2025 NEWEST SALESFORCE DATA-CLOUD-CONSULTANT: VALID DUMPS SALESFORCE CERTIFIED DATA CLOUD CONSULTANT EBOOK

2025 Newest Salesforce Data-Cloud-Consultant: Valid Dumps Salesforce Certified Data Cloud Consultant Ebook

2025 Newest Salesforce Data-Cloud-Consultant: Valid Dumps Salesforce Certified Data Cloud Consultant Ebook

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Salesforce Data-Cloud-Consultant Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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 professionals are often more sought after than their non-certified counterparts and are more likely to earn higher salaries and promotions. Moreover, cracking the Salesforce Certified Data Cloud Consultant (Data-Cloud-Consultant) exam helps to ensure that you stay up to date with the latest trends and developments in the industry, making you more valuable assets to your organization.

Salesforce Certified Data Cloud Consultant Sample Questions (Q26-Q31):

NEW QUESTION # 26
A consultant wants to ensure that every segment managed by multiple brand teams adheres to the same set of exclusion criteria, that are updated on a monthly basis.
What is the most efficient option to allow for this capability?

  • A. Create, publish, and deploy a data kit.
  • B. Create a nested segment.
  • C. Create a segment and copy it for each brand.
  • D. Create a reusable container block with common criteria.

Answer: D

Explanation:
The most efficient option to allow for this capability is to create a reusable container block with common criteria. A container block is a segment component that can be reused across multiple segments. A container block can contain any combination of filters, nested segments, and exclusion criteria. A consultant can create a container block with the exclusion criteria that apply to all the segments managed by multiple brand teams, and then add the container block to each segment. This way, the consultant can update the exclusion criteria in one place and have them reflected in all the segments that use the container block.
The other options are not the most efficient options to allow for this capability. Creating, publishing, and deploying a data kit is a way to share data and segments across different data spaces, but it does not allow for updating the exclusion criteria on a monthly basis. Creating a nested segment is a way to combine segments using logical operators, but it does not allow for excluding individuals based on specific criteria. Creating a segment and copying it for each brand is a way to create multiple segments with the same exclusion criteria, but it does not allow for updating the exclusion criteria in one place.
References:
* Create a Container Block
* Create a Segment in Data Cloud
* Create and Publish a Data Kit
* Create a Nested Segment


NEW QUESTION # 27
A consultant wants to ensure that every segment managed by multiple brand teams adheres to the same set of exclusion criteria, that are updated on a monthly basis.
What is the most efficient option to allow for this capability?

  • A. Create, publish, and deploy a data kit.
  • B. Create a nested segment.
  • C. Create a segment and copy it for each brand.
  • D. Create a reusable container block with common criteria.

Answer: D

Explanation:
The most efficient option to allow for this capability is to create a reusable container block with common criteria. A container block is a segment component that can be reused across multiple segments. A container block can contain any combination of filters, nested segments, and exclusion criteria. A consultant can create a container block with the exclusion criteria that apply to all the segments managed by multiple brand teams, and then add the container block to each segment. This way, the consultant can update the exclusion criteria in one place and have them reflected in all the segments that use the container block.
The other options are not the most efficient options to allow for this capability. Creating, publishing, and deploying a data kit is a way to share data and segments across different data spaces, but it does not allow for updating the exclusion criteria on a monthly basis. Creating a nested segment is a way to combine segments using logical operators, but it does not allow for excluding individuals based on specific criteria. Creating a segment and copying it for each brand is a way to create multiple segments with the same exclusion criteria, but it does not allow for updating the exclusion criteria in one place.
Reference:
Create a Container Block
Create a Segment in Data Cloud
Create and Publish a Data Kit
Create a Nested Segment


NEW QUESTION # 28
A user Is not seeing suggested values from newly-modeled data when building a segment.
What is causing this issue?

  • A. Value suggestion will only return results for the first 50 values of a specific attribute,
  • B. Value suggestion requires Data Aware Specialist permissions at a minimum.
  • C. Value suggestion is still processing and takes up to 24 hours to be available.
  • D. Value suggestion can only work on direct attributes and not related attributes.

Answer: C

Explanation:
The most likely cause of this issue is that value suggestion is still processing and takes up to 24 hours to be available. Value suggestion is a feature that enables you to see suggested values for data model object (DMO) fields when creating segment filters. However, this feature needs to be enabled for each DMO field, and it can take up to 24 hours for the suggested values to appear after enabling the feature1. Therefore, if a user is not seeing suggested values from newly-modeled data, it could be that the data has not been processed yet by the value suggestion feature. Reference:
Use Value Suggestions in Segmentation


NEW QUESTION # 29
Northern Trail Outfitters uploads new customer data to an Amazon S3 Bucket on a daily basis to be ingested in Data Cloud.
In what order should each process be run to ensure that freshly imported data is ready and available to use for any segment?

  • A. Calculated Insight > Refresh Data Stream > Identity Resolution
  • B. Refresh Data Stream > Identity Resolution > Calculated Insight
  • C. Identity Resolution > Refresh Data Stream > Calculated Insight
  • D. Refresh Data Stream > Calculated Insight > Identity Resolution

Answer: B

Explanation:
To ensure that freshly imported data from an Amazon S3 Bucket is ready and available to use for any segment, the following processes should be run in this order:
* Refresh Data Stream: This process updates the data lake objects in Data Cloud with the latest data from the source system. It can be configured to run automatically or manually, depending on the data stream
* settings1. Refreshing the data stream ensures that Data Cloud has the most recent and accurate data from the Amazon S3 Bucket.
* Identity Resolution: This process creates unified individual profiles by matching and consolidating source profiles from different data streams based on the identity resolution ruleset. It runs daily by default, but can be triggered manually as well2. Identity resolution ensures that Data Cloud has a single view of each customer across different data sources.
* Calculated Insight: This process performs calculations on data lake objects or CRM data and returns a result as a new data object. It can be used to create metrics or measures for segmentation or analysis purposes3. Calculated insights ensure that Data Cloud has the derived data that can be used for personalization or activation.
References:
* 1: Configure Data Stream Refresh and Frequency - Salesforce
* 2: Identity Resolution Ruleset Processing Results - Salesforce
* 3: Calculated Insights - Salesforce


NEW QUESTION # 30
A consultant is ingesting a list of employees from their human resources database that they want to segment on.
Which data stream category should the consultant choose when ingesting this data?

  • A. Other Data
  • B. Profile Data
  • C. Engagement Data
  • D. Contact Data

Answer: A

Explanation:
Categories of Data Streams:
* Profile Data: Customer profiles and demographic information.
* Contact Data: Contact points like email and phone numbers.
* Other Data: Miscellaneous data that doesn't fit into the other categories.
* Engagement Data: Interactions and behavioral data.


NEW QUESTION # 31
......

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