PASS GUARANTEED QUIZ SALESFORCE - DATA-CLOUD-CONSULTANT - THE BEST VALID SALESFORCE CERTIFIED DATA CLOUD CONSULTANT EXAM VOUCHER

Pass Guaranteed Quiz Salesforce - Data-Cloud-Consultant - The Best Valid Salesforce Certified Data Cloud Consultant Exam Voucher

Pass Guaranteed Quiz Salesforce - Data-Cloud-Consultant - The Best Valid Salesforce Certified Data Cloud Consultant Exam Voucher

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Salesforce Data-Cloud-Consultant Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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 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.

Salesforce Certified Data Cloud Consultant Sample Questions (Q83-Q88):

NEW QUESTION # 83
A Data Cloud consultant tries to save a new 1-to-l relationship between the Account DMO and Contact Point Address DMO but gets an error.
What should the consultant do to fix this error?

  • A. Map additional fields to the Contact Point Address DMO.
  • B. Make sure that the total account records are high enough for Identity resolution.
  • C. Map Account to Contact Point Email and Contact Point Phone also.
  • D. Change the cardinality to many-to-one to accommodate multiple contacts per account.

Answer: D

Explanation:
Relationship Cardinality: In Salesforce Data Cloud, defining the correct relationship cardinality between data model objects (DMOs) is crucial for accurate data representation and integration.
1-to-1 Relationship Error: The error occurs because the relationship between Account DMO and Contact Point Address DMO is set as 1-to-1, which implies that each account can only have one contact point address.
Solution:
* Change Cardinality: Modify the relationship cardinality to many-to-one. This allows multiple contact point addresses to be associated with a single account, reflecting real-world scenarios more accurately.
* Steps:
* Go to the data model configuration in Data Cloud.
* Locate the relationship between Account DMO and Contact Point Address DMO.
* Change the relationship type from 1-to-1 to many-to-one.
Benefits:
* Accurate Representation: Accommodates real-world data scenarios where an account may have multiple contact points.
* Error Resolution: Resolves the error and ensures smooth data integration.
References:
* Salesforce Data Cloud Documentation: Relationships
* Salesforce Help: Data Modeling in Data Cloud


NEW QUESTION # 84
A consultant wants to confirm the Identity resolution they Just set up. Which two features can the consultant use to validate the data on a unified profile?
Choose 2 answers

  • A. Data Explorer
  • B. Identity Resolution
  • C. Data Actions
  • D. Query API

Answer: A,B


NEW QUESTION # 85
What are the two minimum requirements needed when using the Visual Insights Builder to create a calculated insight?
Choose 2 answers

  • A. At least one dimension
  • B. At least two objects to Join
  • C. At least one measure
  • D. A WHERE clause

Answer: A,C

Explanation:
* Introduction to Visual Insights Builder:
The Visual Insights Builder in Salesforce Data Cloud is a tool used to create calculated insights, which are custom metrics derived from the existing data.
Reference:
* Requirements for Creating Calculated Insights:
Measure: A measure is a quantitative value that you want to analyze, such as revenue, number of purchases, or total time spent on a platform.
Dimension: A dimension is a qualitative attribute that you use to categorize or filter the measures, such as date, region, or customer segment.
* Steps to Create a Calculated Insight:
Navigate to the Visual Insights Builder within Salesforce Data Cloud.
Select "Create New Insight" and choose the dataset.
Add at least one measure: This could be any metric you want to analyze, such as "Total Sales." Add at least one dimension: This helps to break down the measure, such as "Sales by Region."
* Practical Application:
Example: To create an insight on "Average Purchase Value by Region," you would need:
A measure: Total Purchase Value.
A dimension: Customer Region.
This allows for actionable insights, such as identifying high-performing regions.


NEW QUESTION # 86
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 segment and copy it for each brand.
  • C. Create a nested segment.
  • D. Create a reusable container block with common criteria.

Answer: D

Explanation:
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 bereused 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 # 87
Cumulus Financial wants to segregate Salesforce CRM Account data based on Country for its Data Cloud users.
What should the consultant do to accomplish this?

  • A. Use formula fields based on the account Country field to filter incoming records.
  • B. Use the data spaces feature and applying filtering on the Account data lake object based on Country.
  • C. Use streaming transforms to filter out Account data based on Country and map to separate data model objects accordingly.
  • D. Use Salesforce sharing rules on the Account object to filter and segregate records based on Country.

Answer: B

Explanation:
Data spaces are a feature that allows Data Cloud users to create subsets of data based on filters and permissions. Data spaces can be used to segregate data based on different criteria, such as geography, business unit, or product line. In this case, the consultant can use the data spaces feature and apply filtering on the Account data lake object based on Country. This way, the Data Cloud users can access only the Account data that belongs to their respective countries. Reference: Data Spaces, Create a Data Space


NEW QUESTION # 88
......

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