Salesforce Data Cloud Data-Cloud-Consultant Dumps | Updated Mar 02, 2024 - Lead1Pass
Master 2024 Latest The Questions Salesforce Data Cloud and Pass Data-Cloud-Consultant Real Exam!
NEW QUESTION # 26
A customer has a custom Customer Email c object related to the standard Contact object in Salesforce CRM.
This custom object
stores the email addressa Contact that they want to use for activation.
To which data entity ismapped?
- A. Contact
- B. Contact Point_Email
- C. Individual
- D. Custom customer Email__c object
Answer: B
Explanation:
Explanation
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:
* A. 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.
* C. 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.
* D. 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]
NEW QUESTION # 27
A customer is trying to activate data from Data Cloud to an Amazon S3 Cloud File Storage Bucket.
Which authentication type should the consultant recommend to connect to the S3 bucket from Data Cloud?
- A. Use a JWT Token generated on S3.
- B. Use an S3 Encrypted Username and Password.
- C. Use an S3 Private Key Certificate.
- D. Use an S3 Access Key and Secret Key.
Answer: D
Explanation:
Explanation
To use the Amazon S3 Storage Connector in Data Cloud, the consultant needs to provide the S3 bucket name, region, and access key and secret key for authentication. The access key and secret key are generated by AWS and can be managed in the IAM console. The other options are not supported by the S3 Storage Connector or by Data Cloud. References: Amazon S3 Storage Connector - Salesforce, How to Use the Amazon S3 Storage Connector in Data Cloud | Salesforce Developers Blog Learn more 1blob:https://www.bing.com/fed40cd6-30db-497b-a587-44e59b9e1f0bhelp.salesforce.com2blob:https://www.bin
NEW QUESTION # 28
A customer has outlined requirements to trigger a journey for an abandoned browse behavior. Based on the requirements, the consultant determines they will use streaming insights to trigger a data action to Journey Builder every hour.
How should the consultant configure the solution to ensure the data action is triggered at the cadence required?
- A. Configure the data to be ingested in hourly batches.
- B. Set the activation schedule to hourly.
- C. Set the journey entry schedule to run every hour.
- D. Set the insights aggregation time window to 1 hour.
Answer: D
Explanation:
Explanation
Streaming insights are computed from real-time engagement events and can be used to trigger data actions based on pre-set rules. Data actions are workflows that send data from Data Cloud to other systems, such as Journey Builder. To ensure that the data action is triggered every hour, the consultant should set the insights aggregation time window to 1 hour. This means that the streaming insight will evaluate the events that occurred within the last hour and execute the data action if the conditions are met. The other options are not relevant for streaming insights and data actions. References: Streaming Insights and Data Actions Limits and Behaviors, Streaming Insights, Streaming Insights and Data Actions Use Cases, Use Insights in Data Cloud, 6 Ways the Latest Marketing Cloud Release Can Boost Your Campaigns
NEW QUESTION # 29
A Data Cloud consultant recently discovered that their identity resolution process is matching individuals that share email addresses or phone numbers, but are not actually the same individual.
What should the consultant do to address this issue?
- A. Create and run a new rules fewer matching rules, compare the two rulesets to review and verify the results, and then migrate to the new ruleset once approved.
- B. Create and run a new ruleset with stricter matching criteria, compare the two rulesets to review and verify the results, and then migrate to the new ruleset once approved.
- C. Modify the existing ruleset with stricter matching criteria, run the ruleset and review the updated results, then adjust as needed until the individuals are matching correctly.
- D. Modify the existing ruleset with stricter matching criteria, compare the two rulesets to review and verify the results, and then migrate to the new ruleset once approved.
Answer: B
Explanation:
Explanation
Identity resolution is the process of linking source profiles from different data sources into unified individual profiles based on match and reconciliation rules. If the identity resolution process is matching individuals that share email addresses or phone numbers, but are not actually the same individual, it means that the match rules are too loose and need to be refined. The best way to address this issue is to create and run a new ruleset with stricter matching criteria, such as adding more attributes or increasing the match score threshold. Then, the consultant can compare the two rulesets to review and verify the results, and see if the new ruleset reduces the false positives and improves the accuracy of the identity resolution. Once the new ruleset is approved, the consultant can migrate to the new ruleset and delete the old one. The other options are incorrect because modifying the existing ruleset can affect the existing unified profiles and cause data loss or inconsistency.
