Salesforce Salesforce Certifications DATA-CLOUD-CONSULTANT Questions & Answers

• Question 51:

  A retailer wants to unify profiles using Loyalty ID which is different than the unique ID of their customers.

  Which object should the consultant use in identity resolution to perform exact match rules on the Loyalty ID?

  A. Party Identification object

  B. Loyalty Identification object

  C. Individual object

  D. Contact Identification object

  Correct Answer: A

  The Party Identification object is the correct object to use in identity resolution to perform exact match rules on the Loyalty ID. The Party Identification object is a child object of the Individual object that stores different types of identifiers for an individual, such as email, phone, loyalty ID, social media handle, etc. Each identifier has a type, a value, and a source. The consultant can use the Party Identification object to create a match rule that compares the Loyalty ID type and value across different sources and links the corresponding individuals.

  The other options are not correct objects to use in identity resolution to perform exact match rules on the Loyalty ID. The Loyalty Identification object does not exist in Data Cloud. The Individual object is the parent object that represents a unified profile of an individual, but it does not store the Loyalty ID directly. The Contact Identification object is a child object of the Contact object that stores identifiers for a contact, such as email, phone, etc., but it does not store the Loyalty ID.

  References:

  1.

  Data Modeling Requirements for Identity Resolution

  2.

  Identity Resolution in a Data Space

  3.

  Configure Identity Resolution Rulesets

  4.

  Map Required Objects

  5.

  Data and Identity in Data Cloud

• Question 52:

  Northern Trail Outfitters (NTO), an outdoor lifestyle clothing brand, recently started a new line of business. The new business specializes in gourmet camping food. For business reasons as well as security reasons, it's important to NTO to keep all Data Cloud data separated by brand.

  Which capability best supports NTO's desire to separate its data by brand?

  A. Data streams for each brand

  B. Data model objects for each brand

  C. Data spaces for each brand

  D. Data sources for each brand

  Correct Answer: C

  Data spaces are logical containers that allow you to separate and organize your data by different criteria, such as brand, region, product, or business unit1. Data spaces can help you manage data access, security, and governance, as well as enable cross-cloud data integration and activation2. For NTO, data spaces can support their desire to separate their data by brand, so that they can have different data models, rules, and insights for their outdoor lifestyle clothing and gourmet camping food businesses. Data spaces can also help NTO comply with any data privacy and security regulations that may apply to their different brands3. The other options are incorrect because they do not provide the same level of data separation and organization as data spaces. Data streams are used to ingest data from different sources into Data Cloud, but they do not separate the data by brand4. Data model objects are used to define the structure and attributes of the data, but they do not isolate the data by brand5. Data sources are used to identify the origin and type of the data, but they do not partition the data by brand. References: Data Spaces Overview, Create Data Spaces, Data Privacy and Security in Data Cloud, Data Streams Overview, Data Model Objects Overview, [Data Sources Overview]

• Question 53:

  A customer has multiple team members who create segment audiences that work in different time zones. One team member works at the home office in the Pacific time zone, that matches the org Time Zone setting. Another team member works remotely in the Eastern time zone.

  Which user will see their home time zone in the segment and activation schedule areas?

  A. The team member in the Pacific time zone.

  B. The team member in the Eastern time zone.

  C. Neither team member; Data Cloud shows all schedules in GMT.

  D. Both team members; Data Cloud adjusts the segment and activation schedules to the time zone of the logged-in user

  Correct Answer: D

  The correct answer is D, both team members; Data Cloud adjusts the segment and activation schedules to the time zone of the logged-in user. Data Cloud uses the time zone settings of the logged-in user to display the segment and activation schedules. This means that each user will see the schedules in their own home time zone, regardless of the org time zone setting or the location of other team members. This feature helps users to avoid confusion and errors when scheduling segments and activations across different time zones. The other options are incorrect because they do not reflect how Data Cloud handles time zones. The team member in the Pacific time zone will not see the same time zone as the org time zone setting, unless their personal time zone setting matches the org time zone setting. The team member in the Eastern time zone will not see the schedules in the org time zone setting, unless their personal time zone setting matches the org time zone setting. Data Cloud does not show all schedules in GMT, but rather in the user's local time zone.

  References:

  1.

  Data Cloud Time Zones

  2.

  Change default time zones for Users and the organization

  3.

  Change your time zone settings in Salesforce, Google and Outlook

  4.

  DateTime field and Time Zone Settings in Salesforce

• Question 54:

  Data Cloud receives a nightly file of all ecommerce transactions from the previous day.

