Salesforce SALESFORCE-DATA-CLOUD Online Practice Questions and Exam Preparation

Salesforce SALESFORCE-DATA-CLOUD Online Questions & Answers

• Question 41:

  What can be customized in the Data Cloud canonical model?

  A. Fields
  B. Objects, Fields, and Relationships
  C. Objects and Fields
  D. Objects
  B. Objects, Fields, and Relationships

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  Explanation

  You can customize the Data Cloud canonical model by adding, editing, or deleting objects, fields, and relationships. You can also modify the properties, labels, and descriptions of these components.

  References:

  https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_canonical_model.htm&type=5

• Question 42:

  Which two objects or fields are supported for ingestion using the Salesforce CRM connector?

  A. Standard Objects
  B. Standard Big Objects
  C. Custom Big Objects
  D. Custom Objects
  A. Standard Objects
  D. Custom Objects

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  Explanation

  The Salesforce CRM connector supports ingestion of standard objects and custom objects from Salesforce CRM. Standard objects are predefined objects that are included with Salesforce CRM, such as Account, Contact, Lead, etc. Custom objects are objects that customers can create to store information that is specific to their organization or industry.

  References:

  [Salesforce CRM Connector], [Standard Objects], [Custom Objects]

• Question 43:

  A segment fails to refresh with the error "Segment references too many Data Lake Objects (DLOs)".

  What are two remedies for this issue?

  A. Space out the segment schedules to reduce Data Lake Object load
  B. Refine segmentation criteria to limit up to 5 custom DMOs
  C. Split the segment into smaller segments
  D. Use Calculated Insights in order to reduce the complexity of the segmentation query
  A. Space out the segment schedules to reduce Data Lake Object load
  C. Split the segment into smaller segments

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  Explanation

  These two remedies can help resolve the error "Segment references too many Data Lake Objects (DLOs)". Spacing out the segment schedules can reduce the concurrent load on the Data Lake Objects and improve performance. Splitting the segment into smaller segments can reduce the number of Data Lake Objects that are referenced by each segment.

  References:

  https://help.salesforce.com/s/articleView?

• Question 44:

  A customer wants to create segments of users based on their Customer Lifetime Value. However, the source data that will be brought into Data Cloud does not include that key performance indicator (KPI).

  Which sequence of steps should the consultant follow to achieve this requirement?

  A. Ingest Data > Map Data to Data Model > Create Calculated Insight > Use in Segmentation
  B. Create Calculated Insight > Map Data to Data Model> Ingest Data > Use in Segmentation
  C. Create Calculated Insight > Ingest Data > Map Data to Data Model> Use in Segmentation
  D. Ingest Data > Create Calculated Insight > Map Data to Data Model > Use in Segmentation
  A. Ingest Data > Map Data to Data Model > Create Calculated Insight > Use in Segmentation

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  Explanation

  To create segments of users based on their Customer Lifetime Value (CLV), the sequence of steps that the consultant should follow is Ingest Data > Map Data to Data Model > Create Calculated Insight > Use in Segmentation. This is because the first step is to ingest the source data into Data Cloud using data streams 1. The second step is to map the source data to the data model, which defines the structure and attributes of the data 2. The third step is to create a calculated insight, which is a derived attribute that is computed based on the source or unified data 3. In this case, the calculated insight would be the CLV, which can be calculated using a formula or a query based on the sales order data 4.

  The fourth step is to use the calculated insight in segmentation, which is the process of creating groups of individuals or entities based on their attributes and behaviors. By using the CLV calculated insight, the consultant can segment the users by their predicted revenue from the lifespan of their relationship with the brand. The other options are incorrect because they do not follow the correct sequence of steps to achieve the requirement. Option B is incorrect because it is not possible to create a calculated insight before ingesting and mapping the data, as the calculated insight depends on the data model objects 3.

  Option C is incorrect because it is not possible to create a calculated insight before mapping the data, as the calculated insight depends on the data model objects 3.

