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NEW QUESTION # 42
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. Calculated insight
- B. Profile Explorer
- C. Dashboard
- D. Report
Answer: C,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 # 43
When trying to disconnect a data source an error will be generated if it has which two dependencies associated with it?
Choose 2 answers
- A. Data stream
- B. Activation
- C. Segment
- D. Activation target
Answer: A,C
Explanation:
When disconnecting a data source in Salesforce Data Cloud, the system checks for active dependencies that rely on the data source. Based on Salesforce's official documentation (Disconnect a Data Source), the error occurs if the data source has data streams or segments associated with it. Here's the breakdown:
Key Dependencies That Block Disconnection
Data Stream (Option B):
Why It Matters:A data stream is the pipeline that ingests data from the source into Data Cloud. If an active data stream is connected to the data source, disconnecting the source will fail because the stream depends on it for ongoing data ingestion.
Resolution:Delete or pause the data stream first.
Documentation Reference:"Before disconnecting a data source, delete all data streams that are associated with it." (Salesforce Help Article) Segment (Option C):
Why It Matters:Segments built using data from the source will reference that data source. Disconnecting the source would orphan these segments, so the system blocks the action.
Resolution:Delete or modify segments that depend on the data source.
Documentation Reference:"If there are segments that use data from the data source, you must delete those segments before disconnecting the data source." (Salesforce Help Article) Why Other Options Are Incorrect Activation (A):Activations send segments to external systems (e.g., Marketing Cloud) but do not directly depend on the data source itself. The dependency chain is Segment # Activation, not Data Source # Activation.
Activation Target (D):Activation targets (e.g., Marketing Cloud) are destinations and do not tie directly to the data source.
Steps to Disconnect a Data Source
Delete Dependent Segments:Navigate to Data Cloud > Segments and remove any segments built using the data source.
Delete or Pause Data Streams:Go to Data Cloud > Data Streams and delete streams linked to the data source.
Disconnect the Data Source:Once dependencies are resolved, disconnect the source via Data Cloud > Data Sources.
NEW QUESTION # 44
What is the primary purpose of Data Cloud?
- A. Managing sales cycles and opportunities
- B. Analyzing marketing data results
- C. Providing a golden record of a customer
- D. Integrating and unifying customer data
Answer: D
Explanation:
Primary Purpose of Data Cloud:
Salesforce Data Cloud's main function is to integrate and unify customer data from various sources, creating a single, comprehensive view of each customer.
Reference: Salesforce Data Cloud Overview
Benefits of Data Integration and Unification:
Golden Record: Providing a unified, accurate view of the customer.
Enhanced Analysis: Enabling better insights and analytics through comprehensive data.
Improved Customer Engagement: Facilitating personalized and consistent customer experiences across channels.
Reference: Salesforce Data Cloud Benefits Documentation
Steps for Data Integration:
Ingest data from multiple sources (CRM, marketing, service platforms).
Use data harmonization and reconciliation processes to unify data into a single profile.
Reference: Salesforce Data Integration and Unification Guide
Practical Application:
Example: A retail company integrates customer data from online purchases, in-store transactions, and customer service interactions to create a unified customer profile.
This unified data enables personalized marketing campaigns and improved customer service.
Reference: Salesforce Unified Customer Profile Case Studies
NEW QUESTION # 45
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 any custom match rules
- D. Ignores empty fields when running reconciliation rules
Answer: D
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 # 46
A Data Cloud consultant is working with data that is clean and organized. However, the various schemas refer to a person by multiple names - such as user; contact, and subscriber - and need a standard mapping.
Which term describes the process of mapping these different schema points into a standard data model?
- A. Unify
- B. Transform
- C. Harmonize
- D. Segment
Answer: C
Explanation:
Introduction to Data Harmonization:
Data harmonization is the process of bringing together data from different sources and making it consistent.
Reference: Salesforce Data Harmonization Overview
Mapping Different Schema Points:
In Data Cloud, different schemas may refer to the same entity using different names (e.g., user, contact, subscriber).
Harmonization involves standardizing these different terms into a single, consistent schema.
Reference: Salesforce Schema Mapping Guide
Process of Harmonization:
Identify Variations: Recognize the different names and fields referring to the same entity across schemas.
Standard Mapping: Create a standard data model and map the various schema points to this model.
Example: Mapping "user", "contact", and "subscriber" to a single standard entity like "Customer." Reference: Salesforce Data Model Harmonization Documentation Steps to Harmonize Data:
Define a standard data model.
Map the fields from different schemas to this standard model.
Ensure consistency across the data ecosystem.