  Several segments and activations depend upon calculated insights from the updated data in order to maintain accuracy in the customer's scheduled campaign messages.

  What should the consultant do to ensure the ecommerce data is ready for use for each of the scheduled activations?

  A. Use Flow to trigger a change data event on the ecommerce data to refresh calculated insights and segments before the activations are scheduled to run.

  B. Set a refresh schedule for the calculated insights to occur every hour.

  C. Ensure the activations are set to Incremental Activation and automatically publish every hour.

  D. Ensure the segments are set to Rapid Publish and set to refresh every hour.

  Correct Answer: A

  The best option that the consultant should do to ensure the ecommerce data is ready for use for each of the scheduled activations is A. Use Flow to trigger a change data event on the ecommerce data to refresh calculated insights and segments before the activations are scheduled to run. This option allows the consultant to use the Flow feature of Data Cloud, which enables automation and orchestration of data processing tasks based on events or schedules. Flow can be used to trigger a change data event on the ecommerce data, which is a type of event that indicates that the data has been updated or changed. This event can then trigger the refresh of the calculated insights and segments that depend on the ecommerce data, ensuring that they reflect the latest data. The refresh of the calculated insights and segments can be completed before the activations are scheduled to run, ensuring that the customer's scheduled campaign messages are accurate and relevant.

  The other options are not as good as option A. Option B is incorrect because setting a refresh schedule for the calculated insights to occur every hour may not be sufficient or efficient. The refresh schedule may not align with the activation schedule, resulting in outdated or inconsistent data. The refresh schedule may also consume more resources and time than necessary, as the ecommerce data may not change every hour. Option C is incorrect because ensuring the activations are set to Incremental Activation and automatically publish every hour may not solve the problem. Incremental Activation is a feature that allows only the new or changed records in a segment to be activated, reducing the activation time and size. However, this feature does not ensure that the segment data is updated or refreshed based on the ecommerce data. The activation schedule may also not match the ecommerce data update schedule, resulting in inaccurate or irrelevant campaign messages. Option D is incorrect because ensuring the segments are set to Rapid Publish and set to refresh every hour may not be optimal or effective. Rapid Publish is a feature that allows segments to be published faster by skipping some validation steps, such as checking for duplicate records or invalid values. However, this feature may compromise the quality or accuracy of the segment data, and may not be suitable for all use cases. The refresh schedule may also have the same issues as option B, as it may not sync with the ecommerce data update schedule or the activation schedule, resulting in outdated or inconsistent data. References: Salesforce Data Cloud Consultant uide, Flow, Change Data Events, Calculated Insights, Segments, [Activation]

• Question 55:

  Which permission setting should a consultant check if the custom Salesforce CRM object is not available in New Data Stream configuration?

  A. Confirm the Create object permission is enabled in the Data Cloud org.

  B. Confirm the View All object permission is enabled in the source Salesforce CRM org.

  C. Confirm the Ingest Object permission is enabled in the Salesforce CRM org.

  D. Confirm that the Modify Object permission is enabled in the Data Cloud org.

  Correct Answer: B

  To create a new data stream from a custom Salesforce CRM object, the consultant needs to confirm that the View All object permission is enabled in the source Salesforce CRM org. This permission allows the user to view all records associated with the object, regardless of sharing settings1. Without this permission, the custom object will not be available in the New Data Stream configuration.

  References: Manage Access with Data Cloud Permission Sets Object Permissions

• Question 56:

  Cumulus Financial wants to be able to track the daily transaction volume of each of its customers in real time and send out a notification as soon as it detects volume outside a customer's normal range.

  What should a consultant do to accommodate this request?

  A. Use a calculated insight paired with a flow.

  B. Use streaming data transform with a flow.

  C. Use a streaming insight paired with a data action

  D. Use streaming data transform combined with a data action.

  Correct Answer: C

  A streaming insight is a type of insight that analyzes streaming data in real time and triggers actions based on predefined conditions. A data action is a type of action that executes a flow, a data action target, or a data action script when an insight is triggered. By using a streaming insight paired with a data action, a consultant can accommodate Cumulus Financial's request to track the daily transaction volume of each customer and send out a notification when the volume is outside the normal range. A calculated insight is a type of insight that performs calculations on data in a data space and stores the results in a data extension. A streaming data transform is a type of data transform that applies transformations to streaming data in real time and stores the results in a data extension. A flow is a type of automation that executes a series of actions when triggered by an event, a schedule, or another flow. None of these options can achieve the same functionality as a streaming insight paired with a data action. References: Use Insights in Data Cloud Unit, Streaming Insights and Data Actions Use Cases, Streaming Insights and Data Actions Limits and Behaviors

• Question 57:

  Cumulus Financial uses Data Cloud to segment banking customers and activate them for direct mail via a Cloud File Storage activation. The company also wants to analyze individuals who have been in the segment within the last 2 years.

