Free Data-Cloud-Consultant Exam Braindumps (page: 19)

Page 19 of 35

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

  1. Is Today
  2. Is Birthday
  3. Is Between
  4. Is Anniversary Of

Answer(s): 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.



Luxury Retailers created a segment targeting high value customers that it activates through Marketing Cloud for email communication. The company notices that the activated count is smaller than the segment count.
What is a reason for this?

  1. Data Cloud enforces the presence of Contact Point for Marketing Cloud activations. If the individual does not have a related Contact Point, it will not be activated.
  2. Marketing Cloud activations automatically suppress individuals who are unengaged and have not opened or clicked on an email in the last six months.
  3. Marketing Cloud activations only activate those individuals that already exist in Marketing Cloud.

    They do not allow activation of new records.
  4. Marketing Cloud activations apply a frequency cap and limit the number of records that can be sent in an activation.

Answer(s): A

Explanation:

The reason for the activated count being smaller than the segment count is A. Data Cloud enforces the presence of Contact Point for Marketing Cloud activations. If the individual does not have a related Contact Point, it will not be activated. A Contact Point is a data model object that represents a channel or method of communication with an individual, such as email, phone, or social media. For Marketing Cloud activations, Data Cloud requires that the individual has a related Contact Point of type Email, which contains a valid email address. If the individual does not have such a Contact Point, or if the Contact Point is missing or invalid, the individual will not be activated and will not receive the email communication. Therefore, the activated count may be lower than the segment count, depending on how many individuals in the segment have a valid email Contact Point.


Reference:

Salesforce Data Cloud Consultant Exam Guide, Contact Point, Marketing Cloud Activation



A Data Cloud consultant recently added a new data source and mapped some of the data to a new custom data model object (DMO)
that they want to use for creating segments. However, they cannot view the newly created DMO when trying to create a new segment.
What is the cause of this issue?

  1. Data has not yes been ingested into the DMO.
  2. The new DMO is not of category Profile.
  3. The new DMO does not have a relationship to the individual DMO
  4. Segmentation is only supported for the Individual and Unified Individual DMOs.

Answer(s): B

Explanation:

The cause of this issue is that the new custom data model object (DMO) is not of category Profile. A

category is a property of a DMO that defines its purpose and functionality in Data Cloud. There are three categories of DMOs: Profile, Event, and Other. Profile DMOs are used to store attributes of individuals or entities, such as name, email, address, etc. Event DMOs are used to store actions or interactions of individuals or entities, such as purchases, clicks, visits, etc. Other DMOs are used to store any other type of data that does not fit into the Profile or Event categories, such as products, locations, categories, etc. Only Profile DMOs can be used for creating segments in Data Cloud, as segments are based on the attributes of individuals or entities. Therefore, if the new custom DMO is not of category Profile, it will not appear in the segmentation canvas. The other options are not correct because they are not the cause of this issue. Data ingestion is not a prerequisite for creating segments, as segments can be created based on the data model schema without actual data. The new DMO does not need to have a relationship to the individual DMO, as segments can be created based on any Profile DMO, regardless of its relationship to other DMOs. Segmentation is not only supported for the Individual and Unified Individual DMOs, as segments can be created based on any Profile DMO, including custom ones.


Reference:

Create a Custom Data Model Object from an Existing Data Model Object, Create a Segment in Data Cloud, Data Model Object Category



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?

  1. Use streaming transforms to filter out Account data based on Country and map to separate data model objects accordingly.
  2. Use the data spaces feature and applying filtering on the Account data lake object based on Country.
  3. Use Salesforce sharing rules on the Account object to filter and segregate records based on Country.
  4. Use formula fields based on the account Country field to filter incoming records.

Answer(s): 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



Page 19 of 35



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Srivats commented on October 25, 2024
Hello, Great learning. Thank you. Looks like Question 13's answer should be D. "If you plan to use the segment again, stop the publish schedule instead" as highlighted in doc.
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