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

Salesforce SALESFORCE-DATA-CLOUD Online Questions & Answers

• Question 51:

  A customer has two Data Cloud orgs. A new configuration has been completed and tested for an Amazon S3 data stream and its mappings in one of the Data Cloud orgs.

  What is recommended to package and promote this configuration to the customer's second org?

  A. Use the Metadata API.
  B. Use the Salesforce CRM connector.
  C. Create a data kit.
  D. Package as an AppExchange application.
  C. Create a data kit.

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  Explanation

  Data Cloud Configuration Promotion: When managing configurations across multiple Salesforce Data Cloud orgs, it's essential to use tools that ensure consistency and accuracy in the promotion process.

  Data Kits: Salesforce Data Cloud allows users to package and promote configurations using data kits. These kits encapsulate data stream definitions, mappings, and other configuration elements into a portable format.

  Process: Create a data kit in the source org that includes the Amazon S3 data stream configuration and mappings. Export the data kit from the source org. Import the data kit into the target org, ensuring that all configurations are transferred accurately.

  Advantages: Using data kits simplifies the migration process, reduces the risk of configuration errors, and ensures that all settings and mappings are consistently applied in the new org.

  References:

  Salesforce Data Cloud Developer Guide Salesforce Data Cloud Packaging

• Question 52:

  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?

  A. Marketing Cloud activations apply a frequency cap and limit the number of records that can besent in an activation.
  B. Data Cloud enforces the presence of Contact Point for Marketing Cloud activations. If theindividual does not have a related Contact Point, it will not be activated.
  C. Marketing Cloud activations automatically suppress individuals who are unengaged and have notopened or clicked on an email in the last six months.
  D. Marketing Cloud activations only activate those individuals that already exist in Marketing Cloud.They do not allow activation of new records.
  B. Data Cloud enforces the presence of Contact Point for Marketing Cloud activations. If theindividual does not have a related Contact Point, it will not be activated.

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  Explanation

  Data Cloud requires a Contact Point for Marketing Cloud activations, which is a record that links an individual to an email address. This ensures that the individual has given consent to receive email communications and that the email address is valid. If the individual does not have a related Contact Point, they will not be activated in Marketing Cloud.

  This may result in a lower activated count than the segment Data Cloud Activation, Contact Point for Marketing Cloud

• Question 53:

  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.

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  Explanation

  Understanding Primary Keys in Salesforce Data Cloud: A primary key is a unique identifier for records in a data source. It ensures that each record can be uniquely identified and accessed.

  Salesforce Primary Key Documentation Challenges with Missing Primary Keys: Some data sources may lack a natural primary key, making it difficult to uniquely identify records.

  Salesforce Data Integration Guide Solution: Creating a Composite Key:

  Composite Key Definition: A composite key is created by combining two or more fields to generate a unique identifier.

  Formula Fields: Using a formula field, different fields can be concatenated to create a unique composite key.

  Example: If "Email" and "Phone Number" together uniquely identify a record, a formula field can concatenate these values to form a composite key.

  References:

  Salesforce Composite Key Creation Guide Steps to Create a Composite Key: Identify fields that, when combined, can uniquely identify each record. Create a formula field that concatenates these fields. Use this composite key as the primary key for the data source in Data Cloud.

  References:

  Salesforce Formula Field Documentation

• Question 54:

  Which three objects are created as a result of Identity Resolution?

  A. Unified Subscriber
  B. Unified Data Model
  C. Unified Contact Point
  D. Unified Link
  E. Unified Individual
  C. Unified Contact Point
  D. Unified Link
  E. Unified Individual

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  Explanation

  Identity Resolution creates three types of objects8:

  Unified Individual: This object represents the unified profile of an individual, which contains attributes from multiple sources.

  Unified Contact Point: This object represents the unified contact information of an individual, such as email, phone, address, or app.

  Unified Link: This object represents the link between an Individual object and a Unified Individual object, or between a Contact Point object and a Unified Contact Point object.

• Question 55:

  A client wants to bring in loyalty data from a custom object in Salesforce CRM that contains a point balance for accrued hotel points and airline points within the same record. The client wants to split these point systems into two separate records for better tracking and processing.

  What should a consultant recommend in this scenario?

  A. Clone the data source object.
  B. Use batch transforms to create a second data lake object.
  C. Create a junction object in Salesforce CRM and modify the ingestion strategy.
  D. Create a data kit from the data lake object and deploy it to the same Data Cloud org.
  B. Use batch transforms to create a second data lake object.

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  Explanation

  Batch transforms are a feature that allows creating new data lake objects based on existing data lake objects and applying transformations on them. This can be useful for splitting, merging, or reshaping data to fit the data model or business requirements. In this case, the consultant can use batch transforms to create a second data lake object that contains only the airline points from the original loyalty data object. The original object can be modified to contain only the hotel points. This way, the client can have two separate records for each point system and track and process them accordingly.

  References:

  Batch Transforms, Create a Batch Transform

• Question 56:

  During an implementation project, a consultant completed ingestion of all data streams for their customer.

  Prior to segmenting and acting on that data, which additional configuration is required?

  A. Data Activation
  B. Calculated Insights
  C. Data Mapping
  D. Identity Resolution
  D. Identity Resolution

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  Explanation

  After ingesting data from different sources into Data Cloud, the additional configuration that is required before segmenting and acting on that data is Identity Resolution. Identity Resolution is the process of matching and reconciling source profiles from different data sources and creating unified profiles that represent a single individual or entity 1. Identity Resolution enables you to create a 360-degree view of your customers and prospects, and to segment and activate them based on their attributes and behaviors 2. To configure Identity Resolution, you need to create and deploy a ruleset that defines the match rules and reconciliation rules for your data 3. The other options are incorrect because they are not required before segmenting and acting on the data. Data Activation is the process of sending data from Data Cloud to other Salesforce clouds or external destinations for marketing, sales, or service purposes 4. Calculated Insights are derived attributes that are computed based on the source or unified data, such as lifetime value, churn risk, or product affinity 5. Data Mapping is the process of mapping source attributes to unified attributes in the data model. These configurations can be done after segmenting and acting on the data, or in parallel with Identity Resolution, but they are not prerequisites for it.