Creating and running a new ruleset with fewer matching rules can increase the false negatives and reduce the coverage of the identity resolution. References: Create Unified Individual Profiles, AI-based Identity Resolution: Linking Diverse Customer Data, Data Cloud Identiy Resolution.
NEW QUESTION # 30
Which data model subject area defines the revenue or quantity for an opportunity by product family?
- A. Engagement
- B. Product
- C. Party
- D. Sales Order
Answer: D
Explanation:
Explanation
The Sales Order subject area defines the details of an order placed by a customer for one or more products or services. It includes information such as the order date, status, amount, quantity, currency, payment method, and delivery method. The Sales Order subject area also allows you to track the revenue or quantity for an opportunity by product family, which is a grouping of products that share common characteristics or features.
For example, you can use the Sales Order Line Item DMO to associate each product in an order with its product family, and then use the Sales Order Revenue DMO to calculate the total revenue or quantity for each product family in an opportunity. References: Sales Order Subject Area, Sales Order Revenue DMO Reference
NEW QUESTION # 31
Northern Trail Outfitters is using the Marketing Cloud Starter Data Bundles to bring Marketing Cloud data into Data Cloud.
What are two of the available datasets in Marketing Cloud Starter Data Bundles?
Choose 2 answers
- A. Personalization
- B. Loyalty Management
- C. MobilePush
- D. MobileConnect
Answer: C,D
Explanation:
Explanation
The Marketing Cloud Starter Data Bundles are predefined data bundles that allow you to easily ingest data from Marketing Cloud into Data Cloud1. The available datasets in Marketing Cloud Starter Data Bundles are Email, MobileConnect, and MobilePush2. These datasets contain engagement events and metrics from different Marketing Cloud channels, such as email, SMS, and push notifications2. By using these datasets, you can enrich your Data Cloud data model with Marketing Cloud data and create segments and activations based on your marketing campaigns and journeys1. The other options are incorrect because they are not available datasets in Marketing Cloud Starter Data Bundles. Option A is incorrect because Personalization is not a dataset, but a feature of Marketing Cloud that allows you to tailor your content and messages to your audience3. Option C is incorrect because Loyalty Management is not a dataset, but a product of Marketing Cloud that allows you to create and manage loyaltyprograms for your customers4. References: Marketing Cloud Starter Data Bundles in Data Cloud, Connect Your Data Sources, Personalization in Marketing Cloud, Loyalty Management in Marketing Cloud
NEW QUESTION # 32
Cumulus Financial wants to segregate Salesforce CRM Account data based on Country for its Data Cloud users.
What should the consultant do to accomplish this?
- A. Use formula fields based on the account Country field to filter incoming records.
- B. Use streaming transforms to filter out Account data based on Country and map to separate data model objects accordingly.
- C. Use the data spaces feature and applying filtering on the Account data lake object based on Country.
- D. Use Salesforce sharing rules on the Account object to filter and segregate records based on Country.
Answer: C
Explanation:
Explanation
Data spaces are a feature that allows Data Cloud users to create subsets of data based on filters and permissions. Data spaces can be used to segregate data based on different criteria, such as geography, business unit, or product line. In this case, the consultant can use the dataspaces feature and apply filtering on the Account data lake object based on Country. This way, the Data Cloud users can access only the Account data that belongs to their respective countries. References: Data Spaces, Create a Data Space
NEW QUESTION # 33
Which two common use cases can be addressed with Data Cloud?
Choose 2 answers
- A. Govern enterprise data lifecycle through a centralized set of policies and processes.
- B. Harmonize data from multiple sources with a standardized and extendable data model.
- C. Safeguard critical business data by serving as a centralized system for backup and disaster recovery.
- D. Understand and act upon customer data to drive more relevant experiences.
Answer: B,D
Explanation:
Explanation
Data Cloud is a data platform that can help customers connect, prepare, harmonize, unify, query, analyze, and act on their data across various Salesforce and external sources. Some of the common use cases that can be addressed with Data Cloud are:
* Understand and act upon customer data to drive more relevant experiences. Data Cloud can help customers gain a 360-degree view of their customers by unifying data from different sources and resolving identities across channels. Data Cloud can also help customers segment their audiences, create personalized experiences, and activate data in any channel using insights and AI.
