[Dec 30, 2024] Fully Updated Free Actual Salesforce Data-Cloud-Consultant Exam Questions
Free Data-Cloud-Consultant Questions for Salesforce Data-Cloud-Consultant Exam [Dec-2024]
Salesforce Data-Cloud-Consultant Exam Syllabus Topics:
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NEW QUESTION # 79
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. Ensure the activations are set to Incremental Activation and automatically publish every hour.
- C. Set a refresh schedule for the calculated insights to occur every hour.
- D. Ensure the segments are set to Rapid Publish and set to refresh every hour.
Answer: A
Explanation:
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 The refresh schedule may not align with the activation schedule, resulting in outdated or inconsistent data.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 Exam Guide, Flow, Change Data Events, Calculated Insights, Segments, [Activation]
NEW QUESTION # 80
What is Data Cloud's primary value to customers?
- A. To create personalized campaigns by listening, understanding, and acting on customer behavior
- B. To connect all systems with a golden record
- C. To create a single source of truth for all anonymous data
- D. To provide a unified view of a customer and their related data
Answer: D
Explanation:
Data Cloud is a platform that enables you to activate all your customer data across Salesforce applications and other systems. Data Cloud allows you to create a unified profile of each customer by ingesting, transforming, and linking data from various sources, such as CRM, marketing, commerce, service, and external data providers. Data Cloud also provides insights and analytics on customer behavior, preferences, and needs, as well as tools to segment, target, and personalize customer interactions. Data Cloud's primary value to customers is to provide a unified view of a customer and their related data, which can help you deliver better customer experiences, increase loyalty, and drive growth. References: Salesforce Data Cloud, When Data Creates Competitive Advantage
NEW QUESTION # 81
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. COALE
- B. CONCAT
- C. CAST
- D. COMBIN
Answer: B
Explanation:
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)
References:
* Salesforce Documentation: Formula Functions
* Salesforce Data Cloud Guide
NEW QUESTION # 82
Which two requirements must be met for a calculated insight to appear in the segmentation canvas?
Choose 2 answers
- A. The calculated insight must contain a dimension including the Individual or Unified Individual Id.
- B. The primary key of the segmented table must be a dimension in the calculated insight.
- C. The metrics of the calculated insights must only contain numeric values.
- D. The primary key of the segmented table must be a metric in the calculated insight.
Answer: A,B
Explanation:
A calculated insight is a custom metric or measure that is derived from one or more data model objects or data lake objects in Data Cloud. A calculated insight can be used in segmentation to filter or group the data based on the calculated value. However, not all calculated insights can appear in the segmentation canvas. There are two requirements that must be met for a calculated insight to appear in the segmentation canvas:
* The calculated insight must contain a dimension including the Individual or Unified Individual Id. A dimension is a field that can be used to categorize or group the data, such as name, gender, or location.
The Individual or Unified Individual Id is a unique identifier for each individual profile in Data Cloud.
The calculated insight must include this dimension to link the calculated value to the individual profile and to enable segmentation based on the individual profile attributes.
* The primary key of the segmented table must be a dimension in the calculated insight. The primary key is a field that uniquely identifies each record in a table. The segmented table is the table that contains the data that is being segmented, such as the Customer or the Order table. The calculated insight must include the primary key of the segmented table as a dimension to ensure that the calculated value is associated with the correct record in the segmented table and to avoid duplication or inconsistency in the segmentation results.
References: Create a Calculated Insight, Use Insights in Data Cloud, Segmentation
NEW QUESTION # 83
A consultant is setting up a data stream with transactional data,
Which field type should the consultant choose to ensure that leading
zeros in the purchase order number are preserved?
- A. Text
- B. Decimal
- C. Number
- D. Serial
Answer: A
Explanation:
The field type Text should be chosen to ensure that leading zeros in the purchase order number are preserved. This is because text fields store alphanumeric characters as strings, and do not remove any leading or trailing characters. On the other hand, number, decimal, and serial fields store numeric values as numbers, and automatically remove any leading zeros when displaying or exporting the data123. Therefore, text fields are more suitable for storing data that needs to retain its original format, such as purchase order numbers, zip codes, phone numbers, etc. References:
Zeros at the start of a field appear to be omitted in Data Exports
Keep First '0' When Importing a CSV File
Import and export address fields that begin with a zero or contain a plus symbol
NEW QUESTION # 84
Which functionality does Data Cloud offer to improve customer support interactions when a customer is working with an agent?
