Salesforce Data-Cloud-Consultant最新問題集[2025]高得点を掴み取れ [Q96-Q119]

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Salesforce Data-Cloud-Consultant最新問題集[2025]高得点を掴み取れ

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Salesforce Data-Cloud-Consultant 認定試験の出題範囲:

トピック出題範囲
トピック 1
  • Data Cloud Setup and Administration: This topic includes applying Data Cloud permissions, permission sets, org-wide settings. It describes and configures data stream types, and data bundles. Moreover, it discusses use cases for data spaces, creating data spaces, managing and administering Data Cloud using reports, dashboards, flows, packaging, data kits, diagnosing and exploring data using Data Explorer, Profile Explorer, and APIs.
トピック 2
  • Data Ingestion and Modeling: This topic covers the different transformation capabilities within Data Cloud. It includes describing processes and considerations for data ingestion from various sources, defining, mapping, and modeling data using best practices aligned with identity resolution. Lastly, it discusses using available tools to inspect and validate ingested and modeled data.
トピック 3
  • Segmentation and Insights: This topic defines basic concepts of segmentation and use cases, identifies scenarios for analyzing segment membership, configuring, refining, and maintaining segments within Data Cloud, and differentiating between calculated and streaming insights.

 

質問 # 96
A consultant is planning the ingestion of a data stream that has profile information including a mobile phone number.
To ensure that the phone number can be used for future SMS campaigns, they need to confirm the phone number field is in the proper E164 Phone Number format. However, the phone numbers in the file appear to be in varying formats.
What is the most efficient way to guarantee that the various phone number formats are standardized?

  • A. Create a calculated insight after ingestion.
  • B. Create a formula field to standardize the format.
  • C. Edit and update the data in the source system prior to sending to Data Cloud.
  • D. Assign the PhoneNumber field type when creating the data stream.

正解:D

解説:
The most efficient way to guarantee that the various phone number formats are standardized is to assign the PhoneNumber field type when creating the data stream. The PhoneNumber field type is a special field type that automatically converts phone numbers into the E164 format, which is the international standard for phone numbers. The E164 format consists of a plus sign (+), the country code, and the national number. For example,
+1-202-555-1234 is the E164 format for a US phone number. By using the PhoneNumber field type, the consultant can ensure that the phone numbers are consistent and can be used for future SMS campaigns. The other options are either more time-consuming, require manual intervention, or do not address the formatting issue. References: Data Stream Field Types, E164 Phone Number Format, Salesforce Data Cloud Exam Questions


質問 # 97
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. Nested segments
  • B. Flow Orchestration
  • C. Streaming data transform
  • D. Metrics on metrics

正解:D

解説:
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. Reference: Metrics on Metrics, Create Metrics on Metrics


質問 # 98
A customer requests that their personal data be deleted.
Which action should the consultant take to accommodate this request in Data Cloud?

  • A. Use Consent API to request deletion of the customer's information.
  • B. Use Profile Explorer to delete the customer data from Data Cloud.
  • C. Use the Data Rights Subject Request tool to request deletion of the customer's information.
  • D. Use a streaming API call to delete the customer's information.

正解:C


質問 # 99
A user has built a segment in Data Cloud and is in the process of creating an activation. When selecting related attributes, they cannot find a specific set of attributes they know to be related to the individual.
Which statement explains why these attributes are not available?

  • A. The attributes are being used in another activation.
  • B. The segment is not segmenting on profile data.
  • C. The desired attributes reside on different related paths.
  • D. Activations can only include 1-to-1 attributes.

