DATA-CLOUD-CONSULTANT EXAM DISCOUNT, DATA-CLOUD-CONSULTANT NEW BRAINDUMPS PDF

Data-Cloud-Consultant Exam Discount, Data-Cloud-Consultant New Braindumps Pdf

Data-Cloud-Consultant Exam Discount, Data-Cloud-Consultant New Braindumps Pdf

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Salesforce Certified Data Cloud Consultant Sample Questions (Q46-Q51):

NEW QUESTION # 46
Which configuration supports separate Amazon S3 buckets for data ingestion and activation?

  • A. Dedicated S3 data sources in Data Cloud setup
  • B. Dedicated S3 data sources in activation setup
  • C. Separate user credentials for data stream and activation target
  • D. Multiple S3 connectors in Data Cloud setup

Answer: A

Explanation:
Explanation
To support separate Amazon S3 buckets for data ingestion and activation, you need to configure dedicated S3 data sources in Data Cloud setup. Data sources are used to identify the origin and type of the data that you ingest into Data Cloud1. You can create different data sources for each S3 bucket that you want to use for ingestion or activation, and specify the bucket name, region, and access credentials2. This way, you can separate and organize your data by different criteria, such as brand, region, product, or business unit3. The other options are incorrect because they do not support separate S3 buckets for data ingestion and activation. Multiple S3 connectors are not a valid configuration in Data Cloud setup, as there is only one S3 connector available4. Dedicated S3 data sources in activation setup are not a valid configuration either, as activation setup does not require data sources, but activation targets5. Separate user credentials for data stream and activation target are not sufficient to support separate S3 buckets, as you also need to specify the bucket name and region for each data source2. References: Data Sources Overview, Amazon S3 Storage Connector, Data Spaces Overview, Data Streams Overview, Data Activation Overview


NEW QUESTION # 47
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 a nested segment.
  • B. Create a segment and copy it for each brand.
  • C. Create a reusable container block with common criteria.
  • D. Create, publish, and deploy a data kit.

Answer: C

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 be reused 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.
Reference:
Create a Container Block
Create a Segment in Data Cloud
Create and Publish a Data Kit
Create a Nested Segment


NEW QUESTION # 48
A consultant needs to minimize the difference between a Data Cloud segment population and Marketing Cloud data extension count to determine the true size of segments for campaign planning.
What should the consultant recommend to filter the segments by to accomplish this?

  • A. User preferences for marketing outreach
  • B. Geographical divisions
  • C. Business units
  • D. Marketing Cloud Journeys

Answer: A

Explanation:
Segment Population vs. Data Extension Count: Minimizing the difference between Data Cloud segment populations and Marketing Cloud data extensions ensures accurate segment sizes for campaign planning.
Filtering by User Preferences: By filtering segments based on user preferences for marketing outreach, you ensure that only those contacts who have opted in or are eligible for marketing campaigns are included. This aligns the segment population in Data Cloud with the counts in Marketing Cloud.
Process:
* Define Preferences: Ensure that user preferences for marketing outreach are clearly defined and captured
* in the system.
* Filter Segments: Use these preferences to filter segments in Data Cloud, ensuring only the relevant contacts are included.
Benefits:
* Accuracy: Increases the accuracy of segment sizes by including only those who have opted in for marketing.
* Compliance: Helps in complying with regulatory requirements for marketing communications.
References:
* Salesforce Data Cloud Segmentation
* Marketing Cloud Data Extensions


NEW QUESTION # 49
Northern Trail Outfitters wants to use some of its Marketing Cloud data in Data Cloud.
Which engagement channel data will require custom integration?

  • A. SMS
  • B. CloudPage
  • C. Mobile push
  • D. Email

Answer: B

Explanation:
CloudPage is a web page that can be personalized and hosted by Marketing Cloud. It is not one of the standard engagement channels that Data Cloud supports out of the box. To use CloudPage data in Data Cloud, a custom integration is required. The other engagement channels (SMS, email, and mobile push) are supported by Data Cloud and can be integrated using the Marketing Cloud Connector or the Marketing Cloud API. References: Data Cloud Overview, Marketing Cloud Connector, Marketing Cloud API


NEW QUESTION # 50
A consultant is planning the ingestion of a data stream that has profile information including a mobile phone number.
To ensure that the phone number can be used for future SMS campaigns, they need to confirm the phone number field is in the proper E164 Phone Number format. However, the phone numbers in the file appear to be in varying formats.
What is the most efficient way to guarantee that the various phone number formats are standardized?

  • A. Assign the PhoneNumber field type when creating the data stream.
  • B. Edit and update the data in the source system prior to sending to Data Cloud.
  • C. Create a formula field to standardize the format.
  • D. Create a calculated insight after ingestion.

Answer: A

Explanation:
The most efficient way to guarantee that the various phone number formats are standardized is to assign the PhoneNumber field type when creating the data stream. The PhoneNumber field type is a special field type that automatically converts phone numbers into the E164 format, which is the international standard for phone numbers. The E164 format consists of a plus sign (+), the country code, and the national number. For example, +1-202-555-1234 is the E164 format for a US phone number. By using the PhoneNumber field type, the consultant can ensure that the phone numbers are consistent and can be used for future SMS campaigns. The other options are either more time-consuming, require manual intervention, or do not address the formatting issue. Reference: Data Stream Field Types, E164 Phone Number Format, Salesforce Data Cloud Exam Questions


NEW QUESTION # 51
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