- A. Predictive troubleshooting
- B. Enhanced reporting tools
- C. Automated customer service replies
- D. Real-time data integration
Answer: D
Explanation:
Customer Support in Salesforce Data Cloud: One of the key benefits of Salesforce Data Cloud is its ability to enhance customer support by providing comprehensive and real-time customer data.
Real-Time Data Integration: This functionality allows customer support agents to access the most up-to-date customer information, improving their ability to respond to customer inquiries and issues effectively.
Benefits for Customer Support:
* Immediate Access: Agents have real-time access to customer interactions and data, ensuring they can provide accurate and timely support.
* Contextual Information: The integrated data provides a holistic view of the customer's history and preferences, allowing for more personalized support interactions.
Use Case: When a customer contacts support, the agent can see real-time updates on recent purchases, interactions, and any ongoing issues, enabling them to resolve queries quickly and efficiently.
References:
* Salesforce Data Cloud for Customer Support
* Real-Time Data Integration in Salesforce
NEW QUESTION # 85
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. Streaming data transform
- B. Flow Orchestration
- C. Nested segments
- D. Metrics on metrics
Answer: D
Explanation:
Metrics on metrics is a feature that allows creating new metrics based on existing metrics and applying mathematical operations on them. This can be useful for calculating complex business metrics such as LTV, ROI, or conversion rates. In this case, the consultant can use metrics on metrics to calculate the LTV of each customer by summing up the revenue generated by them across different channels. The consultant can also create breakdowns of the revenue by channel by using the channel attribute as a dimension in the metric definition. References: Metrics on Metrics, Create Metrics on Metrics
NEW QUESTION # 86
Cloud Kicks wants to be able to build a segment of customers who have visited its website within the previous
7 days.
Which filter operator on the Engagement Date field fits this use case?
- A. Greater than Last Number of
- B. Is Between
- C. Next Number of Days
- D. Last Number of Days
Answer: D
Explanation:
The filter operator Last Number of Days allows you to filter on date fields using a relative date range that specifies the number of days before today. For example, you can use this operator to filter on customers who have visited your website in the last 7 days, or the last 30 days, or any number of days you want. This operator is useful for creating dynamic segments that update automatically based on the current date12. References:
* Relative Date Filter Reference
* Create Filtered Segments
NEW QUESTION # 87
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. Ensure the activations are set to Incremental Activation and automatically publish every hour.
- C. Set a refresh schedule for the calculated insights to occur every hour.
- D. Ensure the segments are set to Rapid Publish and set to refresh every hour.
Answer: A
Explanation:
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 Exam Guide, Flow, Change Data Events, Calculated Insights, Segments, [Activation]
NEW QUESTION # 88
A company stores customer data in Marketing Cloud and uses the Marketing Cloud Connector to ingest data into Data Cloud.
Where does a request for data deletion or right to be forgotten get submitted?
- A. In Marketing Cloud settings
- B. On the individual data profile in Data Cloud
- C. In Data Cloud settings
- D. through Consent API
Answer: A
Explanation:
Data Deletion Requests: For companies using Salesforce Marketing Cloud and Data Cloud, managing data privacy and deletion requests is essential.
Marketing Cloud Connector: This connector facilitates data integration between Marketing Cloud and Data Cloud, but data deletion requests must follow specific procedures.
Deletion Requests in Marketing Cloud:
* Data Management: Requests for data deletion or the right to be forgotten are submitted through Marketing Cloud settings, where the customer data is originally stored and managed.
* Propagation: Once the request is processed in Marketing Cloud, the changes are propagated to Data Cloud through the connector.
References:
* Salesforce Marketing Cloud Documentation: Data Management
* Salesforce Data Cloud Connector Guide
NEW QUESTION # 89
Which data stream category should be assigned to use the data for time-based operations in segmentation and calculated insights?
