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[Hardware] 100% Pass Salesforce - Data-Cloud-Consultant–Trustable Pass Test

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【Hardware】 100% Pass Salesforce - Data-Cloud-Consultant–Trustable Pass Test

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Salesforce Data-Cloud-Consultant Exam Syllabus Topics:
TopicDetails
Topic 1
  • 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 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
  • 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 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.

Salesforce Certified Data Cloud Consultant Sample Questions (Q26-Q31):NEW QUESTION # 26
How does Data Cloud ensure high availability and fault tolerance for customer data?
  • A. By limiting data access to essential personnel
  • B. By using a data center with robust backups
  • C. By distributing data across multiple regions and data centers
  • D. By Implementing automatic data recovery procedures
Answer: C
Explanation:
Ensuring High Availability and Fault Tolerance:
High availability refers to systems that are continuously operational and accessible, while fault tolerance is the ability to continue functioning in the event of a failure.
Reference: Salesforce High Availability and Fault Tolerance Whitepaper
Data Distribution Across Multiple Regions and Data Centers:
Salesforce Data Cloud ensures high availability by replicating data across multiple geographic regions and data centers. This distribution mitigates risks associated with localized failures.
If one data center goes down, data and services can continue to be served from another location, ensuring uninterrupted service.
Reference: Salesforce Infrastructure Overview
Benefits of Regional Data Distribution:
Redundancy: Having multiple copies of data across regions provides redundancy, which is critical for disaster recovery.
Load Balancing: Traffic can be distributed across data centers to optimize performance and reduce latency.
Regulatory Compliance: Storing data in different regions helps meet local data residency requirements.
Reference: Salesforce Data Center Locations and Regional Data Hosting
Implementation in Salesforce Data Cloud:
Salesforce utilizes a robust architecture involving data replication and failover mechanisms to maintain data integrity and availability.
This architecture ensures that even in the event of a regional outage, customer data remains secure and accessible.
Reference: Salesforce Trust and Compliance Documentation

NEW QUESTION # 27
Which two requirements must be met for a calculated insight to appear in the segmentation canvas?
Choose 2 answers
  • A. The metrics of the calculated insights must only contain numeric values.
  • B. The primary key of the segmented table must be a metric in the calculated insight.
  • C. The calculated insight must contain a dimension including the Individual or Unified Individual Id.
  • D. The primary key of the segmented table must be a dimension in the calculated insight.
Answer: C,D
Explanation:
A calculated insight is a custom metric or measure that is derived from one or more data model objects or data lake objects in Data Cloud. A calculated insight can be used in segmentation to filter or group the data based on the calculated value. However, not all calculated insights can appear in the segmentation canvas.
There are two requirements that must be met for a calculated insight to appear in the segmentation canvas:
The calculated insight must contain a dimension including the Individual or Unified Individual Id. A dimension is a field that can be used to categorize or group the data, such as name, gender, or location.
The Individual or Unified Individual Id is a unique identifier for each individual profile in Data Cloud.
The calculated insight must include this dimension to link the calculated value to the individual profile and to enable segmentation based on the individual profile attributes.
The primary key of the segmented table must be a dimension in the calculated insight. The primary key is a field that uniquely identifies each record in a table. The segmented table is the table that contains the data that is being segmented, such as the Customer or the Order table. The calculated insight must include the primary key of the segmented table as a dimension to ensure that the calculated value is associated with the correct record in the segmented table and to avoid duplication or inconsistency in the segmentation results.
References: Create a Calculated Insight, Use Insights in Data Cloud, Segmentation

NEW QUESTION # 28
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. Calculated insight
  • B. Batch bata transform
  • C. Streaming insight
  • D. Streaming data 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 # 29
A customer has outlined requirements to trigger a journey for an abandoned browse behavior. Based on the requirements, the consultant determines they will use streaming insights to trigger a data action to Journey Builder every hour.
How should the consultant configure the solution to ensure the data action is triggered at the cadence required?
  • A. Set the insights aggregation time window to 1 hour.
  • B. Set the activation schedule to hourly.
  • C. Set the journey entry schedule to run every hour.
  • D. Configure the data to be ingested in hourly batches.
Answer: C
Explanation:
Explanation:

NEW QUESTION # 30
A Data Cloud customer wants to adjust their identity resolution rules to increase their accuracy of matches. Rather than matching on email address, they want to review a rule that joins their CRM Contacts with their Marketing Contacts, where both use the CRM ID as their primary key.
Which two steps should the consultant take to address this new use case?
Choose 2 answers
  • A. Map the primary key from the two systems to party identification, using CRM ID as the identification name for individuals coming from the CRM, and Marketing ID as the identification name for individuals coming from the marketing platform.
  • B. Create a custom matching rule for an exact match on the Individual ID attribute.
  • C. Map the primary key from the two systems to Party Identification, using CRM ID as the identification name for both.
  • D. Create a matching rule based on party identification that matches on CRM ID as the party identification name.
Answer: C,D
Explanation:
To address this new use case, the consultant should map the primary key from the two systems to Party Identification, using CRM ID as the identification name for both, and create a matching rule based on party identification that matches on CRM ID as the party identification name. This way, the consultant can ensure that the CRM Contacts and Marketing Contacts are matched based on their CRM ID, which is a unique identifier for each individual. By using Party Identification, the consultant can also leverage the benefits of this attribute, such as being able to match across different entities and sources, and being able to handle multiple values for the same individual. The other options are incorrect because they either do not use the CRM ID as the primary key, or they do not use Party Identification as the attribute type. References: Configure Identity Resolution Rulesets, Identity Resolution Match Rules, Data Cloud Identity Resolution Ruleset, Data Cloud Identity Resolution Config Input

NEW QUESTION # 31
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