* Harmonize data from multiple sources with a standardized and extendable data model. Data Cloud can help customers transform and cleanse their data before using it, and map it to a common data model that can be extended and customized. Data Cloud can also help customers create calculated insights and related attributes to enrich their data and optimize identity resolution.
The other two options are not common use cases for Data Cloud. Data Cloud does not provide data governance or backup and disaster recovery features, as these are typically handled by other Salesforce or external solutions.
References:
* Learn How Data Cloud Works
* About Salesforce Data Cloud
* Discover Use Cases for the Platform
* Understand Common Data Analysis Use Cases
NEW QUESTION # 34
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 activated profiles have a Unified Contact Point.
- B. The activations are referencing segments that segment on profile data rather than engagement data.
- C. The related engagement events occurred within the last 90 days.
- D. The correct path is selected for the related attributes.
Answer: C,D
Explanation:
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. References: Add Related Attributes to an Activation, Related Attributes in Data Cloud activation have no values, Explore the Engagement Data Model Object
NEW QUESTION # 35
Which data stream category should be assigned to use the data for time-based operations in segmentation and calculated insights?
- A. Engagement
- B. Sales Order
- C. Transaction
- D. Individual
Answer: C
Explanation:
Explanation
Data streams are the sources of data that are ingested into Data Cloud and mapped to the data model. Data streams have different categories that determine how the data is processed and used in Data Cloud.
Transaction data streams are used for time-based operations in segmentation and calculated insights, such as filtering by date range, aggregating by time period, or calculating time-to-event metrics. Transaction data streams are typically used forevent data, such as purchases, clicks, or visits, that have a timestamp and a value associated with them. References: Data Streams, Data Stream Categories
NEW QUESTION # 36
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. Streaming insights
- D. Related attributes
- E. Calculated Insights
Answer: A,D,E
Explanation:
Explanation
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
NEW QUESTION # 37
A customer has a requirement to be able to view the last time each segment was published within their Data Cloud org.
Which two features should the consultant recommend to best address this requirement?
Choose 2 answers
- A. Profile Explorer
- B. Report
- C. Calculated insight
- D. Dashboard
Answer: B,D
Explanation:
Explanation
A customer who wants to view the last time each segment was published within their Data Cloud org can use the dashboard and report features to achieve this requirement. A dashboard is a visual representation of data that can show key metrics, trends, and comparisons. A report is a tabular or matrix view of data that can show details, summaries, and calculations. Both dashboard and report features allow the user to create, customize, and share data views based on their needs and preferences. To view the last time each segment was published, the user can create a dashboard or a report that shows the segment name, the publish date, and the publish status fields from the segment object. The user can also filter, sort, group, or chart the data by these fields to get more insights and analysis. The user can also schedule, refresh, or export the dashboard or report data as needed. References: Dashboards, Reports
NEW QUESTION # 38
What should an organization use to stream inventory levels from an inventory management system into Data Cloud in a fast and scalable, near-real-time way?
- A. Ingestion API
- B. Cloud Storage Connector
- C. Marketing Cloud Personalization Connector
- D. Commerce Cloud Connector
Answer: A
Explanation:
Explanation
The Ingestion API is a RESTful API that allows you to stream data from any source into Data Cloud in a fast and scalable way. You can use the Ingestion API to send data from your inventory management system into Data Cloud as JSON objects, and then use Data Cloud to create data models, segments, and insights based on your inventory data. The Ingestion API supports both batch and streaming modes, and can handle up to
100,000 records per second. The Ingestion API also provides features such as data validation, encryption, compression, and retry mechanisms to ensure data quality and security. References: Ingestion API Developer Guide, Ingest Data into Data Cloud
NEW QUESTION # 39
Which method should a consultant use when performing aggregations in windows of 15 minutes on data collected via the Interaction SDK or Mobile SDK?
