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Salesforce Certified Data Cloud Consultant Sample Questions (Q128-Q133):

NEW QUESTION # 128
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. Contact Data
B. Profile Data
C. Engagement Data
D. Other Data

Answer: D

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.
Reference: Salesforce Data Stream Categories
Ingesting Employee Data:
Employee data typically doesn't fit into profile, contact, or engagement categories meant for customer data.
"Other Data" is appropriate for non-customer-specific data like employee information.
Reference: Salesforce Data Ingestion Guide
Steps to Ingest Employee Data:
Navigate to the data ingestion settings in Salesforce Data Cloud.
Select "Create New Data Stream" and choose the "Other Data" category.
Map the fields from the HR database to the corresponding fields in Data Cloud.
Reference: Salesforce Data Ingestion Tutorial
Practical Application:
Example: A company ingests employee data to segment internal communications or analyze workforce metrics.
Choosing the "Other Data" category ensures that this non-customer data is correctly managed and utilized.
Reference: Salesforce Data Management Case Studies

NEW QUESTION # 129
A bank collects customer data for its loan applicants and high net worth customers. A customer can be both a load applicant and a high net worth customer, resulting in duplicate data.
How should a consultant ingest and map this data in Data Cloud?

A. Ingest the data into two DLOs and then map to two custom DMOs.
B. Use a data transform to consolidate the data into one DLO and them map it to the individual and Contact Point Email DMOs.
C. Ingest the data into one DLO and then map to one custom DMO.
D. Ingest the data into two DLOs and map each to the individual and Contact point Email DMOs.

Answer: D

Explanation:
To handle duplicate data for customers who are both loan applicants and high net worth individuals, the consultant should ingest the data into two separate Data Lake Objects (DLOs) and map them to the Individual and Contact Point Email Data Model Objects (DMOs). Here's why and how this works:
Understanding the Problem :
Customers may exist in both datasets (loan applicants and high net worth individuals), leading to potential duplication.
To avoid redundancy while maintaining data integrity, the data must be ingested and mapped carefully.
Why Two DLOs?
By ingesting the data into two DLOs, you can maintain separation between the two datasets while still leveraging shared attributes (e.g., email addresses).
Mapping both DLOs to the Individual and Contact Point Email DMOs ensures that identity resolution can consolidate duplicate records based on shared identifiers like email.
Steps to Implement This Solution :
Step 1: Create two DLOs-one for loan applicants and another for high net worth customers.
Step 2: Map both DLOs to the Individual DMO to consolidate customer profiles.
Step 3: Map the email fields from both DLOs to the Contact Point Email DMO to enable identity resolution based on email addresses.
Step 4: Configure identity resolution rules to merge duplicate records based on shared attributes like email.
Why Not Other Options?
A . Use a data transform to consolidate the data into one DLO: Consolidating into a single DLO before mapping would lose the distinction between the two datasets and make it harder to manage updates or changes.
C . Ingest the data into two DLOs and then map to two custom DMOs: Creating custom DMOs is unnecessary complexity when the standard Individual and Contact Point Email DMOs can handle this scenario.
D . Ingest the data into one DLO and then map to one custom DMO: Using a single DLO would result in data loss or confusion, as the distinction between loan applicants and high net worth customers would be lost.
By using two DLOs and mapping them to the standard DMOs, the consultant ensures clean data ingestion and effective identity resolution.

NEW QUESTION # 130
A consultant is building a segment to announce a new product launch for customers that have previously purchased black pants.
How should the consultant place attributes for product color and product type from the Order Product object to meet this criteria?

A. Place the attributes for product and product type as direct attributes.
B. Place the attributes for product color and product type in a single container.
C. Place an attribute for the "black" calculated insight to dynamically apply
D. Place the attribute for product color in onecontainer and the attribute for product type in another container.

Answer: B

Explanation:
Explanation
To create a segment based on the product color and product type from the Order Product object, the consultant should place the attributes for product color and product type in a single container. This way, the segment will include only the customers who have purchased black pants, and not those who have purchased black shirts or blue pants. A container is a grouping of attributes that defines a segment of individuals based on a logical AND operation. Placing the attributes in separate containers would result in a segment that includes customers who have purchased any black product or any pants product, which is not the desired criteria. Placing an attribute for the "black" calculated insight would not work, because calculated insights are based on aggregated data and not individual-level data. Placing the attributes as direct attributes would not work, because direct attributes are used to filter individuals based on their profile data, not their order data. References:
* Create a Segment in Data Cloud
* Learn About Segmentation Tools
* Salesforce Launches: Data Cloud Consultant Certification

NEW QUESTION # 131
Which operator should a consultant use to create a segment for a birthday campaign that is evaluated daily?

A. Is Today
B. Is Birthday
C. Is Between
D. Is Anniversary Of

Answer: D

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 # 132
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. Increase the Data Cloud segmentation concurrency limit.
B. Reduce the number of segments being published.
C. Adjust the publish schedule start time of each segment to prevent overlapping processes.
D. Enable rapid segment publishing to all to segment to reduce generation time.

Answer: C

NEW QUESTION # 133
......

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