- A. Sales Order
- B. Engagement
- 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 # 90
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 apply a frequency cap and limit the number of records that can be sent in an activation.
- D. Marketing Cloud activations automatically suppress individuals who are unengaged and have not opened or clicked on an email in the last six months.
Answer: A
Explanation:
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 count. References: Data Cloud Activation, Contact Point for Marketing Cloud
NEW QUESTION # 91
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. Identity Resolution
- B. Data Cleansing
- C. Data Consolidation
- D. Harmonization
Answer: A
Explanation:
Identity resolution is the feature that allows Data Cloud to match and reconcile data about individuals from multiple data sources into a single unified profile. Identity resolution uses rulesets to define how source profiles are matched and consolidated based on common attributes, such as name, email, phone, or party identifier. Identity resolution enables Data Cloud to create a 360-degree view of each customer across different data sources and systems12. The other options are not the best features to highlight for this customer need because:
* A. Data cleansing is the process of detecting and correcting errors or inconsistencies in data, such as duplicates, missing values, or invalid formats. Data cleansing can improve the quality and accuracy of data, but it does not match or reconcile data across different data sources3.
* B. Harmonization is the process of standardizing and transforming data from different sources into a common format and structure. Harmonization can enable data integration and interoperability, but it does not match or reconcile data across different data sources4.
* C. Data consolidation is the process of combining data from different sources into a single data set or system. Data consolidation can reduce data redundancy and complexity, but it does not match or reconcile data across different data sources5. References: 1: Data and Identity in Data Cloud | Salesforce Trailhead, 2: Data Cloud Identiy Resolution | Salesforce AI Research, 3: [Data Cleansing - Salesforce], 4: [Harmonization - Salesforce], 5: [Data Consolidation - Salesforce]
NEW QUESTION # 92
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 apply a frequency cap and limit the number of records that can be sent in an activation.
- D. Marketing Cloud activations automatically suppress individuals who are unengaged and have not opened or clicked on an email in the last six months.
Answer: A
Explanation:
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. References: Salesforce Data Cloud Consultant Exam Guide, Contact Point, Marketing Cloud Activation
NEW QUESTION # 93
What does the Ignore Empty Value option do in identity resolution?
- A. Ignores empty fields when running the standard match rules
- B. Ignores Individual object records with empty fields when running identity resolution rules
- C. Ignores empty fields when running reconciliation rules
- D. Ignores empty fields when running any custom match rules
Answer: C
Explanation:
The Ignore Empty Value option in identity resolution allows customers to ignore empty fields when running reconciliation rules. Reconciliation rules are used to determine the final value of an attribute for a unified individual profile, based on the values from different sources. The Ignore Empty Value option can be set to true or false for each attribute in a reconciliation rule. If set to true, the reconciliation rule will skip any source that has an empty value for that attribute and move on to the next source in the priority order. If set to false, the reconciliation rule will consider any source that has an empty value for that attribute as a valid source and use it to populate the attribute value for the unified individual profile.
The other options are not correct descriptions of what the Ignore Empty Value option does in identity resolution. The Ignore Empty Value option does not affect the custom match rules or the standard match rules, which are used to identify and link individuals across different sources based on their attributes. The Ignore Empty Value option also does not ignore individual object records with empty fields when running identity resolution rules, as identity resolution rules operate on the attribute level, not the record level.
References:
* Data Cloud Identity Resolution Reconciliation Rule Input
* Configure Identity Resolution Rulesets
* Data and Identity in Data Cloud
NEW QUESTION # 94
Cumulus Financial created a segment called High Investment Balance Customers. This is a foundational segment that includes several segmentation criteria the marketing team should consistently use.
Which feature should the consultant suggest the marketing team use to ensure this consistency when creating future, more refined segments?
- A. Package High Investment Balance Customers in a data kit.
- B. Create new segments using nested segments.
- C. Create a High Investment Balance calculated insight.
- D. Create new segments by cloning High Investment Balance Customers.