- A. Streaming insight
- B. Batch transform
- C. Calculated insight
- D. Formula fields
Answer: A
Explanation:
Explanation
Streaming insight is a method that allows you to perform aggregations in windows of 15 minutes on data collected via the Interaction SDK or Mobile SDK. Streaming insight is a feature that enables you to create real-time metrics and insights based on streaming data from various sources, such as web, mobile, or IoT devices. Streaming insight allows you to define aggregation rules, such as count, sum, average, min, max, or percentile, and apply them to streaming data in time windows of 15 minutes. For example, you can use streaming insight to calculate the number of visitors, the average session duration, or the conversion rate for your website or app in 15-minute intervals. Streaming insight also allows you to visualize and explore the aggregated data in dashboards, charts, or tables. References: Streaming Insight, Create Streaming Insights
NEW QUESTION # 40
During a privacy law discussion with a customer, the customer indicates they need to honor requests for the right to be forgotten. The consultant determines that Consent API will solve this business need.
Which two considerations should the consultant inform the customer about?
Choose 2 answers
- A. Data deletion requests submitted to Data Cloud are passed to all connected Salesforce clouds.
- B. Data deletion requests are submitted for Individual profiles.
- C. Data deletion requests are reprocessed at 30, 60, and 90 days.
- D. Data deletion requests are processed within 1 hour.
Answer: A,B
Explanation:
Explanation
When advising a customer about using the Consent API in Salesforce to comply with requests for the right to be forgotten, the consultant should focus on two primary considerations:
* Data deletion requests are submitted for Individual profiles (Answer C): The Consent API in Salesforce is designed to handle data deletion requests specifically for individual profiles. This means that when a request is made to delete data, it is targeted at the personal data associated with an individual's profile in the Salesforce system. The consultant should inform the customer that the requests must be specific to individual profiles to ensure accurate processing and compliance with privacy laws.
* Data deletion requests submitted to Data Cloud are passed to all connected Salesforce clouds (Answer D): When a data deletion request is made through the Consent API in Salesforce Data Cloud, the request is not limited to the Data Cloud alone. Instead, it propagates through all connected Salesforce clouds, such as Sales Cloud, Service Cloud, Marketing Cloud, etc. This ensures comprehensive compliance with the right to be forgotten across the entire Salesforce ecosystem. The customer should be aware that the deletion request will affect all instances of the individual's data across the connected Salesforce environments.
NEW QUESTION # 41
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. Map name to the Individual object and email address to the Contact Phone Email object.
- B. Map all fields to the Individual object, adding a custom field for the email address.
- C. Map all fields to the Customer object.
- D. Create a new custom object with fields that directly match the incoming table.
Answer: A
Explanation:
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
NEW QUESTION # 42
How does Data Cloud handle an individual's Right to be Forgotten?
- A. Deletes the records from all data source objects, and any downstream data model objects are updated at the next scheduled ingestion
- B. Deletes the specified Individual record and its Unified Individual Link record.
- C. Deletes the specified Individual and records from any data model object/data lake object related to the Individual.
- D. Deletes the specified Individual and records from any data source object mapped to the Individual data model object.
Answer: C
Explanation:
Explanation
Data Cloud handles an individual's Right to be Forgotten by deleting the specified Individual and records from any data model object/data lake object related to the Individual. This means that Data Cloud removes all the data associated with the individual from the data space, including the data from the source objects, the unified individual profile, and any related objects. Data Cloud also deletes the Unified Individual Link record that links the individual to the source records. Data Cloud uses the Consent API to process the Right to be Forgotten requests, which are reprocessed at 30, 60, and 90 days to ensure a full deletion.
The other options are not correct descriptions of how Data Cloud handles an individual's Right to be Forgotten. Data Cloud does not delete the records from all data source objects, as this would affect the data integrity and availability of the source systems. Data Cloud also does not delete only the specified Individual record and its Unified Individual Link record, as this would leave the source records and the related records intact. Data Cloud also does not delete only the specified Individual and records from any data source object mapped to the Individual data model object, as this would leave the related records intact.
References:
* Requesting Data Deletion or Right to Be Forgotten
* Data Deletion for Data Cloud
* Use the Consent API with Data Cloud
* Data and Identity in Data Cloud
NEW QUESTION # 43
Cloud Kicks received a Request to be Forgotten by a customer.
In which two ways should a consultant use Data Cloud to honor this request?
Choose 2 answers
- A. Use Data Explorer to locate and manually remove the Individual.
- B. Add the Individual ID to a headerless file and use the delete from file functionality.