正解:C

解説:
The correct answer is C, the desired attributes reside on different related paths. When creating an activation in Data Cloud, you can select related attributes from data model objects that are linked to the segment entity. However, not all related attributes are available for every activation. The availability of related attributes depends on the container path, which is the sequence of data model objects that connects the segment entity to the related entity. For example, if you segment on the Unified Individual entity, you can select related attributes from the Order Product entity, but only if the container path is Unified Individual > Order > Order Product. If the container path is Unified Individual > Order Line Item > Order Product, then the related attributes from Order Product are not available for activation. This is because Data Cloud only supports one-to-many relationships for related attributes, and Order Line Item is a many-to-many junction object between Order and Order Product. Therefore, you need to ensure that the desired attributes reside on the same related path as the segment entity, and that the path does not include any many-to-many junction objects. The other options are incorrect because they do not explain why the related attributes are not available. The segment entity can be any data model object, not just profile data. The attributes are not restricted by being used in another activation. Activations can include one-to-many attributes, not just one-to-one attributes. Reference:
Related Attributes in Activation
Considerations for Selecting Related Attributes
Salesforce Launches: Data Cloud Consultant Certification
Create a Segment in Data Cloud


質問 # 100
A segment fails to refresh with the error "Segment references too many data lake objects (DLOS)".
Which two troubleshooting tips should help remedy this issue?
Choose 2 answers

  • A. Space out the segment schedules to reduce DLO load.
  • B. Split the segment into smaller segments.
  • C. Refine segmentation criteria to limit up to five custom data model objects (DMOs).
  • D. Use calculated insights in order to reduce the complexity of the segmentation query.

正解:B、D

解説:
The error "Segment references too many data lake objects (DLOs)" occurs when a segment query exceeds the limit of 50 DLOs that can be referenced in a single query. This can happen when the segment has too many filters, nested segments, or exclusion criteria that involve different DLOs. To remedy this issue, the consultant can try the following troubleshooting tips:
* Split the segment into smaller segments. The consultant can divide the segment into multiple segments that have fewer filters, nested segments, or exclusion criteria. This can reduce the number of DLOs that are referenced in each segment query and avoid the error. The consultant can then use the smaller segments as nested segments in a larger segment, or activate them separately.
* Use calculated insights in order to reduce the complexity of the segmentation query. The consultant can create calculated insights that are derived from existing data using formulas. Calculated insights can simplify the segmentation query by replacing multiple filters or nested segments with a single attribute.
For example, instead of using multiple filters to segment individuals based on their purchase history, the consultant can create a calculated insight that calculates the lifetime value of each individual and use that as a filter.
The other options are not troubleshooting tips that can help remedy this issue. Refining segmentation criteria to limit up to five custom data model objects (DMOs) is not a valid option, as the limit of 50 DLOs applies to both standard and custom DMOs. Spacing out the segment schedules to reduce DLO load is not a valid option, as the error is not related to the DLO load, but to the segment query complexity.
References:
* Troubleshoot Segment Errors
* Create a Calculated Insight
* Create a Segment in Data Cloud


質問 # 101
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. Cloud Storage Connector
  • B. Ingestion API
  • C. Commerce Cloud Connector
  • D. Marketing Cloud Personalization Connector

正解:B

解説:
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


質問 # 102
A Data Cloud customer wants to adjust their identity resolution rules to increase their accuracy of matches. Rather than matching on email address, they want to review a rule that joins their CRM Contacts with their Marketing Contacts, where both use the CRM ID as their primary key.
Which two steps should the consultant take to address this new use case?
Choose 2 answers

  • A. Create a custom matching rule for an exact match on the Individual ID attribute.
  • B. Map the primary key from the two systems to Party Identification, using CRM ID as the identification name for both.
  • C. Map the primary key from the two systems to party identification, using CRM ID as the identification name for individuals coming from the CRM, and Marketing ID as the identification name for individuals coming from the marketing platform.
  • D. Create a matching rule based on party identification that matches on CRM ID as the party identification name.

