Salesforce Certified Data Cloud Consultant Exam Practice Questions & Data-Cloud-Consultant Free Download Pdf & Salesforce Certified Data Cloud Consultant Valid Training Material

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Salesforce Data-Cloud-Consultant Exam Syllabus Topics:

Topic	Details
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	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.
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	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.

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Salesforce Certified Data Cloud Consultant Sample Questions (Q81-Q86):

NEW QUESTION # 81
The leadership team at Cumulus Financial has determined that customers who deposited more than $250,000 in the last five years and are not using advisory services will be the central focus for all new campaigns in the next year.
Which features support this use case?

A. Streaming insight and data action
B. Calculated insight and segment
C. Streaming insight and segment
D. Calculated insight and data action

Answer: B

Explanation:
* Understanding the Use Case:
The leadership team wants to focus on customers who have deposited more than $250,000 in the last five years and are not using advisory services.
Reference:
* Features Involved:
Calculated Insight: This feature helps derive metrics and values based on existing data. In this case, it can calculate total deposits over the last five years.
Segment: Segmentation allows targeting specific groups of customers based on defined criteria, such as total deposits and usage of advisory services.
* Steps to Implement:
Create a Calculated Insight:
Navigate to Visual Insights Builder in Salesforce Data Cloud.
Create a new calculated insight to sum deposits for each customer over the last five years.
Create a Segment:
Use the Segment Canvas to create a new segment.
Apply filters to include customers with deposits over $250,000 and exclude those using advisory services.
* Practical Application:
Example: Identify high-value customers who are not leveraging additional services and target them with personalized marketing campaigns to promote advisory services.

NEW QUESTION # 82
A consultant is discussing the benefits of Data Cloud with a customer that has multiple disjointed data sources.
Which two functional areas should the consultant highlight in relation to managing customer data?
Choose 2 answers

A. Data Harmonization
B. Unified Profiles
C. Data Marketplace
D. Master Data Management

Answer: A,B

Explanation:
Data Cloud is an open and extensible data platform that enables smarter, more efficient AI with secure access to first-party and industry data1. Two functional areas that the consultant should highlight in relation to managing customer data are:
Data Harmonization: Data Cloud harmonizes data from multiple sources and formats into a common schema, enabling a single source of truth for customer data1. Data Cloud also applies data quality rules and transformations to ensure data accuracy and consistency.
Unified Profiles: Data Cloud creates unified profiles of customers and prospects by linking data across different identifiers, such as email, phone, cookie, and device ID1. Unified profiles provide a holistic view of customer behavior, preferences, and interactions across channels and touchpoints. The other options are not correct because:
Master Data Management: Master Data Management (MDM) is a process of creating and maintaining a single, consistent, and trusted source of master data, such as product, customer, supplier, or location data. Data Cloud does not provide MDM functionality, but it can integrate with MDM solutions to enrich customer data.
Data Marketplace: Data Marketplace is a feature of Data Cloud that allows users to discover, access, and activate data from third-party providers, such as demographic, behavioral, and intent data. Data Marketplace is not a functional area related to managing customer data, but rather a source of external data that can enhance customer data. Reference:
Salesforce Data Cloud
[Data Harmonization for Data Cloud]
[Unified Profiles for Data Cloud]
[What is Master Data Management?]
[Integrate Data Cloud with Master Data Management]
[Data Marketplace for Data Cloud]

NEW QUESTION # 83
How can a consultant modify attribute names to match a naming convention in Cloud File Storage targets?

A. Update field names in the data model object.
B. Update attribute names in the data stream configuration.
C. Set preferred attribute names when configuring activation.
D. Use a formula field to update the field name in an activation.