Answer: B
Explanation:
Nested segments are segments that include or exclude one or more existing segments. They allow the marketing team to reuse filters and maintain consistency in their data by using an existing segment to build a new one. For example, the marketing team can create a nested segment that includes High Investment Balance Customers and excludes customers who have opted out of email marketing. This way, they can leverage the foundational segment and apply additional criteria without duplicating the rules. The other options are not the best features to ensure consistency because:
B: A calculated insight is a data object that performs calculations on data lake objects or CRM data and returns a result. It is not a segment and cannot be used for activation or personalization.
C: A data kit is a bundle of packageable metadata that can be exported and imported across Data Cloud orgs. It is not a feature for creating segments, but rather for sharing components.
D: Cloning a segment creates a copy of the segment with the same rules and filters. It does not allow the marketing team to add or remove criteria from the original segment, and it may create confusion and redundancy. References: Create a Nested Segment - Salesforce, Save Time with Nested Segments (Generally Available) - Salesforce, Calculated Insights - Salesforce, Create and Publish a Data Kit Unit Salesforce Trailhead, Create a Segment in Data Cloud - Salesforce
NEW QUESTION # 95
How can a consultant modify attribute names to match a naming convention in Cloud File Storage targets?
- A. Set preferred attribute names when configuring activation.
- B. Use a formula field to update the field name in an activation.
- C. Update field names in the data model object.
- D. Update attribute names in the data stream configuration.
Answer: A
NEW QUESTION # 96
What does it mean to build a trust-based, first-party data asset?
- A. To ensure opt-in consents are collected for all email marketing as required by law
- B. To obtain competitive data from reliable sources through interviews, surveys, and polls
- C. To provide trusted, first-party data in the Data Cloud Marketplace that follows all compliance regulations
- D. To provide transparency and security for data gathered from individuals who provide consent for its use and receive value in exchange
Answer: D
Explanation:
Building a trust-based, first-party data asset means collecting, managing, and activating data from your own customers and prospects in a way that respects their privacy and preferences. It also means providing them with clear and honest information about how you use their data, what benefits they can expect from sharing their data, and how they can control their data. By doing so, you can create a mutually beneficial relationship with your customers, where they trust you to use their data responsibly and ethically, and you can deliver more relevant and personalized experiences to them. A trust-based, first-party data asset can help you improve customer loyalty, retention, and growth, as well as comply with data protection regulations and standards. References: Use first-party data for a powerful digital experience, Why first-party data is the key to data privacy, Build a first-party data strategy
NEW QUESTION # 97
A customer has a custom Customer Email c object related to the standard Contact object in Salesforce CRM.
This custom object
stores the email address a Contact that they want to use for activation.
To which data entity is mapped?
- A. Contact
- B. Contact Point_Email
- C. Custom customer Email__c object
- D. Individual
Answer: B
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 # 98
A consultant is working in a customer's Data Cloud org and is asked to delete the existing identity resolution ruleset.
Which two impacts should the consultant communicate as a result of this action?
Choose 2 answers
- A. Dependencies on data model objects will be removed.
- B. All source profile data will be removed
- C. All individual data will be removed.
- D. Unified customer data associated with this ruleset will be removed.
Answer: A,D
Explanation:
Explanation
Deleting an identity resolution ruleset has two major impacts that the consultant should communicate to the customer. First, it will permanently remove all unified customer data that was created by the ruleset, meaning that the unified profiles and their attributes will no longer be available in Data Cloud1. Second, it will eliminate dependencies on data model objects that were used by the ruleset, meaning that the data model objects can be modified or deleted without affecting the ruleset1. These impacts can have significant consequences for the customer's data quality, segmentation, activation, and analytics, so the consultant should advise the customer to carefully consider the implications of deleting a ruleset before proceeding. The other options are incorrect because they are not impacts of deleting a ruleset. Option A is incorrect because deleting a ruleset will not remove all individual data, but only the unified customer data. The individual data from the source systems will still be available in Data Cloud1. Option D is incorrect because deleting a ruleset will not remove all source profile data, but only the unified customer data. The source profile data from the data streams will still be available in Data Cloud1. References: Delete an Identity Resolution Ruleset
NEW QUESTION # 99
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