正解:B、D

解説:
To address this new use case, the consultant should map the primary key from the two systems to Party Identification, using CRM ID as the identification name for both, and create a matching rule based on party identification that matches on CRM ID as the party identification name. This way, the consultant can ensure that the CRM Contacts and Marketing Contacts are matched based on their CRM ID, which is a unique identifier for each individual. By using Party Identification, the consultant can also leverage the benefits of this attribute, such as being able to match across different entities and sources, and being able to handle multiple values for the same individual. The other options are incorrect because they either do not use the CRM ID as the primary key, or they do not use Party Identification as the attribute type. References: Configure Identity Resolution Rulesets, Identity Resolution Match Rules, Data Cloud Identity Resolution Ruleset, Data Cloud Identity Resolution Config Input


質問 # 103
Which tool allows users to visualize and analyze unified customer data in Data Cloud?

  • A. Tableau
  • B. Salesforce CLI
  • C. Heroku
  • D. Einstein Analytics

正解:A

解説:
* Salesforce Data Cloud Overview: Salesforce Data Cloud enables organizations to unify and manage customer data from multiple sources, providing a comprehensive view of customer interactions and behaviors.
* Visualization and Analysis: For visualizing and analyzing this unified data, Salesforce provides multiple tools, each serving different purposes. Tableau is particularly noted for its advanced analytics and visualization capabilities.
* Tableau Integration: Tableau is integrated with Salesforce, allowing users to create detailed and interactive visualizations. It can connect directly to Salesforce Data Cloud, pulling in unified data for comprehensive analysis.
* Capabilities: Tableau supports a wide range of data sources and formats, offering drag-and-drop features to create complex charts and dashboards. This makes it an ideal tool for analyzing the rich datasets managed within Salesforce Data Cloud.
* Reference:
Salesforce Help: Tableau Integration
Salesforce Data Cloud Overview


質問 # 104
A user Is not seeing suggested values from newly-modeled data when building a segment.
What is causing this issue?

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

正解:A

解説:
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 feature1. 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


質問 # 105
How should a Data Cloud consultant successfully apply consent during segmentation?

  • A. Include the Consent Status from the golden record during activation for any applicable channels of engagement.
  • B. Include the Unified Profile during segmentation for any applicable channels of engagement.
  • C. Include Party Identification for any applicable channels of engagement in the filter criteria for each segment.
  • D. Include the Consent Status for any applicable channels of engagement in the filter criteria for each segment.

正解:D

解説:
* Understanding Consent Management in Salesforce Data Cloud:
Consent management is crucial for maintaining compliance with data protection regulations like GDPR and CCPA. It ensures that customer data is used in accordance with their given permissions.
Reference:
* Role of Consent Status in Segmentation:
The Consent Status indicates whether a customer has agreed or opted-in to specific types of communication or data processing activities.
During segmentation, applying the correct consent status ensures that only those customers who have provided the necessary permissions are included in targeted campaigns.
* Implementation of Consent Status in Segmentation:
When creating segments, including the Consent Status in the filter criteria helps to dynamically segment the audience based on their consent preferences.
This ensures compliance and improves the relevance and personalization of communications.
Example: If creating a marketing campaign for email outreach, the segment would only include customers who have a consent status allowing email communication.
* Practical Application:
Go to the segmentation tool within Salesforce Data Cloud.
In the filter criteria, add the Consent Status attribute relevant to the channel of engagement.
Define the values (e.g., Opted-in, Subscribed) to ensure only compliant customer profiles are included.


質問 # 106
Which two dependencies need to be removed prior to disconnecting a data source?
Choose 2 answers

  • A. Activation
  • B. Activation target
  • C. Data stream
  • D. Segment

正解:C、D

解説:
* Dependencies in Data Cloud:
Before disconnecting a data source, all dependencies must be removed to prevent data integrity issues.
Reference:
* Identifying Dependencies:
Segment: Segments using data from the source must be deleted or reassigned.
Data Stream: The data stream must be disconnected, as it directly relies on the data source.
* Steps to Remove Dependencies:
Remove Segments:
Navigate to the Segmentation interface in Salesforce Data Cloud.
Identify and delete segments relying on the data source.
Disconnect Data Stream:
Go to the Data Stream settings.
Locate and disconnect the data stream associated with the source.
* Practical Application:
Example: When preparing to disconnect a legacy CRM system, ensure all segments and data streams using its data are properly removed or migrated.


