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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Ingestion and Modeling | 20% | - Data modeling best practices aligned with identity resolution - Validation and inspection of ingested data - Ingestion from various source systems - Transformation and data mapping capabilities |
| Topic 2: Act on Data | 18% | - Data actions and requirements - Activation concepts and use cases - Troubleshooting activation issues - Attributes, related attributes, and timing dependencies |
| Topic 3: Identity Resolution | 14% | - Reconciliation rules and data unification - Unified identity outcomes and use cases - Matching rules and application |
| Topic 4: Segmentation and Insights | 18% | - Segment creation, maintenance, and membership analysis - Calculated vs. streaming insights - Segmentation concepts and business scenarios |
| Topic 5: Data Cloud Setup and Administration | 12% | - Administration tools: reports, dashboards, flows, packaging - Data streams, data bundles, and data spaces - Data exploration and diagnostics: Explorer tools, APIs - Permissions, permission sets, and org settings |
| Topic 6: Data Cloud Overview | 18% | - Common enterprise use cases - Data ethics and responsible usage principles - Architecture, dependencies, and lifecycle - Core functions, terminology, and business value |
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NEW QUESTION # 12
A retailer wants to unify profiles using Loyalty ID which is different than the unique ID of their customers.
Which object should the consultant use in identity resolution to perform exact match rules on the Loyalty ID?
Answer: A
Explanation:
The Party Identification object is the correct object to use in identity resolution to perform exact match rules on the Loyalty ID. The Party Identification object is a child object of the Individual object that stores different types of identifiers for an individual, such as email, phone, loyalty ID, social media handle, etc. Each identifier has a type, a value, and a source. The consultant can use the Party Identification object to create a match rule that compares the Loyalty ID type and value across different sources and links the corresponding individuals.
The other options are not correct objects to use in identity resolution to perform exact match rules on the Loyalty ID. The Loyalty Identification object does not exist in Data Cloud. The Individual object is the parent object that represents a unified profile of an individual, but it does not store the Loyalty ID directly. The Contact Identification object is a child object of the Contact object that stores identifiers for a contact, such as email, phone, etc., but it does not store the Loyalty ID.
Data Modeling Requirements for Identity Resolution
Identity Resolution in a Data Space
Configure Identity Resolution Rulesets
Map Required Objects
Data and Identity in Data Cloud
NEW QUESTION # 13
A consultant is ingesting a list of employees from their human resources database that they want to segment on.
Which data stream category should the consultant choose when ingesting this data?
Answer: D
Explanation:
Categories of Data Streams:
Profile Data: Customer profiles and demographic information.
Contact Data: Contact points like email and phone numbers.
Other Data: Miscellaneous data that doesn't fit into the other categories.
Engagement Data: Interactions and behavioral data.
Reference: Salesforce Data Stream Categories
Ingesting Employee Data:
Employee data typically doesn't fit into profile, contact, or engagement categories meant for customer data.
"Other Data" is appropriate for non-customer-specific data like employee information.
Reference: Salesforce Data Ingestion Guide
Steps to Ingest Employee Data:
Navigate to the data ingestion settings in Salesforce Data Cloud.
Select "Create New Data Stream" and choose the "Other Data" category.
Map the fields from the HR database to the corresponding fields in Data Cloud.
Reference: Salesforce Data Ingestion Tutorial
Practical Application:
Example: A company ingests employee data to segment internal communications or analyze workforce metrics.
Choosing the "Other Data" category ensures that this non-customer data is correctly managed and utilized.
Reference: Salesforce Data Management Case Studies
NEW QUESTION # 14
Northern Trail Outfitters (NTO) wants to send a promotional campaign for customers that have purchased within the past 6 months. The consultant created a segment to meet this requirement.
Now, NTO brings an additional requirement to suppress customers who have made purchases within the last week.
What should the consultant use to remove the recent customers?
Answer: A
Explanation:
The consultant should use B. Segmentation exclude rules to remove the recent customers. Segmentation exclude rules are filters that can be applied to a segment to exclude records that meet certain criteria. The consultant can use segmentation exclude rules to exclude customers who have made purchases within the last week from the segment that contains customers who have purchased within the past 6 months. This way, the segment will only include customers who are eligible for the promotional campaign.
The other options are not correct. Option A is incorrect because batch transforms are data processing tasks that can be applied to data streams or data lake objects to modify or enrich the data. Batch transforms are not used for segmentation or activation. Option C is incorrect because related attributes are attributes that are derived from the relationships between data model objects. Related attributes are not used for excluding records from a segment. Option D is incorrect because streaming insights are derived attributes that are calculated at the time of data ingestion. Streaming insights are not used for excluding records from a segment. References: Salesforce Data Cloud Consultant Exam Guide, Segmentation, Segmentation Exclude Rules
NEW QUESTION # 15
An organization wants to enable users with the ability to identify and select text attributes from a picklist of options.
Which Data Cloud feature should help with this use case?
Answer: B
Explanation:
Value suggestion is a Data Cloud feature that allows users to see and select the possible values for a text field when creating segment filters. Value suggestion can be enabled or disabled for each data model object (DMO) field in the DMO record home. Value suggestion can help users to identify and select text attributes from a picklist of options, without having to type or remember the exact values. Value suggestion can also reduce errors and improve data quality by ensuring consistent and valid values for the segment filters. References: Use Value Suggestions in Segmentation, Considerations for Selecting Related Attributes
NEW QUESTION # 16
A new user of Data Cloud only needs to be able to review individual rows of ingested data and validate that it has been modeled successfully to its linked data model object. The user will also need to make changes if required.
What is the minimum permission set needed to accommodate this use case?
Answer: B
Explanation:
The Data Cloud User permission set is the minimum permission set needed to accommodate this use case.
The Data Cloud User permission set grants access to the Data Explorer feature, which allows the user to review individual rows of ingested data and validate that it has been modeled successfully to its linked data model object. The user can also make changes to the data model object fields, such as adding or removing fields, changing field types, or creating formula fields. The Data Cloud User permission set does not grant access to other Data Cloud features or tasks, such as creating data streams, creating segments, creating activations, or managing users. The other permission sets are either too restrictive or too permissive for this use case. The Data Cloud for Marketing Specialist permission set only grants access to the segmentation and activation features, but not to the Data Explorer feature. The Data Cloud Admin permission set grants access to all Data Cloud features and tasks, including the Data Explorer feature, but it is more than what the user needs. The Data Cloud for Marketing Data Aware Specialist permission set grants access to the Data Explorer feature, but also to the segmentation and activation features, which are not required for this use case. References: Data Cloud Standard Permission Sets, Data Explorer, Set Up Data Cloud Unit
NEW QUESTION # 17
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