  Which Data Cloud component allows for this?

  A. Nested segments

  B. Segment exclusion

  C. Calculated insights

  D. Segment membership data model object

  Correct Answer: D

  The segment membership data model object is a Data Cloud component that allows for analyzing individuals who have been in a segment within a certain time period. The segment membership data model object is a table that stores the information about which individuals belong to which segments and when they were added or removed from the segments. This object can be used to create calculated insights, such as segment size, segment duration, segment overlap, or segment retention, that can help measure the effectiveness of segmentation and activation strategies. The segment membership data model object can also be used to create nested segments or segment exclusions based on the segment membership criteria, such as segment name, segment type, or segment date range. The other options are not correct because they are not Data Cloud components that allow for analyzing individuals who have been in a segment within the last 2 years. Nested segments and segment exclusions are features that allow for creating more complex segments based on existing segments, but they do not provide the historical data about segment membership. Calculated insights are custom metrics or measures that are derived from data model objects or data lake objects, but they do not store the segment membership information by themselves. References: Segment Membership Data Model Object, Create a Calculated Insight, Create a Nested Segment

• Question 58:

  What does the Source Sequence reconciliation rule do in identity resolution?

  A. Includes data from sources where the data is most frequently occurring

  B. Identifies which individual records should be merged into a unified profile by setting a priority for specific data sources

  C. Identifies which data sources should be used in the process of reconcillation by prioritizing the most recently updated data source

  D. Sets the priority of specific data sources when building attributes in a unified profile, such as a first or last name

  Correct Answer: D

  The Source Sequence reconciliation rule sets the priority of specific data sources when building attributes in a unified profile, such as a first or last name. This rule allows you to define which data source should be used as the primary source of truth for each attribute, and which data sources should be used as fallbacks in case the primary source is missing or invalid. For example, you can set the Source Sequence rule to use data from Salesforce CRM as the first priority, data from Marketing Cloud as the second priority, and data from Google Analytics as the third priority for the first name attribute. This way, the unified profile will use the first name value from Salesforce CRM if it exists, otherwise it will use the value from Marketing Cloud, and so on. This rule helps you to ensure the accuracy and consistency of the unified profile attributes across different data sources. References: Salesforce Data Cloud Consultant uide, Identity Resolution, Reconciliation Rules

• Question 59:

  How does identity resolution select attributes for unified individuals when there Is conflicting information in the data model?

  A. Creates additional contact points

  B. Leverages reconciliation rules

  C. Creates additional rulesets

  D. Leverages match rules

  Correct Answer: B

  Identity resolution is the process of creating unified profiles of individuals by matching and merging data from different sources. When there is conflicting information in the data model, such as different names, addresses, or phone numbers for the same person, identity resolution leverages reconciliation rules to select the most accurate and complete attributes for the unified profile. Reconciliation rules are configurable rules that define how to resolve conflicts based on criteria such as recency, frequency, source priority, or completeness. For example, a reconciliation rule can specify that the most recent name or the most frequent phone number should be selected for the unified profile. Reconciliation rules can be applied at the attribute level or the contact point level. References: Identity Resolution, Reconciliation Rules, Salesforce Data Cloud Exam Questions

• Question 60:

  The Salesforce CRM Connector is configured and the Case object data stream is set up. Subsequently, a new custom field named Business Priority is created on the Case object in Salesforce CRM. However, the new field is not available when trying to add it to the data stream.

  Which statement addresses the cause of this issue?

  A. The Salesforce Integration User Is missing Rad permissions on the newly created field.

  B. The Salesforce Data Loader application should be used to perform a bulk upload from a desktop.

  C. Custom fields on the Case object are not supported for ingesting into Data Cloud.

  D. After 24 hours when the data stream refreshes it will automatically include any new fields that were added to the Salesforce CRM.

  Correct Answer: A

  The Salesforce CRM Connector uses the Salesforce Integration User to access the data from the Salesforce CRM org. The Integration User must have the Read permission on the fields that are included in the data stream. If the Integration User does not have the Read permission on the newly created field, the field will not be available for selection in the data stream configuration. To resolve this issue, the administrator should assign the Read permission on the new field to the Integration User profile or permission set. References: Create a Salesforce CRM Data Stream, Edit a Data Stream, Salesforce Data Cloud Full Refresh for CRM, SFMC, or Ingestion API Data Streams