- C. Use the Consent API to suppress processing and delete the Individual and related records from source data streams.
- D. Delete the data from the incoming data stream and perform a full refresh.
Answer: B,C
Explanation:
Explanation
To honor a Request to be Forgotten by a customer, a consultant should use Data Cloud in two ways:
* Add the Individual ID to a headerless file and use the delete from file functionality. This option allows the consultant to delete multiple Individuals from Data Cloud by uploading a CSV file with their IDs1. The deletion process is asynchronous and can take up to 24 hours to complete1.
* Use the Consent API to suppress processing and delete the Individual and related records from source data streams. This option allows the consultant to submit a Data Deletion request for an Individual profile in Data Cloud using the Consent API2. A Data Deletion request deletes the specified Individual entity and any entities where a relationship has been defined between that entity's identifying attribute and the Individual ID attribute2. The deletion process is reprocessed at 30, 60, and 90 days to ensure a full deletion2. The other options are not correct because:
* Deleting the data from the incoming data stream and performing a full refresh will not delete the existing data in Data Cloud, only the new data from the source system3.
* Using Data Explorer to locate and manually remove the Individual will not delete the related records from the source data streams, only the Individual entity in Data Cloud. References:
* Delete Individuals from Data Cloud
* Requesting Data Deletion or Right to Be Forgotten
* Data Refresh for Data Cloud
* [Data Explorer]
NEW QUESTION # 44
Cumulus Financial wants to be able to track the daily transaction volume of each of its customers in real time and send out anotification as soon as it detects volume outside a customer's normal range.
What should a consultant do to accommodate this request?
- A. Use streaming data transform combined with a data action.
- B. Use streaming data transform with a flow.
- C. Use a streaming insight paired with a data action
- D. Use a calculated insight paired with a flow.
Answer: C
Explanation:
Explanation
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
NEW QUESTION # 45
A consultant has an activation that is set to publish every 12 hours, but has discovered that updates to the data prior to activation are delayed by up to 24 hours.
Which two areas should a consultant review to troubleshoot this issue?
Choose 2 answers
- A. Review segments to ensure they're refreshed after the data is ingested.
- B. Review calculated insights to make sure they're run before segments are refreshed.
- C. Review data transformations to ensure they're run after calculated insights.
- D. Review calculated insights to make sure they're run after the segments are refreshed.
Answer: A,B
Explanation:
Explanation
The correct answer is B and C because calculated insights and segments are both dependent on the data ingestion process. Calculated insights are derived from the data model objects and segments are subsets of data model objects that meet certain criteria. Therefore, both of them need to be updated after the data is ingested to reflect the latest changes. Data transformations are optional steps that can be applied to the data streams before they are mapped to the data model objects, so they are not relevant to the issue. Reviewing calculated insights to make sure they're run after the segments are refreshed (option D) is also incorrect because calculated insights are independent of segments and do not need to be refreshed after them. References: Salesforce Data Cloud Consultant Exam Guide, Data Ingestion and Modeling, Calculated Insights, Segments
NEW QUESTION # 46
A consultant is helping a beauty company ingest its profile data into Data Cloud. The company's source data includes several fields, such as eye color, skin type, and hair color, that are not fields in the standardIndividual data model object (DMO).
What should the consultant recommend to map this data to be used for both segmentation and identity resolution?
- A. Create a custom DMO with only the additional fields and map it to the standard Individual DMO.
- B. Create custom fields on the standard Individual DMO.
- C. Duplicate the standard Individual DMO and add the additional fields.
- D. Create a custom DMO from scratch that has all fields that are needed.
Answer: B
Explanation:
Explanation
The best option to map the data to be used for both segmentation and identity resolution is to create custom fields on the standard Individual DMO. This way, the consultant can leverage the existing fields and functionality of the Individual DMO, such as identity resolution rulesets, calculated insights, and data actions, while adding the additional fields that are specific to the beauty company's data1. Creating a custom DMO from scratch or duplicating the standard Individual DMO would require more effort and maintenance, and might not be compatible with the existing features of Data Cloud. Creating a custom DMO with only the additional fields and mapping it to the standard Individual DMO would create unnecessary complexity and redundancy, and might not allow the use of the custom fields for identity resolution. References:
* 1: Data Model Objects in Data Cloud
NEW QUESTION # 47
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