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

Salesforce DATA-CLOUD-CONSULTANT Online Questions & Answers

• Question 141:

  Northern Trail Outfitters (NTO) wants to connect their B2C Commerce data with Data Cloud and bring two years of transactional history into Data Cloud.

  What should NTO use to achieve this?

  A. B2C Commerce Starter Bundles
  B. Direct Sales Order entity ingestion
  C. Direct Sales Product entity ingestion
  D. B2C Commerce Starter Bundles plus a custom extract
  D. B2C Commerce Starter Bundles plus a custom extract

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  The B2C Commerce Starter Bundles are predefined data streams that ingest order and product data from B2C Commerce into Data Cloud. However, the starter bundles only bring in the last 90 days of data by default. To bring in two years of transactional history, NTO needs to use a custom extract from B2C Commerce that includes the historical data and configure the data stream to use the custom extract as the source. The other options are not sufficient to achieve this because: B2C Commerce Starter Bundles only ingest the last 90 days of data by default. Direct Sales Order entity ingestion is not a supported method for connecting B2C Commerce data with Data Cloud. Data Cloud does not provide a direct-access connection for B2C Commerce data, only data ingestion. Direct Sales Product entity ingestion is not a supported method for connecting B2C Commerce data with Data Cloud. Data Cloud does not provide a direct-access connection for B2C Commerce data, only data ingestion. References: Create a B2C Commerce Data Bundle - Salesforce, B2C Commerce Connector - Salesforce, Salesforce B2C Commerce Pricing Plans and Costs

• Question 142:

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

• Question 143:

  What is a typical use case for Salesforce Data Cloud?

  A. Data synchronization across the Salesforce ecosystem
  B. Storing CRM data on promises
  C. Data harmonization across multiple platforms
  D. Sending personalized emails at scale
  C. Data harmonization across multiple platforms

• Question 144:

  If a data source does not have a field that can be designated as a primary key, what should the consultant do?

  A. Use the default primary key recommended by Data Cloud.
  B. Create a composite key by combining two or more source fields through a formula field.
  C. Select a field as a primary key and then add a key qualifier.
  D. Remove duplicates from the data source and then select a primary key.
  B. Create a composite key by combining two or more source fields through a formula field.

• Question 145:

  Northern Trail Qutfitters wants to be able to calculate each customer's lifetime value {LTV) but also create breakdowns of the revenue sourced by website, mobile app, and retail channels.

  What should a consultant use to address this use case in Data Cloud?

  A. Flow Orchestration
  B. Nested segments
  C. Metrics on metrics D. Streaming data transform
  C. Metrics on metrics D. Streaming data transform

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  Metrics on metrics is a feature that allows creating new metrics based on existing metrics and applying mathematical operations on them. This can be useful for calculating complex business metrics such as LTV, ROI, or conversion rates. In this case, the consultant can use metrics on metrics to calculate the LTV of each customer by summing up the revenue generated by them across different channels. The consultant can also create breakdowns of the revenue by channel by using the channel attribute as a dimension in the metric definition. References: Metrics on Metrics, Create Metrics on Metrics

• Question 146:

  A company is seeking advice from a consultant on how to address the challenge of having multiple leads and contacts in Salesforce that share the same email address. The consultant wants to provide a detailed and comprehensive explanation on how Data Cloud can be leveraged to effectively solve this issue.

  What should the consultant highlight to address this company's business challenge?

  A. Data Bundles
  B. Calculated Insights
  C. Identity Resolution
  D. Identity Resolution
  C. Identity Resolution

• Question 147:

  A consultant wants to build a new audience in Data Cloud.

  Which three criteria can the consultant include when building a segment? Choose 3 answers

  A. Direct attributes
  B. Data stream attributes
  C. Calculated Insights
  D. Related attributes
  E. Streaming insights
  A. Direct attributes
  C. Calculated Insights
  D. Related attributes

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  A segment is a subset of individuals who meet certain criteria based on their attributes and behaviors. A consultant can use different types of criteria when building a segment in Data Cloud, such as: Direct attributes: These are attributes that describe the characteristics of an individual, such as name, email, gender, age, etc. These attributes are stored in the Profile data model object (DMO) and can be used to filter individuals based on their profile data. Calculated Insights: These are insights that perform calculations on data in a data space and store the results in a data extension. These insights can be used to segment individuals based on metrics or scores derived from their data, such as customer lifetime value, churn risk, loyalty tier, etc. Related attributes: These are attributes that describe the relationships of an individual with other DMOs, such as Email, Engagement, Order, Product, etc. These attributes can be used to segment individuals based on their interactions or transactions with different entities, such as email opens, clicks, purchases, etc. The other two options are not valid criteria for building a segment in Data Cloud. Data stream attributes are attributes that describe the streaming data that is ingested into Data Cloud from various sources, such as Marketing Cloud, Commerce Cloud, Service Cloud, etc. These attributes are not directly available for segmentation, but they can be transformed and stored in data extensions using streaming data transforms. Streaming insights are insights that analyze streaming data in real time and trigger actions based on predefined conditions. These insights are not used for segmentation, but for activation and personalization. References: Create a Segment in Data Cloud, Use Insights in Data Cloud, Data Cloud Data Model

