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

Salesforce SALESFORCE-DATA-CLOUD Online Questions & Answers

• Question 171:

  The leadership team at Cumulus Financial has determined that customers who deposited more than $250,000 in the last five years and are not using advisory services will be the central focus for all new campaigns in the next year.

  Which features support this use case?

  A. Calculated insight and data action
  B. Calculated insight and segment
  C. Streaming insight and segment
  D. Streaming insight and data action
  B. Calculated insight and segment

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  Explanation

  Understanding the Use Case: The leadership team wants to focus on customers who have deposited more than $250,000 in the last five years and are not using advisory services.

  References:

  Salesforce Data Cloud Use Case Documentation Features Involved: Calculated Insight: This feature helps derive metrics and values based on existing data. In this case, it can calculate total deposits over the last five years. Segment: Segmentation allows targeting specific groups of customers based on defined criteria, such as total deposits and usage of advisory services.

  Salesforce Calculated Insights and Segmentation Guide Steps to Implement: Create a Calculated Insight:

  Navigate to Visual Insights Builder in Salesforce Data Cloud. Create a new calculated insight to sum deposits for each customer over the last five years. Create a Segment: Use the Segment Canvas to create a new segment. Apply filters to include customers with deposits over $250,000 and exclude those using advisory services.

  Salesforce Calculated Insights Tutorial and Segment Creation Guide Practical Application: Example: Identify high-value customers who are not leveraging additional services and target them with personalized marketing campaigns to promote advisory services.

  References:

  Salesforce High-Value Customer Segmentation Case Study

• Question 172:

  When setting up the data source object or schema for data ingestion, what are the three data categories to select from?

  A. Engagement Data
  B. Event Data
  C. Other Data
  D. Order Data
  E. Profile Data
  A. Engagement Data
  D. Order Data
  E. Profile Data

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  Explanation

  These are the three data categories to select from when setting up the data source object or schema for data ingestion. Engagement data includes information about how customers interact with a brand or product, such as clicks, views, likes, etc. Order data includes information about transactions or purchases made by customers, such as order ID, amount, date, etc. Profile data includes information about customers' attributes or preferences, such as name, email, gender, etc.

• Question 173:

  Which two statements about Data Cloud's Web and Mobile App connector are true?

  A. Any Data Streams associated with Web or Mobile connector app will be automatically deleted upon deleting the app from Data Cloud Setup
  B. Data Cloud administrators can see the status of a Web or Mobile connector app on the app details page
  C. Tenant Specific Endpoint is auto-generated in Data Cloud when setting up a Mobile or Web app connection
  D. Mobile and Web SDK schema can be updated to delete an existing field
  B. Data Cloud administrators can see the status of a Web or Mobile connector app on the app details page
  C. Tenant Specific Endpoint is auto-generated in Data Cloud when setting up a Mobile or Web app connection

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  Explanation

  The app details page shows the status of the app, such as active, inactive, or error. The tenant specific endpoint is a unique URL that is generated for each app and used to send data to Data Cloud from the web or mobile SDK.

  References:

  https://help.salesforce.com/s/articleView?id=sf.c360_a_web_mobile_app_connector.htm&type=5

• Question 174:

  A consultant needs to create a data graph based on several DLOs,

  Which step should the consultant take to make this work?

  A. Use a data action to update the data graph with the DLO data
  B. Map the DLOS to DMOS and use these in the data graph.
  C. Map the DLOs directly to a data graph.
  D. Batch transform the DLOs to multiple DMOs and activate these with the data graph.
  B. Map the DLOS to DMOS and use these in the data graph.

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  Explanation

  To create a data graph based on several Data Lake Objects (DLOs), the consultant should map the DLOs to Data Model Objects (DMOs) and use these in the data graph. Here's why: Understanding Data Graphs A data graph in Salesforce Data Cloud represents relationships between entities (e.g., customers, accounts, orders) and their attributes. It is built using Data Model Objects (DMOs), which provide a standardized structure for unified profiles and related data. Why Map DLOs to DMOs?

  Role of DLOs and DMOs: DLOs are raw data sources ingested into Data Cloud. DMOs are standardized objects used for identity resolution and unified profiles. Mapping DLOs to DMOs ensures that raw data is transformed into a structured format suitable for data graphs. Building the Data Graph: Once the DLOs are mapped to DMOs, the consultant can use the DMOs to define relationships and build the data graph.

  This approach ensures consistency and alignment with the unified data model.

  Other Options Are Less Suitable:

  A. Use a data action to update the data graph with the DLO data: Data actions are used for triggering workflows, not for building data graphs.

  C. Map the DLOs directly to a data graph: DLOs cannot be directly mapped to a data graph; they must first be transformed into DMOs.

