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[General] Salesforce-Data-Cloud Study Material | Exam Salesforce-Data-Cloud Simulator Onli

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【General】 Salesforce-Data-Cloud Study Material | Exam Salesforce-Data-Cloud Simulator Onli

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Salesforce Data Cloud Accredited Professional Exam Sample Questions (Q49-Q54):NEW QUESTION # 49
A Data Cloud consultant recently discovered that their identity resolution process is matching individuals that share email addresses or phone numbers, but are not actually the same individual.
What should the consultant do to address this issue?
  • A. Modify the existing ruleset with stricter matching criteria, run the ruleset and review the updated results, then adjust as needed until the individuals are matching correctly.
  • B. Modify the existing ruleset with stricter matching criteria, compare the two rulesets to review and verify the results, and then migrate to the new ruleset once approved.
  • C. Create and run a new ruleset with stricter matching criteria, compare the two rulesets to review and verify the results, and then migrate to the new ruleset once approved.
  • D. Create and run a new rules fewer matching rules, compare the two rulesets to review and verify the results, and then migrate to the new ruleset once approved.
Answer: C
Explanation:
Identity resolution is the process of linking source profiles from different data sources into unified individual profiles based on match and reconciliation rules. If the identity resolution process is matching individuals that share email addresses or phone numbers, but are not actually the same individual, it means that the match rules are too loose and need to be refined. The best way to address this issue is to create and run a new ruleset with stricter matching criteria, such as adding more attributes or increasing the match score threshold. Then, the consultant can compare the two rulesets to review and verify the results, and see if the new ruleset reduces the false positives and improves the accuracy of the identity resolution. Once the new ruleset is approved, the consultant can migrate to the new ruleset and delete the old one. The other options are incorrect because modifying the existing ruleset can affect the existing unified profiles and cause data loss or inconsistency.
Creating and running a new ruleset with fewer matching rules can increase the false negatives and reduce the coverage of the identity resolution. References: Create Unified Individual Profiles, AI-based Identity Resolution: Linking Diverse Customer Data, Data Cloud Identiy Resolution.

NEW QUESTION # 50
What component of Calculated Insights can be included as attribute data in an activation?
  • A. Dimensions
  • B. Metrics
  • C. Metrics and Dimensions
  • D. Filters
Answer: A
Explanation:
Dimensions are attributes that can be used to group or filter data in calculated insights. You can include dimensions as attribute data in an activation by selecting them from the available attributes list. References:
https://help.salesforce.com/s/ar ... ghts.htm&type=5

NEW QUESTION # 51
When creating a segment on an individual, what is the result of using two separate containers linked by an AND: At Least 1 of GoodsProduct.Color Is Equal To 'red' AND At Least 1 of GoodsProduct.
PrimaryProductCategory Is Equal To shoes'?
  • A. Individuals who purchased at least 1 'red shoes' as a single line item in a purchase
  • B. Individuals who made a purchase of at least 1 of only 'red shoes' and nothing else
  • C. Individuals who purchased at least 1 of any red' product and also purchased at least 1 pair of shoes'
  • D. Individuals whopurchased at least 1 'red shoes'. 1 of any red' item, or 1 of any 'shoes' item in a purchase
Answer: C
Explanation:
According to the Data Cloud documentation, when using two separatecontainers linked by an AND operator, the segment includes individuals who meet both conditions. In this case, the segment includes individuals who purchased at least one product with the color attribute equal to 'red', and also purchased at least one product with the primary product category attribute equal to 'shoes'. The products do not have to be the same or in the same order line item.

NEW QUESTION # 52
Which two dependencies prevent a data stream from being deleted?
Choose 2 answers
  • A. The underlying data lake object is used in activation.
  • B. The underlying data lake object is mapped to a data model object.
  • C. The underlying data lake object is used in a data transform.
  • D. The underlying data lake object is used in segmentation.
Answer: B,C
Explanation:
To delete a data stream in Data Cloud, the underlying data lake object (DLO) must not have any dependencies or references to other objects or processes. The following two dependencies prevent a data stream from being deleted1:
Data transform: This is a process that transforms the ingested data into a standardized format and structure for the data model. A data transform can use one or more DLOs as input or output. If a DLO is used in a data transform, it cannot be deleted until the data transform is removed or modified2.
Data model object: This is an object that represents a type of entity or relationship in the data model. A data model object can be mapped to one or more DLOs to define its attributes and values. If a DLO is mapped to a data model object, it cannot be deleted until the mapping is removed or changed3.
1: Delete a Data Stream article on Salesforce Help
2: [Data Transforms in Data Cloud] unit on Trailhead
3: [Data Model in Data Cloud] unit on Trailhead

NEW QUESTION # 53
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?
  • A. Individual object
  • B. Loyalty Identification object
  • C. Contact Identification object
  • D. Party Identification object
Answer: D
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 # 54
......
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