質問 # 107
Cumulus Financial needs to create a composite key on an incoming data source that combines the fields Customer Region and Customer Identifier.
Which formula function should a consultant use to create a composite key when a primary key is not available in a data stream?

  • A. CONCAT
  • B. CAST
  • C. COMBIN
  • D. COALE

正解:A

解説:
* Composite Keys in Data Streams: When working with data streams in Salesforce Data Cloud, there may be situations where a primary key is not available. In such cases, creating a composite key from multiple fields ensures unique identification of records.
* Formula Functions: Salesforce provides several formula functions to manipulate and combine data fields. Among them, the CONCAT function is used to combine multiple strings into one.
* Creating Composite Keys: To create a composite key using CONCAT, a consultant can combine the values of Customer Region and Customer Identifier into a single unique identifier.
Example Formula: CONCAT(Customer_Region, Customer_Identifier)
* Reference:
Salesforce Documentation: Formula Functions
Salesforce Data Cloud Guide


質問 # 108
Northern Trail Outfitters (NTD) creates a calculated insight to computerecency, frequency, monetary {RFM) scores on its unified individuals. NTO then creates a segment based on these scores that it activates to a Marketing Cloud activation target.
Which two actions are required when configuring the activation?
Choose 2 answers

  • A. Select contact points.
  • B. Add additional attributes.
  • C. Add the calculated insight in the activation.
  • D. Choose a segment.

正解:A、D

解説:
Explanation
To configure an activation to a Marketing Cloud activation target, you need to choose a segment and select contact points. Choosing a segment allows you to specify which unified individuals you want to activate.
Selecting contact points allows you to map the attributes from the segment to the fields in the Marketing Cloud data extension. You do not need to add additional attributes or add the calculated insight in the activation, as these are already part of the segment definition. References: Create a Marketing Cloud Activation Target; Types of Data Targets in Data Cloud


質問 # 109
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 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.
  • D. The B2C Commerce Order Bundle ingests 6 months of historical data.

正解:C

解説:
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 file12. References:
* Create a B2C Commerce Data Bundle
* Data Access and Export for B2C Commerce and Commerce Marketplace


質問 # 110
A user wants to be able to create a multi-dimensional metric to identify unified individual lifetime value (LTV).
Which sequence of data model object (DMO) joins is necessary within the calculated Insight to enable this calculation?

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

正解:B

解説:
Explanation
To create a multi-dimensional metric to identify unified individual lifetime value (LTV), the sequence of data model object (DMO) joins that is necessary within the calculated Insight is Unified Individual > Unified Link Individual > Sales Order. This is because the Unified Individual DMO represents the unified profile of an individual or entity that is created by identity resolution1. The Unified Link Individual DMO represents the link between a unified individual and an individual from a source system2. The Sales Order DMO represents the sales order information from a source system3. By joining these three DMOs, you can calculate the LTV of a unified individual based on the sales order data from different source systems. The other options are incorrect because they do not join the correct DMOs to enable the LTV calculation. Option B is incorrect because the Individual DMO represents the source profile of an individual or entity from a source system, not the unified profile4. Option C is incorrect because the join order is reversed, and you need to start with the Unified Individual DMO to identify the unified profile. Option D is incorrect because it is missing the Unified Link Individual DMO, which is needed to link the unified profile with the source profile. References: Unified Individual Data Model Object, Unified Link Individual Data Model Object, Sales Order Data Model Object, Individual Data Model Object


質問 # 111
An organization wants to enable users with the ability to identify and select text attributes from a picklist of options.
Which Data Cloud feature should help with this use case?