Answer: C

Explanation:
A Cloud File Storage target is a type of data action target in Data Cloud that allows sending data to a cloud storage service such as Amazon S3 or Google Cloud Storage. When configuring an activation to a Cloud File Storage target, a consultant can modify the attribute names to match a naming convention by setting preferred attribute names in Data Cloud. Preferred attribute names are aliases that can be used to control the field names in the target file. They can be set for each attribute in the activation configuration, and they will override the default field names from the data model object. The other options are incorrect because they do not affect the field names in the target file. Using a formula field to update the field name in an activation will not change the field name, but only the field value. Updating attribute names in the data stream configuration will not affect the existing data lake objects or data model objects. Updating field names in the data model object will change the field names for all data sources and activations that use the object, which may not be desirable or consistent. Reference: Preferred Attribute Name, Create a Data Cloud Activation Target, Cloud File Storage Target

NEW QUESTION # 84
A Data Cloud consultant recently added a new data source and mapped some of the data to a new custom data model object (DMO) that they want to use for creating segments. However, they cannot view the newly created DMO when trying to create a new segment.
What is the cause of this issue?

A. Segmentation is only supported for the Individual and Unified Individual DMOs.
B. The new DMO is not of category Profile.
C. Data has not yes been ingested into the DMO.
D. The new DMO does not have a relationship to the individual DMO

Answer: B

Explanation:
The cause of this issue is that the new custom data model object (DMO) is not of category Profile. A category is a property of a DMO that defines its purpose and functionality in Data Cloud. There are three categories of DMOs: Profile, Event, and Other. Profile DMOs are used to store attributes of individuals or entities, such as name, email, address, etc. Event DMOs are used to store actions or interactions of individuals or entities, such as purchases, clicks, visits, etc. Other DMOs are used to store any other type of data that does not fit into the Profile or Event categories, such as products, locations, categories, etc. Only Profile DMOs can be used for creating segments in Data Cloud, as segments are based on the attributes of individuals or entities. Therefore, if the new custom DMO is not of category Profile, it will not appear in the segmentation canvas. The other options are not correct because they are not the cause of this issue. Data ingestion is not a prerequisite for creating segments, as segments can be created based on the data model schema without actual data. The new DMO does not need to have a relationship to the individual DMO, as segments can be created based on any Profile DMO, regardless of its relationship to other DMOs. Segmentation is not only supported for the Individual and Unified Individual DMOs, as segments can be created based on any Profile DMO, including custom ones. Reference: Create a Custom Data Model Object from an Existing Data Model Object, Create a Segment in Data Cloud, Data Model Object Category

NEW QUESTION # 85
A customer has outlined requirements to trigger a journey for an abandoned browse behavior. Based on the requirements, the consultant determines they will use streaming insights to trigger a data action to Journey Builder every hour.
How should the consultant configure the solution to ensure the data action is triggered at the cadence required?

A. Set the insights aggregation time window to 1 hour.
B. Configure the data to be ingested in hourly batches.
C. Set the journey entry schedule to run every hour.
D. Set the activation schedule to hourly.

Answer: A

Explanation:
Streaming insights are computed from real-time engagement events and can be used to trigger data actions based on pre-set rules. Data actions are workflows that send data from Data Cloud to other systems, such as Journey Builder. To ensure that the data action is triggered every hour, the consultant should set the insights aggregation time window to 1 hour. This means that the streaming insight will evaluate the events that occurred within the last hour and execute the data action if the conditions are met. The other options are not relevant for streaming insights and data actions. References: Streaming Insights and Data Actions Limits and Behaviors, Streaming Insights, Streaming Insights and Data Actions Use Cases, Use Insights in Data Cloud, 6 Ways the Latest Marketing Cloud Release Can Boost Your Campaigns

NEW QUESTION # 86
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Salesforce Certified Data Cloud Consultant Exam Practice Questions & Data-Cloud-Consultant Free Download Pdf & Salesforce Certified Data Cloud Consultant Valid Training Material

Salesforce Data-Cloud-Consultant Exam Syllabus Topics:

Data-Cloud-Consultant Valid Exam Preparation, Reliable Data-Cloud-Consultant Test Tutorial

Salesforce Certified Data Cloud Consultant Sample Questions (Q81-Q86):

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