CERTIFICATION DATA-CLOUD-CONSULTANT QUESTIONS - NEW DATA-CLOUD-CONSULTANT BRAINDUMPS

Certification Data-Cloud-Consultant Questions - New Data-Cloud-Consultant Braindumps

Certification Data-Cloud-Consultant Questions - New Data-Cloud-Consultant Braindumps

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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 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
  • 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 4
  • 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 5
  • 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 (Q84-Q89):

NEW QUESTION # 84
Cumulus Financial is experiencing delays in publishing multiple segments simultaneously. The company wants to avoid reducing the frequency at which segments are published, while retaining the same segments in place today.
Which action should a consultant take to alleviate this issue?

  • A. Adjust the publish schedule start time of each segment to prevent overlapping processes.
  • B. Enable rapid segment publishing to all to segment to reduce generation time.
  • C. Reduce the number of segments being published.
  • D. Increase the Data Cloud segmentation concurrency limit.

Answer: A


NEW QUESTION # 85
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 spaces for each brand
  • C. Data model objects for each brand
  • D. Data sources for each brand

Answer: B

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 define the 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. Reference: 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 # 86
Cumulus Financial uses Data Cloud to segment banking customers and activate them for direct mail via a Cloud File Storage activation. The company also wants to analyze individuals who have been in the segment within the last 2 years.
Which Data Cloud component allows for this?

  • A. Nested segments
  • B. Segment exclusion
  • C. Segment membership data model object
  • D. Calculated insights

Answer: C

Explanation:
Explanation
Data Cloud allows customers to analyze the segment membership history of individuals using the Segment Membership data model object. This object storesinformation about when an individual joined or left a segment, and can be used to create reports and dashboards to track segment performance over time. Cumulus Financial can use this object to filter individuals who have been in the segment within the last 2 years and compare them with other metrics.
The other options are not Data Cloud components that allow for this analysis. Segment exclusion is a feature that allows customers to remove individuals from a segment based on another segment. Nested segments are segments that are created from other segments using logical operators. Calculated insights are derived attributes that are created from existing data using formulas.
References:
* Segment Membership Data Model Object
* Data Cloud Reports and Dashboards
* Create a Segment in Data Cloud


NEW QUESTION # 87
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 a segment and copy it for each brand.
  • B. Create a nested segment.
  • C. Create, publish, and deploy a data kit.
  • 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 # 88
A company stores customer data in Marketing Cloud and uses the Marketing Cloud Connector to ingest data into Data Cloud.
Where does a request for data deletion or right to be forgotten get submitted?

  • A. On the individual data profile in Data Cloud
  • B. In Marketing Cloud settings
  • C. through Consent API
  • D. In Data Cloud settings

Answer: B

Explanation:
* Data Deletion Requests: For companies using Salesforce Marketing Cloud and Data Cloud, managing data privacy and deletion requests is essential.
* Marketing Cloud Connector: This connector facilitates data integration between Marketing Cloud and Data Cloud, but data deletion requests must follow specific procedures.
* Deletion Requests in Marketing Cloud:
Data Management: Requests for data deletion or the right to be forgotten are submitted through Marketing Cloud settings, where the customer data is originally stored and managed.
Propagation: Once the request is processed in Marketing Cloud, the changes are propagated to Data Cloud through the connector.
* Reference:
Salesforce Marketing Cloud Documentation: Data Management
Salesforce Data Cloud Connector Guide


NEW QUESTION # 89
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