data Cloud Marketing Specialist permission set, the consultant ensures that the user has the necessary permissions without overextending their access.
NEW QUESTION # 81
Every day, Northern Trail Outfitters uploads a summary of the last 24 hours of store transactions to a new file in an Amazon S3 bucket, and files older than seven days are automatically deleted. Each file contains a timestamp in a standardized naming convention.
Which two options should a consultant configure when ingesting this data stream?
Choose 2 answers
Answer: C,D
Explanation:
When ingesting data from an Amazon S3 bucket, the consultant should configure the following options:
* The refresh mode should be set to "Upsert", which means that new and updated records will be added or updated in Data Cloud, while existing records will be preserved. This ensures that the data is always up to date and consistent with the source.
* The filename should contain a wildcard to accommodate the timestamp, which means that the file name pattern should include a variable part that matches the timestamp format. For example, if the file name is store_transactions_2023-12-18.csv, the wildcard could be store_transactions_*.csv. This ensures that the ingestion process can identify and process the correct file every day.
The other options are not necessary or relevant for this scenario:
* Deletion of old files is a feature of the Amazon S3 bucket, not the Data Cloud ingestion process. Data Cloud does not delete any files from the source, nor does it require the source files to be deleted after ingestion.
* Full Refresh is a refresh mode that deletes all existing records in Data Cloud and replaces them with the records from the source file. This is not suitable for this scenario, as it would result in data loss and inconsistency, especially if the source file only contains the summary of the last 24 hours of transactions. References: Ingest Data from Amazon S3, Refresh Modes
NEW QUESTION # 82
A financial services firm specializing in wealth management contacts a Data Cloud consultant with an identity resolution request. The company wants to enhance its strategy to better manage individual client profiles within family portfolios.
Family members often share addresses and sometimes phone numbers but have distinct investment preferences and financial goals. The firm aims to avoid blending individual family profiles into a single entity to maintain personalized service and accurate financial advice.
Which identity resolution strategy should the consultant put in place?
Answer: D
Explanation:
To manage individual client profiles within family portfolios while avoiding blending profiles, the consultant should recommend a more restrictive design approach for identity resolution. Here's why:
Understanding the Requirement
The financial services firm wants to maintain distinct profiles for individual family members despite shared contact points (e.g., address, phone number).
The goal is to avoid blending profiles to ensure personalized service and accurate financial advice.
Why a Restrictive Design Approach?
Avoiding Over-Matching :
A restrictive design approach ensures that match rules are narrowly defined to prevent over-matching (e.g., merging profiles based solely on shared addresses or phone numbers).
This preserves the uniqueness of individual profiles while still allowing for some shared attributes.
Custom Match Rules :
The consultant can configure custom match rules that prioritize unique identifiers (e.g., email, social security number) over shared contact points.
This ensures that family members with shared addresses or phone numbers remain distinct.
Other Options Are Less Suitable :
A . Configure a single match rule with a single connected contact point based on address : This would likely result in over-matching and blending profiles, which is undesirable.
B . Use multiple contact points without individual attributes in the match rules : This approach lacks the precision needed to maintain distinct profiles.
D . Configure a single match rule based on a custom identifier : While custom identifiers are useful, relying on a single rule may not account for all scenarios and could lead to over-matching.
Steps to Implement the Solution
Step 1: Analyze Shared Attributes
Identify shared attributes (e.g., address, phone number) and unique attributes (e.g., email, social security number).
Step 2: Define Restrictive Match Rules
Configure match rules that prioritize unique attributes and minimize reliance on shared contact points.
Step 3: Test Identity Resolution
Test the match rules to ensure that individual profiles are preserved while still allowing for some shared attributes.
Step 4: Monitor and Refine
Continuously monitor the results and refine the match rules as needed to achieve the desired outcome.
Conclusion
A more restrictive design approach ensures that match rules perform as desired, preserving the uniqueness of individual profiles while accommodating shared attributes within family portfolios.
NEW QUESTION # 83
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