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[General] 100% Pass Salesforce - Latest Data-Cloud-Consultant Dumps Files

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【General】 100% Pass Salesforce - Latest Data-Cloud-Consultant Dumps Files

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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 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 3
  • 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 4
  • 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.

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Salesforce Certified Data Cloud Consultant Sample Questions (Q123-Q128):NEW QUESTION # 123
Which solution provides an easy way to ingest Marketing Cloud subscriber profile attributes into Data Cloud on a daily basis?
  • A. Automation Studio and Profile file API
  • B. Email Studio Starter Data Bundle
  • C. Marketing Cloud Data extension Data Stream
  • D. Marketing Cloud Connect API
Answer: C
Explanation:
Explanation
The solution that provides an easy way to ingest Marketing Cloud subscriber profile attributes into Data Cloud on a daily basis is the Marketing Cloud Data extension Data Stream. The Marketing Cloud Data extension Data Stream is a feature that allows customers to stream data from Marketing Cloud data extensions to Data Cloud data spaces. Customers can select which data extensions they want to stream, and Data Cloud will automatically create and update the corresponding data model objects (DMOs) in the data space.
Customers can also map the data extension fields to the DMO attributes using a user interface or an API. The Marketing Cloud Data extension Data Stream can help customers ingest subscriber profile attributes and other data from Marketing Cloud into Data Cloud without writing any code or setting up any complex integrations.
The other options are not solutions that provide an easy way to ingest Marketing Cloud subscriber profile attributes into Data Cloud on a daily basis. Automation Studio and Profile file API are tools that can be used to export data from Marketing Cloud to external systems, but they require customers to write scripts, configure file transfers, and schedule automations. Marketing Cloud Connect API is an API that can be used to access data from Marketing Cloud in other Salesforce solutions, such as Sales Cloud or Service Cloud, but it does not support streaming data to Data Cloud. Email Studio Starter Data Bundle is a data kit that contains sample data and segments for Email Studio, but it does not contain subscriber profile attributes or stream data to Data Cloud.
References:
* Marketing Cloud Data Extension Data Stream
* Data Cloud Data Ingestion
* [Marketing Cloud Data Extension Data Stream API]
* [Marketing Cloud Connect API]
* [Email Studio Starter Data Bundle]

NEW QUESTION # 124
The recruiting team at Cumulus Financial wants to identify which candidates have browsed the jobs page on its website at least twice within the last 24 hours. They want the information about these candidates to be available for segmentation in Data Cloud and the candidates added to their recruiting system.
Which feature should a consultant recommend to achieve this goal?
  • A. Streaming data transform
  • B. Calculated insight
  • C. Streaming insight
  • D. Batch bata transform
Answer: C
Explanation:
A streaming insight is a feature that allows users to create and monitor real-time metrics from streaming data sources, such as web and mobile events. A streaming insight can also trigger data actions, such as sending notifications, creating records, or updating fields, based on the metric values and conditions. Therefore, a streaming insight is the best feature to achieve the goal of identifying candidates who have browsed the jobs page on the website at least twice within the last 24 hours, and adding them to the recruiting system. The other options are incorrect because:
* A streaming data transform is a feature that allows users to transform and enrich streaming data using SQL expressions, such as filtering, joining, aggregating, or calculating values. However, a streaming data transform does not provide the ability to monitor metrics or trigger data actions based on conditions.
* A calculated insight is a feature that allows users to define and calculate multidimensional metrics from data using SQL expressions, such as LTV, CSAT, or average order value. However, a calculated insight is not suitable for real-time data analysis, as it runs on a scheduled basis and does not support data
* actions.
* A batch data transform is a feature that allows users to create and schedule complex data transformations using a visual editor, such as joining, aggregating, filtering, or appending data.
However, a batch data transform is not suitable for real-time data analysis, as it runs on a scheduled basis and does not support data actions. References: Streaming Insights, Create a Streaming Insight, Use Insights in Data Cloud, Learn About Data Cloud Insights, Data Cloud Insights Using SQL, Streaming Data Transforms, Get Started with Batch Data Transforms in Data Cloud, Transformations for Batch Data Transforms, Batch Data Transforms in Data Cloud: Quick Look, Salesforce Data Cloud: AI CDP.

NEW QUESTION # 125
Northern Trail Outfitters (NTO), an outdoor lifestyle clothing brand, recently started a new line of business. The new business specializes in gourmet camping food. For business reasons as well as security reasons, it's important to NTO to keep all Data Cloud data separated by brand.
Which capability best supports NTO's desire to separate its data by brand?
  • A. Data streams for each brand
  • B. Data sources for each brand
  • C. Data model objects for each brand
  • D. Data spaces for each brand
Answer: D
Explanation:
Explanation
Data spaces are logical containers that allow you to separate and organize your data by different criteria, such as brand, region, product, or business unit1. Data spaces can help you manage data access, security, and governance, as well as enable cross-cloud data integration and activation2. For NTO, data spaces can support their desire to separate their data by brand, so that they can have different data models, rules, and insights for their outdoor lifestyle clothing and gourmet camping food businesses. Data spaces can also help NTO comply with any data privacy and security regulations that may apply to their different brands3. The other options are incorrect because they do not provide the same level of data separation and organization as data spaces. Data streams are used to ingest data from different sources into Data Cloud, but they do not separate the data by brand4. Data model objects are used to definethe structure and attributes of the data, but they do not isolate the data by brand5. Data sources are used to identify the origin and type of the data, but they do not partition the data by brand. References: Data Spaces Overview, Create Data Spaces, Data Privacy and Security in Data Cloud, Data Streams Overview, Data Model Objects Overview, [Data Sources Overview]