  References:

  Identity Resolution Overview, Segment and Activate Data in Data Cloud, Configure Identity Resolution Rulesets, Data Activation Overview, Calculated Insights Overview, [Data Mapping Overview]

• Question 57:

  An administrator wants to be able to create a multi-dimensional metric to identify unified individual lifetime value (LTV).

  Which sequence of DMO joins are necessary within the Calculated Insight to enable this calculation?

  A. Unified Individual > Individual > Sales Order
  B. Unified Individual > Unified Link Individual > Sales Order
  C. Sales Order > Unified Individual
  D. Sales Order > Individual > Unified Individual
  B. Unified Individual > Unified Link Individual > Sales Order

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  Explanation

  To create a multi-dimensional metric to identify unified individual lifetime value (LTV), the administrator needs to join the following data model objects (DMOs) in the Calculated Insight:

  Unified Individual: This DMO represents the unified profile of an individual, which contains attributes from multiple sources.

  Unified Link Individual: This DMO represents the link between an Individual DMO and a Unified Individual DMO.

  Sales Order: This DMO represents a transaction or purchase made by an individual.

  The sequence of joins should start from the Unified Individual DMO, then join the Unified Link Individual DMO using the UnifiedIndividualId field, and then join the Sales Order DMO using the IndividualId field. This way, the administrator can access the sales order data for each unified individual and calculate their lifetime value.

• Question 58:

  An administrator has configured the Salesforce CRM connector and set up a data stream for the Case object. A new custom field called "Business Priority" was created on the Case object. However, that field is not available when trying to add it in the data stream.

  What could be causing this issue?

  A. Custom fields on the Case objects are not supported for ingesting into Data Cloud
  B. Utilize the Salesforce Dataloader application to perform a bulk upload from a desktop
  C. The Data Cloud administrator does not need to do anything. After 24 hours when the data stream refreshes, it will automatically include any new fields that were added to CRM
  D. The Salesforce Integration User is missing "Read" permissions on the newly created field
  D. The Salesforce Integration User is missing "Read" permissions on the newly created field

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  Explanation

  One possible reason why a new custom field is not available in the data stream is that the Salesforce Integration User, which is used to connect to the CRM source, does not have "Read" permissions on that field 2. To fix this issue, the administrator needs to grant the appropriate permissions to the Integration User profile or permission set.

• Question 59:

  Northern Trail Outfitters has the following customer data to ingest into Data Cloud and use for segmentation.

  1. Propensity to purchase

  2. Has active membership

  3. Work email address

  Which data types should the consultant use when ingesting this data?

  A. Number, Text, URL
  B. Percent, Boolean, Email
  C. Number, Boolean, Text
  D. Percent, Number, Email
  B. Percent, Boolean, Email

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  Explanation

  When ingesting customer data into Data Cloud, it is critical to use the correct data types to ensure proper segmentation and usage. Here's how the consultant should handle the provided data points:

  Propensity to Purchase: This represents a likelihood or probability value, typically expressed as a percentage (e.g., 75%). The appropriate data type for this field is Percent, which allows for easy interpretation and use in segmentation.

  Has Active Membership: This is a binary value indicating whether a customer has an active membership (e.g., "Yes" or "No"). The correct data type for this field is Boolean, which supports true/false values.

  Work Email Address: This is a standard email address field. The appropriate data type is Email, which ensures proper validation and formatting. Why Not Other Options?

  A. Number, Text, URL: These data types are incorrect because "Propensity to Purchase" should be a percentage, not a generic number. Similarly, "Work Email Address" should be an email type, not a URL.

  C. Number, Boolean, Text: While "Number" could work for propensity scores, it lacks the semantic meaning of a percentage. Additionally, "Text" is not suitable for email addresses.

  D. Percent, Number, Email: Using "Number" for "Has Active Membership" is incorrect because it is a binary value, not a numeric one. By selecting Percent, Boolean, Email, the consultant ensures that the data is correctly formatted and ready for segmentation and analysis.

• Question 60:

  A customer has a Master Customer table from their CRM to ingest into Data Cloud. The table contains a name and primary email address, along with other personally Identifiable information (Pll).

  How should the fields be mapped to support identity resolution?

  A. Create a new custom object with fields that directly match the incoming table.
  B. Map all fields to the Customer object.
  C. Map name to the Individual object and email address to the Contact Phone Email object.
  D. Map all fields to the Individual object, adding a custom field for the email address.
  C. Map name to the Individual object and email address to the Contact Phone Email object.

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  Explanation

  To support identity resolution in Data Cloud, the fields from the Master Customer table should be mapped to the standard data model objects that are designed for this purpose. The Individual object is used to store the name and other personally identifiable information (PII) of a customer, while the Contact Phone Email object is used to store the primary email address and other contact information of a customer. These objects are linked by a relationship field that indicates the contact information belongs to the individual. By mapping the fields to these objects, Data Cloud can use the identity resolution rules to match and reconcile the profiles from different sources based on the name and email address fields. The other options are not recommended because they either create a new custom object that is not part of the standard data model, or map all fields to the Customer object that is not intended for identity resolution, or map all fields to the Individual object that does not have a standard email address field.

  References:

  Data Modeling Requirements for Identity Resolution, Create Unified Individual Profiles