  Option D is incorrect because it is not recommended to create a calculated insight before mapping the data, as the calculated insight may not reflect the correct data model structure and attributes 3.

  References:

  Data Streams Overview, Data Model Objects Overview, Calculated Insights Overview, Calculating Customer Lifetime Value (CLV) With Salesforce, [Segmentation Overview]

• Question 45:

  Which feature can integrate in real time with Salesforce CRM?

  A. Data Actions
  B. Identity Resolution
  C. CRM Starter Bundle
  D. Data Model Triggers
  A. Data Actions

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  Explanation

  This feature can integrate in real time with Salesforce CRM. Data Actions allow you to perform actions on Salesforce CRM records based on Data Cloud data, such as creating, updating, or deleting records.

  References:

  https://help.salesforce.com/s/articleView?id=sf.c360_a_data_actions.htm&type=5

• Question 46:

  How do the Data streams that use the Marketing Cloud Connector refresh data?

  A. Manually refreshed by CDP Admin
  B. Marketing Cloud's Automation Studio handles this process.
  C. APIs are used for refresh
  D. None of the above
  B. Marketing Cloud's Automation Studio handles this process.

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  Explanation

  The data streams that use the Marketing Cloud Connector refresh data using Marketing Cloud's Automation Studio. The Marketing Cloud Connector is a feature that allows you to stream data from Marketing Cloud to Data Cloud in near real time. The connector uses Automation Studio to schedule and run data extracts from Marketing Cloud data extensions and send them to Data Cloud via SFTP. You can configure the frequency and time of the data extracts in Automation Studio.

  References:

  Marketing Cloud Connector

• Question 47:

  An administrator is setting up a data stream with transactional data.

  What field type should the administrator choose to ensure that leading zeros in the purchase order number are preserved?

  A. Number
  B. Decimal
  C. Text
  D. Serial
  C. Text

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  Explanation

  The Text field type should be chosen to preserve leading zeros in the purchase order number, as this field type stores alphanumeric characters as strings. The Number and Decimal field types store numeric values as numbers, which would remove any leading zeros. The Serial field type is not a valid field type in Data Cloud.

• Question 48:

  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

  A. The related engagement events occurred within the last 90 days.
  B. The activations are referencing segments that segment on profile data rather than engagement data.
  C. The correct path is selected for the related attributes.
  D. The activated profiles have a Unified Contact Point.
  A. The related engagement events occurred within the last 90 days.
  C. The correct path is selected for the related attributes.

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  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.

  Add Related Attributes to an Activation, Related Attributes in Data Cloud activation have no values, Explore the Engagement Data Model Object

• Question 49:

  When can the data types be changed during ingestion?

  A. After the DSO is created
  B. Before DSO is created
  C. Data type can never be changed
  D. Data type can be changed at any time
  B. Before DSO is created

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  Explanation

  The data types can be changed during ingestion before the Data Source Object (DSO) is created. A DSO is a container for ingested data that defines the schema, format, and metadata of the data. Data types can be changed in the Data Explorer before creating a DSO by using the Edit Schema option. Once a DSO is created, the data types cannot be changed.

  References:

  Create a Data Source Object

• Question 50:

  What happens if no file name is specified in AWS S3 data stream during ingestion?

  A. The system does not fetch any file and the data stream shows an error.
  B. The system chooses the first file found in the S3 bucket
  C. The ingestion setup can't be completed without specifying the filename.
  D. The ingestion setup is completed but the data stream shows 0 records
  A. The system does not fetch any file and the data stream shows an error.

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  Explanation

  If no file name is specified in AWS S3 data stream during ingestion, the system does not fetch any file and the data stream shows an error. AWS S3 data stream is a feature that allows you to stream data from Amazon Web Services Simple Storage Service (AWS S3) to Data Cloud in near real time. You need to specify the file name or prefix of the files that you want to ingest from your S3 bucket. If you leave this field blank, the system cannot find any matching files and returns an error message.

  References:

  AWS S3 Data Stream