NEW QUESTION # 126
Cumulus Financial created a segment called Multiple Investments that contains individuals who have invested in two or more mutual funds.
The company plans to send an email to this segment regarding a new mutual fund offering, and wants to personalize the email content with information about each customer's current mutual fund investments.
How should the Data Cloud consultant configure this activation?
  • A. Choose the Multiple Investments segment, choose the Email contact point, add related attribute Fund Name, and add related attribute filter for Fund Type equal to "Mutual Fund".
  • B. Include Fund Name and Fund Type by default for post processing in the target system.
  • C. Choose the Multiple Investments segment, choose the Email contact point, and add related attribute Fund Type.
  • D. Include Fund Type equal to "Mutual Fund" as a related attribute. Configure an activation based on the new segment with no additional attributes.
Answer: A
Explanation:
To personalize the email content with information about each customer's current mutual fund investments, the Data Cloud consultant needs to add related attributes to the activation. Related attributes are additional data fields that can be sent along with the segment to the target system for personalization or analysis purposes. In this case, the consultant needs to add the Fund Name attribute, which contains the name of the mutual fund that the customer has invested in, and apply a filter for Fund Type equal to "Mutual Fund" to ensure that only relevant data is sent. The other options are not correct because:
* A. Including Fund Type equal to "Mutual Fund" as a related attribute is not enough to personalize the email content. The consultant also needs to include the Fund Name attribute, which contains the specific name of the mutual fund that the customer has invested in.
* C. Adding related attribute Fund Type is not enough to personalize the email content. The consultant also needs to add the Fund Name attribute, which contains the specific name of the mutual fund that the customer has invested in, and apply a filter for Fund Type equal to "Mutual Fund" to ensure that only relevant data is sent.
* D. Including Fund Name and Fund Type by default for post processing in the target system is not a valid option. The consultant needs to add the related attributes and filters during the activation configuration in Data Cloud, not after the data is sent to the target system. References: Add Related Attributes to an Activation - Salesforce, Related Attributes in Activation - Salesforce, Prepare for Your Salesforce Data Cloud Consultant Credential

NEW QUESTION # 127
A finance company that uses Data Cloud wants to simplify how its users can view all the various channels a customer engages  with Which feature should the consultant recommend to meet this requirement?
  • A. Create segments based on the ingested data and insights to activate in Marketing Cloud.
  • B. Use calculated insights to determine when and how to engage with various customers.
  • C. Use Data Cloud to connect with analytic tools, like Tableau.
  • D. Use Data Cloud to ingest data from various available data sources.
Answer: C
Explanation:
To simplify how users can view all the various channels a customer engages with, the best solution is to use Data Cloud to connect with analytic tools like Tableau . Here's why and how this works:
Understanding the Requirement
The finance company wants its users to have a consolidated view of all customer engagement channels (e.g., email, social media, website interactions, etc.). This requires:
Aggregating data from multiple sources into a unified platform.
Providing an intuitive and visual way to analyze and interpret the data.
Why Use Data Cloud with Analytic Tools like Tableau?
Data Cloud as a Centralized Data Hub :
Salesforce Data Cloud aggregates data from multiple sources (e.g., CRM, Marketing Cloud, external systems) into a unified platform. This ensures that all customer engagement data is available in one place.
Tableau for Advanced Visualization :
Tableau is a powerful analytics and visualization tool that integrates seamlessly with Salesforce Data Cloud.
It allows users to create interactive dashboards and reports that provide a comprehensive view of customer engagement across all channels.
Users can drill down into specific channels, analyze trends, and gain actionable insights without needing advanced technical skills.
Simplified User Experience :
By leveraging Tableau's intuitive interface, users can easily explore and understand customer engagement patterns without requiring deep knowledge of the underlying data structure.
Steps to Implement This Solution
Step 1: Ingest Data into Data Cloud
Ensure that all relevant customer engagement data (e.g., website visits, email interactions, social media activity) is ingested into Data Cloud from various sources.
Use Data Streams to bring in data from CRM, Marketing Cloud, and other external systems.
Step 2: Connect Data Cloud to Tableau
Navigate to Setup > Analytics > Tableau CRM in Salesforce.
Configure the integration between Data Cloud and Tableau to enable seamless data flow.
Step 3: Create Dashboards in Tableau
Use Tableau to build dashboards that consolidate customer engagement data from all channels.
Include visualizations such as bar charts, heatmaps, and trend lines to highlight key insights (e.g., most active channels, engagement frequency, etc.).
Step 4: Share Dashboards with Users
Publish the dashboards to Tableau Server or Tableau Online.
Provide access to the relevant users within the finance company so they can view and interact with the dashboards.
Why Not Other Options?
B: Use calculated insights to determine when and how to engage with various customers :
While calculated insights are useful for understanding customer behavior, they do not provide a consolidated view of all engagement channels. This option focuses more on decision-making rather than visualization.
C: Create segments based on the ingested data and insights to activate in Marketing Cloud :
Segmentation is valuable for targeting specific groups of customers, but it does not address the requirement to view all engagement channels in one place. Segments are more about grouping customers rather than providing a holistic view.
D: Use Data Cloud to ingest data from various available data sources :
While ingesting data is a critical first step, it does not solve the problem of simplifying how users view engagement channels. The focus here is on data ingestion, not visualization or analysis.
Conclusion
By connecting Data Cloud with Tableau , the finance company can provide its users with a simplified and visually intuitive way to view all customer engagement channels. This approach lever

NEW QUESTION # 128
......
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