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Pass Guaranteed 2025 Salesforce Data-Cloud-Consultant: Salesforce Certified Data Cloud Consultant–Updated Exam Assessment

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Salesforce Data-Cloud-Consultant Exam Syllabus Topics:

Topic
Details

Topic 1

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 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

Act on Data: This topic defines activations and their basic use cases, using attributes and related attributes, identifying and analyzing timing dependencies affecting the Data Cloud lifecycle. Additionally it focuses on troubleshooting common problems with activations, and using data actions, including their requirements and intended use cases.

Topic 5

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.

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To increase your chances of success, consider utilizing the Data-Cloud-Consultant Exam Questions, which are valid, updated, and reflective of the actual Data-Cloud-Consultant Exam. Don't miss the opportunity to strengthen your Salesforce Data-Cloud-Consultant exam preparation with these valuable questions.

Salesforce Certified Data Cloud Consultant Sample Questions (Q36-Q41):

NEW QUESTION # 36
Which consideration related to the way Data Cloud ingests CRM data is true?

A. Formula fields are refreshed at regular sync intervals and are updated at the next full refresh.
B. The CRM Connector's synchronization times can be customized to up to 15-minute intervals.
C. CRM data cannot be manually refreshed and must wait for the next scheduled synchronization,
D. The CRM Connector allows standard fields to stream into Data Cloud in real time.

Answer: D

Explanation:
The correct answer is D. The CRM Connector allows standard fields to stream into Data Cloud in real time.
This means that any changes to the standard fields in the CRM data source are reflected in Data Cloud almost instantly, without waiting for the next scheduled synchronization. This feature enables Data Cloud to have the most up-to-date and accurate CRM data for segmentation and activation1.
The other options are incorrect for the following reasons:
* A. CRM data can be manually refreshed at any time by clicking the Refresh button on the data stream detail page2. This option is false.
* B. The CRM Connector's synchronization times can be customized to up to 60-minute intervals, not
15-minute intervals3. This option is false.
* C. Formula fields are not refreshed at regular sync intervals, but only at the next full refresh4. A full refresh is a complete data ingestion process that occurs once every 24 hours or when manually triggered.
This option is false.
References:
* 1: Connect and Ingest Data in Data Cloud article on Salesforce Help
* 2: Data Sources in Data Cloud unit on Trailhead
* 3: Data Cloud for Admins module on Trailhead
* 4: [Formula Fields in Data Cloud] unit on Trailhead
* : [Data Streams in Data Cloud] unit on Trailhead

NEW QUESTION # 37
The marketing manager at Cloud Kicks plans to bring in corporate phone numbers for its accounts into Data Cloud. They plan to use a custom field with data set to Phone to store these phone numbers.
Which statement is true when ingesting phone numbers?

A. The phone number field car only accept 10-digit values.
B. The phone number field should be used as a primary key.
C. Text value can be accepted for ingestion into = phone data type field.
D. Data Cloud validates the format of the phone number at the time of Ingestion.

Answer: C

NEW QUESTION # 38
A customer wants to create segments of users based on their Customer Lifetime Value.
However, the source data that will be brought into Data Cloud does not include that key performance indicator (KPI).
Which sequence of steps should the consultant follow to achieve this requirement?

A. Ingest Data > Map Data to Data Model > Create Calculated Insight > Use in Segmentation
B. Create Calculated Insight > Ingest Data > Map Data to Data Model> Use in Segmentation
C. Ingest Data > Create Calculated Insight > Map Data to Data Model > Use in Segmentation
D. Create Calculated Insight > Map Data to Data Model> Ingest Data > Use in Segmentation

Answer: A

Explanation:
To create segments of users based on their Customer Lifetime Value (CLV), the sequence of steps that the consultant should follow is Ingest Data > Map Data to Data Model > Create Calculated Insight > Use in Segmentation. This is because the first step is to ingest the source data into Data Cloud using data streams1. The second step is to map the source data to the data model, which defines the structure and attributes of the data2. The third step is to create a calculated insight, which is a derived attribute that is computed based on the source or unified data3. In this case, the calculated insight would be the CLV, which can be calculated using a formula or a query based on the sales order data4. The fourth step is to use the calculated insight in segmentation, which is the process of creating groups of individuals or entities based on their attributes and behaviors. By using the CLV calculated insight, the consultant can segment the users by their predicted revenue from the lifespan of their relationship with the brand. The other options are incorrect because they do not follow the correct sequence of steps to achieve the requirement. Option B is incorrect because it is not possible to create a calculated insight before ingesting and mapping the data, as the calculated insight depends on the data model objects3. Option C is incorrect because it is not possible to create a calculated insight before mapping the data, as the calculated insight depends on the data model objects3. Option D is incorrect because it is not recommended to create a calculated insight before mapping the data, as the calculated insight may not reflect the correct data model structure and attributes3. References: Data Streams Overview, Data Model Objects Overview, Calculated Insights Overview, Calculating Customer Lifetime Value (CLV) With Salesforce, [Segmentation Overview]

NEW QUESTION # 39
What is a key functionality of Data Cloud?

A. To give a persistent ID for unified profiles
B. To help users build a heat map using their data
C. To build insights on unified profiles
D. To create a master data management (MUM) strategy

Answer: C

Explanation:
A key functionality of Salesforce Data Cloud is its ability to build insights on unified profiles . Here's why this is the correct answer:
Understanding the Functionality of Data Cloud
Salesforce Data Cloud is designed to aggregate, unify, and analyze customer data from multiple sources.
Its primary purpose is to provide actionable insights that drive personalized customer experiences.
Why Build Insights on Unified Profiles?
Unified Profiles :
Data Cloud creates a unified profile by combining data from various sources (e.g., CRM, Marketing Cloud, external systems).
This single view of the customer enables organizations to understand behaviors, preferences, and interactions across touchpoints.
Building Insights :
Insights derived from unified profiles help organizations make data-driven decisions.
Examples include identifying high-value customers, predicting churn, and personalizing marketing campaigns.
Other Options Are Less Relevant :
A . To create a master data management (MDM) strategy : While Data Cloud supports data unification, it is not primarily an MDM tool.
B . To give a persistent ID for unified profiles : Persistent IDs are a feature of unified profiles but not the core functionality of Data Cloud.
D . To help users build a heat map using their data : Heat maps are a visualization tool, not a core functionality of Data Cloud.
Steps to Build Insights on Unified Profiles
Step 1: Ingest Data
Bring in customer data from multiple sources into Data Cloud.
Step 2: Create Unified Profiles
Use identity resolution to merge related records into a single unified profile.
Step 3: Analyze Data
Use tools like calculated insights, segments, and dashboards to derive actionable insights.
Step 4: Activate Insights
Use the insights to personalize customer experiences in downstream systems (e.g., Marketing Cloud, Sales Cloud).
Conclusion
The key functionality of Salesforce Data Cloud is to build insights on unified profiles , enabling organizations to deliver personalized and impactful customer experiences.

NEW QUESTION # 40
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. Last Number of Days
B. Greater than Last Number of
C. Next Number of Days
D. Is Between

Answer: A

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. Reference:
Relative Date Filter Reference
Create Filtered Segments

NEW QUESTION # 41
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