  • A. Global picklists
  • B. Data harmonization
  • C. Transformation formulas
  • D. Value suggestion

正解:D

解説:
Value suggestion is a Data Cloud feature that allows users to see and select the possible values for a text field when creating segment filters. Value suggestion can be enabled or disabled for each data model object (DMO) field in the DMO record home. Value suggestion can help users to identify and select text attributes from a picklist of options, without having to type or remember the exact values. Value suggestion can also reduce errors and improve data quality by ensuring consistent and valid values for the segment filters. Reference: Use Value Suggestions in Segmentation, Considerations for Selecting Related Attributes


質問 # 112
What is the role of artificial intelligence (AI) in Data Cloud?

  • A. Generating email templates for use cases
  • B. Automating data validation
  • C. Creating dynamic data-driven management dashboards
  • D. Enhancing customer interactions through insights and predictions

正解:D

解説:
* Role of AI in Data Cloud: Artificial intelligence (AI) plays a crucial role in Salesforce Data Cloud by leveraging data to generate insights and predictions that enhance customer interactions.
* Insights and Predictions:
AI Algorithms: Use machine learning algorithms to analyze vast amounts of customer data.
Predictive Analytics: Provide predictive insights, such as customer behavior trends, preferences, and potential future actions.
* Enhancing Customer Interactions:
Personalization: AI helps in creating personalized experiences by predicting customer needs and preferences.
Efficiency: Enables proactive customer service by predicting issues and suggesting solutions before customers reach out.
Marketing: Improves targeting and segmentation, ensuring that marketing efforts are directed towards the most promising leads and customers.
* Use Cases:
Recommendation Engines: Suggest products or services based on past behavior and preferences.
Churn Prediction: Identify customers at risk of leaving and engage them with retention strategies.
* Reference:
Salesforce Data Cloud AI Capabilities
Salesforce AI for Customer Interaction


質問 # 113
During discovery, which feature should a consultant highlight for a customer who has multiple data sources and needs to match and reconcile data about individuals into a single unified profile?

  • A. Data Consolidation
  • B. Data Cleansing
  • C. Harmonization
  • D. Identity Resolution

正解:D

解説:
The feature that the consultant should highlight for a customer who has multiple data sources and needs to match and reconcile data about individuals into a single unified profile is D. Identity Resolution. Identity Resolution is the process of identifying, matching, and reconciling data about individuals across different data sources and creating a unified profile that represents a single view of the customer. Identity Resolution uses various methods and rules to determine the best match and reconciliation of data, such as deterministic matching, probabilistic matching, reconciliation rules, and identity graphs. Identity Resolution enables the customer to have a complete and accurate understanding of their customers and their interactions across different channels and touchpoints. References: Salesforce Data Cloud Consultant Exam Guide, Identity Resolution


質問 # 114
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. Data Cloud enforces the presence of Contact Point for Marketing Cloud activations. If the individual does not have a related Contact Point, it will not be activated.
  • B. Marketing Cloud activations only activate those individuals that already exist in Marketing Cloud. They do not allow activation of new records.
  • C. Marketing Cloud activations automatically suppress individuals who are unengaged and have not opened or clicked on an email in the last six months.
  • D. Marketing Cloud activations apply a frequency cap and limit the number of records that can be sent in an activation.

正解:A

解説:
The reason for the activated count being smaller than the segment count is A. Data Cloud enforces the presence of Contact Point for Marketing Cloud activations. If the individual does not have a related Contact Point, it will not be activated. A Contact Point is a data model object that represents a channel or method of communication with an individual, such as email, phone, or social media. For Marketing Cloud activations, Data Cloud requires that the individual has a related Contact Point of type Email, which contains a valid email address. If the individual does not have such a Contact Point, or if the Contact Point is missing or invalid, the individual will not be activated and will not receive the email communication. Therefore, the activated count may be lower than the segment count, depending on how many individuals in the segment have a valid email Contact Point. Reference: Salesforce Data Cloud Consultant Exam Guide, Contact Point, Marketing Cloud Activation


質問 # 115
When performing segmentation or activation, which time zone is used to publish and refresh data?

