THE BEST DATA-CLOUD-CONSULTANT REAL TEST DUMPS: SALESFORCE CERTIFIED DATA CLOUD CONSULTANT ARE SUITABLE FOR YOU - PASSEXAMDUMPS

The best Data-Cloud-Consultant Real Test Dumps: Salesforce Certified Data Cloud Consultant are suitable for you - PassExamDumps

The best Data-Cloud-Consultant Real Test Dumps: Salesforce Certified Data Cloud Consultant are suitable for you - PassExamDumps

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Salesforce Data-Cloud-Consultant Exam Syllabus Topics:

TopicDetails
Topic 1
  • Data Ingestion and Modeling: This topic covers the different transformation capabilities within Data Cloud. It includes describing processes and considerations for data ingestion from various sources, defining, mapping, and modeling data using best practices aligned with identity resolution. Lastly, it discusses using available tools to inspect and validate ingested and modeled data.
Topic 2
  • Data Cloud Overview: This topic covers Data Cloud's function, key terminology, business value, typical use cases, the Data Cloud lifecycle, dependencies, and principles of data ethics. These sub-topics provide an overview of Data Cloud's capabilities and applications.
Topic 3
  • Segmentation and Insights: This topic defines basic concepts of segmentation and use cases, identifies scenarios for analyzing segment membership, configuring, refining, and maintaining segments within Data Cloud, and differentiating between calculated and streaming insights.
Topic 4
  • Data Cloud Setup and Administration: This topic includes applying Data Cloud permissions, permission sets, org-wide settings. It describes and configures data stream types, and data bundles. Moreover, it discusses use cases for data spaces, creating data spaces, managing and administering Data Cloud using reports, dashboards, flows, packaging, data kits, diagnosing and exploring data using Data Explorer, Profile Explorer, and APIs.
Topic 5
  • Identity Resolution: It describes matching and how its rule sets are applied. Furthermore, it discusses reconciling data and its rule sets, the results of identity resolution, and use cases.

Salesforce Certified Data Cloud Consultant Sample Questions (Q106-Q111):

NEW QUESTION # 106
A consultant wants to build a new audience in Data Cloud.
Which three criteria can the consultant include when building a segment?
Choose 3 answers

  • A. Related attributes
  • B. Data stream attributes
  • C. Calculated Insights
  • D. Direct attributes
  • E. Streaming insights

Answer: A,C,D

Explanation:
Explanation
A segment is a subset of individuals who meet certain criteria based on their attributes and behaviors. A consultant can use different types of criteria when building a segment in Data Cloud, such as:
* Direct attributes: These are attributes that describe the characteristics of an individual, such as name, email, gender, age, etc. These attributes are stored in the Profile data model object (DMO) and can be used to filter individuals based on their profile data.
* Calculated Insights: These are insights that perform calculations on data in a data space and store the results in a data extension. These insights can be used to segment individuals based on metrics or scores derived from their data, such as customer lifetime value, churn risk, loyalty tier, etc.
* Related attributes: These are attributes that describe the relationships of an individual with other DMOs,
* such as Email, Engagement, Order, Product, etc. These attributes can be used to segment individuals based on their interactions or transactions with different entities, such as email opens, clicks, purchases, etc.
The other two options are not valid criteria for building a segment in Data Cloud. Data stream attributes are attributes that describe the streaming data that is ingested into Data Cloud from various sources, such as Marketing Cloud, Commerce Cloud, Service Cloud, etc. These attributes are not directly available for segmentation, but they can be transformed and stored in data extensions using streaming data transforms.
Streaming insights are insights that analyze streaming data in real time and trigger actions based on predefined conditions. These insights are not used for segmentation, but for activation and personalization. References: Create a Segment in Data Cloud, Use Insights in Data Cloud, Data Cloud Data Model


NEW QUESTION # 107
A customer notices that their consolidation rate is low across their account unification. They have mapped Account to the Individual and Contact Point Email DMOs.
What should they do to increase their consolidation rate?

  • A. Increase the number of matching rules.
  • B. Update their account address details in the data source
  • C. Disable the individual identity ruleset.
  • D. Change reconciliation rules to Most Occurring.