  D. Batch transform the DLOs to multiple DMOs and activate these with the data graph: This is overly complex and unnecessary when mapping DLOs to DMOs suffices. Steps to Create the Data Graph Step 1: Map DLOs to DMOs Navigate to Data Cloud > Data Streams and map the relevant fields from the DLOs to the corresponding DMOs. Step 2: Define Relationships Use the Data Model tab to define relationships between DMOs (e.g., linking Individuals to Accounts). Step 3: Build the Data Graph Use the mapped DMOs to create the data graph, defining nodes (entities) and edges (relationships). Step 4: Validate the Graph Test the data graph to ensure it accurately represents the desired relationships and data flow. Conclusion The consultant should map the DLOs to DMOs and use these in the data graph to ensure a structured and consistent approach to building relationships between entities.

• Question 175:

  A user Is not seeing suggested values from newly-modeled data when building a segment.

  What is causing this issue?

  A. Value suggestion will only return results for the first 50 values of a specific attribute,
  B. Value suggestion can only work on direct attributes and not related attributes.
  C. Value suggestion requires Data Aware Specialist permissions at a minimum.
  D. Value suggestion is still processing and takes up to 24 hours to be available.
  D. Value suggestion is still processing and takes up to 24 hours to be available.

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  Explanation

  The most likely cause of this issue is that value suggestion is still processing and takes up to 24 hours to be available. Value suggestion is a feature that enables you to see suggested values for data model object (DMO) fields when creating segment filters. However, this feature needs to be enabled for each DMO field, and it can take up to 24 hours for the suggested values to appear after enabling the feature 1. Therefore, if a user is not seeing suggested values from newly-modeled data, it could be that the data has not been processed yet by the value suggestion feature.

  References:

  Use Value Suggestions in Segmentation

• Question 176:

  What is the correct formula to display the value of the raw data column of "RetailPrice' plus an additional 5 percent?

  A. sourceField['RetailPrice1*l .05
  B. SELECT(['RetailPrice']*1.05)
  C. sourceField['retailprice']*1.05
  D. SELECT(['retailprice']*1.05)
  C. sourceField['retailprice']*1.05

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  Explanation

  This is the correct formula to display the value of the raw data column of "RetailPrice" plus an additional 5 percent. The formula uses the sourceField function to access the raw data column, and then multiplies it by 1.05 to add 5 percent. The formula is case-sensitive, so the column name must match exactly with the raw data column name.

  References:

  [Formula Editor], [sourceField Function]

• Question 177:

  How many calculated insights can be created per tenant?

  A. 5
  B. 10
  C. 50
  D. 100
  C. 50

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  Explanation

  The maximum number of calculated insights that can be created per tenant is 50. A calculated insight is a metric that defines and calculates a multidimensional measure on your data. You can use calculated insights to create segments and analyze your data in Data Cloud. You can also use calculated insights to create dashboards and reports in Tableau CRM.

  References:

  Calculated Insights

• Question 178:

  The leadership team at Cumulus Financial has declared that customers who have deposited more than $250,000 in the last 5 years and who are not using advisory services, will be the central focus for all new campaigns in the next year.

  Which two features support this need?

  A. Calculated Insight
  B. Report|
  C. Segment
  D. Dashboard
  A. Calculated Insight
  C. Segment

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  Explanation

  These two features support the need to calculate each customer's lifetime value (LTV) and create breakdowns of the revenue sourced by different channels. Calculated Insight allows you to create complex calculations based on stored data, such as LTV. Segment allows you to create audiences based on different criteria, such as revenue source.

  References:

  https://help.salesforce.com/s/articleView?id=sf.c360_a_calculated_insights.htm&type=5https://help.salesforce.com/s/articleView?id=sf.c360_a_segmentation.htm&type=5

• Question 179:

  Which operator can be used to create a segment for a birthday campaign that is evaluated daily?

  A. Is This Year
  B. Is Anniversary Of
  C. Is Between
  D. Is Birthday
  B. Is Anniversary Of

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  Explanation

  This operator can be used to create a segment for a birthday campaign that is evaluated daily. It compares a date attribute to the current date and returns true if they have the same month and day, regardless of the year.

  References:

  https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_segmentation_operators.htm&type=5

• Question 180:

  What is the relationship between Individual and Contact Point Objects?

  A. 1:1
  B. 1: Many
  C. Many: Many
  D. None of the above
  B. 1: Many

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  Explanation

  The relationship between Individual and Contact Point Objects is 1: Many. This means that one Individual can have many Contact Points, such as email addresses, phone numbers, or postal addresses, but each Contact Point can only belong to one Individual.

  References:

  Data Model Overview