  • A. Time zone specified on the activity at the time of creation
  • B. Time zone set by the Salesforce Data Cloud org
  • C. Time zone of the user creating the activity
  • D. Time zone of the Data Cloud Admin user

正解:B

解説:
The time zone that is used to publish and refresh data when performing segmentation or activation is D. Time zone set by the Salesforce Data Cloud org. This time zone is the one that is configured in the org settings when Data Cloud is provisioned, and it applies to all users and activities in Data Cloud. This time zone determines when the segments are scheduled to refresh and when the activations are scheduled to publish. Therefore, it is important to consider the time zone difference between the Data Cloud org and the destination systems or channels when planning the segmentation and activation strategies. References: Salesforce Data Cloud Consultant Exam Guide, Segmentation, Activation


質問 # 116
To import campaign members into a campaign in Salesforce CRM, a user wants to export the segment to Amazon S3. The resulting file needs to include the Salesforce CRM Campaign ID in the name.
What are two ways to achieve this outcome?
Choose 2 answers

  • A. Include campaign identifier in the filename specification.
  • B. Include campaign identifier in the activation name.
  • C. Hard code the campaign identifier as a new attribute in the campaign activation.
  • D. Include campaign identifier in the segment name.

正解:A、B

解説:
Explanation
The two ways to achieve this outcome are A and C. Include campaign identifier in the activation name and include campaign identifier in the filename specification. These two options allow the user to specify the Salesforce CRM Campaign ID in the name of the file that is exported to Amazon S3. The activation name and the filename specification are both configurable settings in the activation wizard, where the user can enter the campaign identifier as a text or a variable. The activation name is used as the prefix of the filename, and the filename specification is used as the suffix of the filename. For example, if the activation name is
"Campaign_123" and the filename specification is "{segmentName}_{date}", the resulting file name will be
"Campaign_123_SegmentA_2023-12-18.csv". This way, the user can easily identify the file that corresponds to the campaign and import it into Salesforce CRM.
The other options are not correct. Option B is incorrect because hard coding the campaign identifier as a new attribute in the campaign activation is not possible. The campaign activation does not have any attributes, only settings. Option D is incorrect because including the campaign identifier in the segment name is not sufficient.
The segment name is not used in the filename of the exported file, unless it is specified in the filename specification. Therefore, the user will not be able to see the campaign identifier in the file name.


質問 # 117
Which data model subject area should be used for any Organization, Individual, or Member in the Customer 360 data model?

  • A. Engagement
  • B. Global Account
  • C. Party
  • D. Membership

正解:C

解説:
The data model subject area that should be used for any Organization, Individual, or Member in the Customer 360 data model is the Party subject area. The Party subject area defines the entities that are involved in any business transaction or relationship, such as customers, prospects, partners, suppliers, etc. The Party subject area contains the following data model objects (DMOs):
Organization: A DMO that represents a legal entity or a business unit, such as a company, a department, a branch, etc.
Individual: A DMO that represents a person, such as a customer, a contact, a user, etc.
Member: A DMO that represents the relationship between an individual and an organization, such as an employee, a customer, a partner, etc.
The other options are not data model subject areas that should be used for any Organization, Individual, or Member in the Customer 360 data model. The Engagement subject area defines the actions that people take, such as clicks, views, purchases, etc. The Membership subject area defines the associations that people have with groups, such as loyalty programs, clubs, communities, etc. The Global Account subject area defines the hierarchical relationships between organizations, such as parent-child, subsidiary, etc.
Reference:
Data Model Subject Areas
Party Subject Area
Customer 360 Data Model


質問 # 118
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 calculated insights to make sure they're run after the segments are refreshed.
  • B. Review calculated insights to make sure they're run before segments are refreshed.
  • C. Review segments to ensure they're refreshed after the data is ingested.
  • D. Review data transformations to ensure they're run after calculated insights.

正解:B、C

解説:
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


質問 # 119
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