Answer: A

Explanation:
Consolidation Rate: The consolidation rate in Salesforce Data Cloud refers to the effectiveness of unifying records into a single profile. A low consolidation rate indicates that many records are not being successfully unified.
Matching Rules: Matching rules are critical in the identity resolution process. They define the criteria for identifying and merging duplicate records.
Solution:
* Increase Matching Rules: Adding more matching rules improves the system's ability to identify duplicate records. This includes matching on additional fields or using more sophisticated matching algorithms.
* Steps:
* Access the Identity Resolution settings in Data Cloud.
* Review the current matching rules.
* Add new rules that consider more fields such as phone number, address, or other unique identifiers.
Benefits:
* Improved Unification: Higher accuracy in matching and merging records, leading to a higher consolidation rate.
* Comprehensive Profiles: Enhanced customer profiles with consolidated data from multiple sources.
References:
* Salesforce Data Cloud Identity Resolution
* Salesforce Help: Matching Rules


NEW QUESTION # 108
Which information is provided in a .csv file when activating to Amazon S3?

  • A. The manifest of origin sources within Data Cloud
  • B. The activated data payload
  • C. The metadata regarding the segment definition
  • D. An audit log showing the user who activated the segment and when it was activated

Answer: B

Explanation:
When activating to Amazon S3, the information that is provided in a .csv file is the activated data payload. The activated data payload is the data that is sent from Data Cloud to the activation target, which in this case is an Amazon S3 bucket1. The activated data payload contains the attributes and values of the individuals or entities that are included in the segment that is being activated2. The activated data payload can be used for various purposes, such as marketing, sales, service, or analytics3. The other options are incorrect because they are not provided in a .csv file when activating to Amazon S3. Option A is incorrect because an audit log is not provided in a .csv file, but it can be viewed in the Data Cloud UI under the Activation History tab4. Option C is incorrect because the metadata regarding the segment definition is not provided in a .csv file, but it can be viewed in the Data Cloud UI under the Segmentation tab5. Option D is incorrect because the manifest of origin sources within Data Cloud is not provided in a .csv file, but it can be viewed in the Data Cloud UI under the Data Sources tab. References: Data Activation Overview, Create and Activate Segments in Data Cloud, Data Activation Use Cases, View Activation History, Segmentation Overview, [Data Sources Overview]


NEW QUESTION # 109
Cloud Kicks wants to be able to build a segment of customers who have visited its website within the previous
7 days.
Which filter operator on the Engagement Date field fits this use case?

  • A. Next Number of Days
  • B. Last Number of Days
  • C. Greater than Last Number of
  • D. Is Between

Answer: B

Explanation:
Explanation
The filter operator Last Number of Days allows you to filter on date fields using a relative date range that specifies the number of days before today. For example, you can use this operator to filter on customers who have visited your website in the last 7 days, or the last 30 days, or any number of days you want. This operator is useful for creating dynamic segments that update automatically based on the current date12. References:
* Relative Date Filter Reference
* Create Filtered Segments


NEW QUESTION # 110
Cloud Kicks received a Request to be Forgotten by a customer.
In which two ways should a consultant use Data Cloud to honor this request?
Choose 2 answers

  • A. Delete the data from the incoming data stream and perform a full refresh.
  • B. Use Data Explorer to locate and manually remove the Individual.
  • C. Use the Consent API to suppress processing and delete the Individual and related records from source data streams.
  • D. Add the Individual ID to a headerless file and use the delete from file functionality.

Answer: C,D

Explanation:
To honor a Request to be Forgotten by a customer, a consultant should use Data Cloud in two ways:
* Add the Individual ID to a headerless file and use the delete from file functionality. This option allows the consultant to delete multiple Individuals from Data Cloud by uploading a CSV file with their IDs1. The deletion process is asynchronous and can take up to 24 hours to complete1.
* Use the Consent API to suppress processing and delete the Individual and related records from source data streams. This option allows the consultant to submit a Data Deletion request for an Individual profile in Data Cloud using the Consent API2. A Data Deletion request deletes the specified Individual entity and any entities where a relationship has been defined between that entity's identifying attribute and the Individual ID attribute2. The deletion process is reprocessed at 30, 60, and 90 days to ensure a full deletion2. The other options are not correct because:
* Deleting the data from the incoming data stream and performing a full refresh will not delete the existing data in Data Cloud, only the new data from the source system3.
* Using Data Explorer to locate and manually remove the Individual will not delete the related records from the source data streams, only the Individual entity in Data Cloud. References:
* Delete Individuals from Data Cloud
* Requesting Data Deletion or Right to Be Forgotten
* Data Refresh for Data Cloud
* [Data Explorer]


NEW QUESTION # 111
......

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