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Salesforce Certified Data Cloud Consultant Sample Questions (Q66-Q71):
NEW QUESTION # 66
Which operator should a consultant use to create a segment for a birthday campaign that is evaluated daily?
Answer: B
Explanation:
To create a segment for a birthday campaign that is evaluated daily, the consultant should use the Is Anniversary Of operator. This operator compares a date field with the current date and returns true if the month and day are the same, regardless of the year. For example, if the date field is 1990-01-01 and the current date is 2023-01-01, the operator returns true. This way, the consultant can create a segment that includes all the customers who have their birthday on the same day as the current date, and the segment will be updated daily with the new birthdays. The other options are not the best operators to use for this purpose because:
A). The Is Today operator compares a date field with the current date and returns true if the date is the same, including the year. For example, if the date field is 1990-01-01 and the current date is 2023-01-01, the operator returns false. This operator is not suitable for a birthday campaign, as it will only include the customers who were born on the same day and year as the current date, which is very unlikely.
B). The Is Birthday operator is not a valid operator in Data Cloud. There is no such operator available in the segment canvas or the calculated insight editor.
C). The Is Between operator compares a date field with a range of dates and returns true if the date is within the range, including the endpoints. For example, if the date field is 1990-01-01 and the range is 2022-12-25 to
2023-01-05, the operator returns true. This operator is not suitable for a birthday campaign, as it will only include the customers who have their birthday within a fixed range of dates, and the segment will not be updated daily with the new birthdays.
NEW QUESTION # 67
A new user of Data Cloud only needs to be able to review individual rows of ingested data and validate that it has been modeled successfully to its linked data model object. The user will also need to make changes if required.
What is the minimum permission set needed to accommodate this use case?
Answer: C
Explanation:
The Data Cloud User permission set is the minimum permission set needed to accommodate this use case. The Data Cloud User permission set grants access to the Data Explorer feature, which allows the user to review individual rows of ingested data and validate that it has been modeled successfully to its linked data model object. The user can also make changes to the data model object fields, such as adding or removing fields, changing field types, or creating formula fields. The Data Cloud User permission set does not grant access to other Data Cloud features or tasks, such as creating data streams, creating segments, creating activations, or managing users. The other permission sets are either too restrictive or too permissive for this use case. The Data Cloud for Marketing Specialist permission set only grants access to the segmentation and activation features, but not to the Data Explorer feature. The Data Cloud Admin permission set grants access to all Data Cloud features and tasks, including the Data Explorer feature, but it is more than what the user needs. The Data Cloud for Marketing Data Aware Specialist permission set grants access to the Data Explorer feature, but also to the segmentation and activation features, which are not required for this use case. References: Data Cloud Standard Permission Sets, Data Explorer, Set Up Data Cloud Unit
NEW QUESTION # 68
A consultant is reviewing a recent activation using engagement-based related attributes but is not seeing any related attributes in their payload for the majority of their segment members.
Which two areas should the consultant review to help troubleshoot this issue?
Choose 2 answers
Answer: C,D
Explanation:
Explanation
Engagement-based related attributes are attributes that describe the interactions of a person with an email message, such as opens, clicks, unsubscribes, etc. These attributes are stored in the Engagement data model object (DMO) and can be added to an activation to send more personalized communications. However, there are some considerations and limitations when using engagement-based related attributes, such as:
* For engagement data, activation supports a 90-day lookback window. This means that only the attributes from the engagement events that occurred within the last 90 days are considered for activation. Any records outside of this window are not included in the activation payload. Therefore, the consultant should review the event time of the related engagement events and make sure they are within the lookback window.
* The correct path to the related attributes must be selected for the activation. A path is a sequence of DMOs that are connected by relationships in the data model. For example, the path from Individual to Engagement is Individual -> Email -> Engagement. The path determines which related attributes are available for activation and how they are filtered. Therefore, the consultant should review the path selection and make sure it matches the desired related attributes and filters.
The other two options are not relevant for this issue. The activations can reference segments that segment on profile data rather than engagement data, as long as the activation target supports related attributes. The activated profiles do not need to have a Unified Contact Point, which is a unique identifier for a person across different data sources, to activate engagement-based related attributes. References: Add Related Attributes to an Activation, Related Attributes in Data Cloud activation have no values, Explore the Engagement Data Model Object
NEW QUESTION # 69
What is a typical use case for Salesforce Data Cloud?
Answer: C
Explanation:
A typical use case for Salesforce Data Cloud is data harmonization across multiple platforms . Here's why:
Understanding Salesforce Data Cloud
Salesforce Data Cloud is designed to aggregate, unify, and analyze customer data from multiple sources, including CRM, Marketing Cloud, external systems, and third-party platforms.
Its primary purpose is to provide a unified view of customer data for personalized experiences and actionable insights.
Why Data Harmonization Across Multiple Platforms?
Data Harmonization :
Data Cloud harmonizes data by standardizing and cleansing it from disparate sources.
This ensures consistency and accuracy across platforms, enabling organizations to create a single source of truth for customer data.
Use Case Alignment :
Data harmonization is a core functionality of Data Cloud, making it the most relevant use case among the options provided.
Other Options Are Less Relevant :
A . Data synchronization across the Salesforce ecosystem : While Data Cloud integrates with Salesforce products, its primary focus is on unifying data from multiple platforms, not just Salesforce.
B . Storing CRM data on premises : Data Cloud is a cloud-based solution and does not support on-premises storage.
D . Sending personalized emails at scale : This is a use case for Marketing Cloud, not Data Cloud.
Steps to Achieve Data Harmonization
Step 1: Ingest Data
Bring in customer data from multiple sources (e.g., CRM, Marketing Cloud, external systems) into Data Cloud.
Step 2: Standardize and Cleanse Data
Use batch or streaming transformations to standardize formats, remove duplicates, and cleanse data.
Step 3: Create Unified Profiles
Use identity resolution to merge related records into a single unified profile.
Step 4: Activate Insights
Leverage the harmonized data for segmentation, personalization, and analytics.
Conclusion
The most typical use case for Salesforce Data Cloud is data harmonization across multiple platforms , enabling organizations to unify and leverage customer data effectively.
NEW QUESTION # 70
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?
Answer: B
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 # 71
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