• Question 148:

  Northern Trail Outfitters (NTO) wants to send a promotional campaign for customers that have purchased within the past 6 months. The consultant created a segment to meet this requirement.

  Now, NTO brings an additional requirement to suppress customers who have made purchases within the last week.

  What should the consultant use to remove the recent customers?

  A. Batch transforms
  B. Segmentation exclude rules
  C. Related attributes
  D. Streaming insight
  B. Segmentation exclude rules

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  The consultant should use B. Segmentation exclude rules to remove the recent customers. Segmentation exclude rules are filters that can be applied to a segment to exclude records that meet certain criteria. The consultant can use segmentation exclude rules to exclude customers who have made purchases within the last week from the segment that contains customers who have purchased within the past 6 months. This way, the segment will only include customers who are eligible for the promotional campaign. The other options are not correct. Option A is incorrect because batch transforms are data processing tasks that can be applied to data streams or data lake objects to modify or enrich the data. Batch transforms are not used for segmentation or activation. Option C is incorrect because related attributes are attributes that are derived from the relationships between data model objects. Related attributes are not used for excluding records from a segment. Option D is incorrect because streaming insights are derived attributes that are calculated at the time of data ingestion. Streaming insights are not used for excluding records from a segment. References: Salesforce Data Cloud Consultant Exam Guide, Segmentation, Segmentation Exclude Rules

• Question 149:

  Northern Trail Outfitters uses B2C Commerce and is exploring implementing Data Cloud to get a unified view of its customers and all their order transactions.

  What should the consultant keep in mind with regard to historical data ingesting order data using the B2C Commerce Order Bundle?

  A. The B2C Commerce Order Bundle ingests 12 months of historical data.
  B. The B2C Commerce Order Bundle ingests 6 months of historical data.
  C. The B2C Commerce Order Bundle does not ingest any historical data and only ingests new orders from that point on.
  D. The B2C Commerce Order Bundle ingests 30 days of historical data.
  C. The B2C Commerce Order Bundle does not ingest any historical data and only ingests new orders from that point on.

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  The B2C Commerce Order Bundle is a data bundle that creates a data stream to flow order data from a B2C Commerce instance to Data Cloud. However, this data bundle does not ingest any historical data and only ingests new orders from the time the data stream is created. Therefore, if a consultant wants to ingest historical order data, they need to use a different method, such as exporting the data from B2C Commerce and importing it to Data Cloud using a CSV file. References: Create a B2C Commerce Data Bundle Data Access and Export for B2C Commerce and Commerce Marketplace

• Question 150:

  A customer has a custom Customer Email c object related to the standard Contact object in Salesforce CRM.

  This custom object stores the email address a Contact that they want to use for activation.

  To which data entity is mapped?

  A. Contact
  B. Contact Point_Email
  C. Custom customer Email__c object
  D. Individual
  B. Contact Point_Email

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  The Contact Point_Email object is the data entity that represents an email address associated with an individual in Data Cloud. It is part of the Customer 360 Data Model, which is a standardized data model that defines common entities and relationships for customer data. The Contact Point_Email object can be mapped to any custom or standard object that stores email addresses in Salesforce CRM, such as the custom Customer Email__c object. The other options are not the correct data entities to map to because: The Contact object is the data entity that represents a person who is associated with an account that is a customer, partner, or competitor in Salesforce CRM. It is not the data entity that represents an email address in Data Cloud. The custom Customer Email__c object is not a data entity in Data Cloud, but a custom object in Salesforce CRM. It can be mapped to a data entity in Data Cloud, such as the Contact Point_Email object, but it is not a data entity itself. The Individual object is the data entity that represents a unique person in Data Cloud. It is the core entity for managing consent and privacy preferences, and it can be related to one or more contact points, such as email addresses, phone numbers, or social media handles. It is not the data entity that represents an email address in Data Cloud. References: Customer 360 Data Model: Individual and Contact Points - Salesforce, Contact Point_Email | Object Reference for the Salesforce Platform | Salesforce Developers, [Contact | Object Reference for the Salesforce Platform | Salesforce Developers], [Individual | Object Reference for the Salesforce Platform | Salesforce Developers]