Reference: Salesforce Data Harmonization Best Practices
NEW QUESTION # 47
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. Commerce Cloud Connector
- C. Marketing Cloud Personalization Connector
- D. Cloud Storage Connector
Answer: A
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. Reference: Ingestion API Developer Guide, Ingest Data into Data Cloud
NEW QUESTION # 48
Which solution provides an easy way to ingest Marketing Cloud subscriber profile attributes into Data Cloud on a daily basis?
- A. Marketing Cloud Data extension Data Stream
- B. Marketing Cloud Connect API
- C. Automation Studio and Profile file API
- D. Email Studio Starter Data Bundle
Answer: A
Explanation:
The solution that provides an easy way to ingest Marketing Cloud subscriber profile attributes into Data Cloud on a daily basis is the Marketing Cloud Data extension Data Stream. The Marketing Cloud Data extension Data Stream is a feature that allows customers to stream data from Marketing Cloud data extensions to Data Cloud data spaces. Customers can select which data extensions they want to stream, and Data Cloud will automatically create and update the corresponding data model objects (DMOs) in the data space.
Customers can also map the data extension fields to the DMO attributes using a user interface or an API. The Marketing Cloud Data extension Data Stream can help customers ingest subscriber profile attributes and other data from Marketing Cloud into Data Cloud without writing any code or setting up any complex integrations.
The other options are not solutions that provide an easy way to ingest Marketing Cloud subscriber profile attributes into Data Cloud on a daily basis. Automation Studio and Profile file API are tools that can be used to export data from Marketing Cloud to external systems, but they require customers to write scripts, configure file transfers, and schedule automations. Marketing Cloud Connect API is an API that can be used to access data from Marketing Cloud in other Salesforce solutions, such as Sales Cloud or Service Cloud, but it does not support streaming data to Data Cloud. Email Studio Starter Data Bundle is a data kit that contains sample data and segments for Email Studio, but it does not contain subscriber profile attributes or stream data to Data Cloud.
References:
* Marketing Cloud Data Extension Data Stream
* Data Cloud Data Ingestion
* [Marketing Cloud Data Extension Data Stream API]
* [Marketing Cloud Connect API]
* [Email Studio Starter Data Bundle]
NEW QUESTION # 49
A consultant needs to package Data Cloud components from one
organization to another.
Which two Data Cloud components should the consultant include in a
data kit to achieve this goal?
Choose 2 answers
- A. Segments
- B. Identity resolution rulesets
- C. Data model objects
- D. Calculated insights
Answer: B,C
Explanation:
To package Data Cloud components from one organization to another, the consultant should include the following components in a data kit:
Data model objects: These are the custom objects that define the data model for Data Cloud, such as Individual, Segment, Activity, etc. They store the data ingested from various sources and enable the creation of unified profiles and segments1.
Identity resolution rulesets: These are the rules that determine how data from different sources are matched and merged to create unified profiles. They specify the criteria, logic, and priority for identity resolution2. Reference:
1: Data Model Objects in Data Cloud
2: Identity Resolution Rulesets in Data Cloud
NEW QUESTION # 50
A Data Cloud consultant tries to save a new 1-to-l relationship between the Account DMO and Contact Point Address DMO but gets an error.
What should the consultant do to fix this error?
- A. Map additional fields to the Contact Point Address DMO.
- B. Map Account to Contact Point Email and Contact Point Phone also.
- C. Make sure that the total account records are high enough for Identity resolution.
- D. Change the cardinality to many-to-one to accommodate multiple contacts per account.
Answer: A
NEW QUESTION # 51
Which two steps should a consultant take if a successfully configured Amazon S3 data stream fails to refresh with a "NO FILE FOUND" error message?
Choose 2 answers
- A. Check if the Amazon S3 data source is enabled in Data Cloud Setup.
- B. Check if correct permissions are configured for the Data Cloud user.
- C. Check if correct permissions are configured for the S3 user.
- D. Check If the file exists in the specified bucket location.
Answer: B,D
Explanation:
A "NO FILE FOUND" error message indicates that Data Cloud cannot access or locate the file from the Amazon S3 source. There are two possible reasons for this error and two corresponding steps that a consultant should take to troubleshoot it:
* The Data Cloud user does not have the correct permissions to read the file from the Amazon S3 bucket.
This could happen if the user's permission set or profile does not include the Data Cloud Data Stream Read permission, or if the user's Amazon S3 credentials are invalid or expired. To fix this issue, the consultant should check and update the user's permissions and credentials in Data Cloud and Amazon S3, respectively.
* The file does not exist in the specified bucket location. This could happen if the file name or path has changed, or if the file has been deleted or moved from the Amazon S3 bucket. To fix this issue, the consultant should check and verify the file name and path in the Amazon S3 bucket, and update the data stream configuration in Data Cloud accordingly. References: Create Amazon S3 Data Stream in Data Cloud, How to Use the Amazon S3 Storage Connector in Data Cloud, Amazon S3 Connection
NEW QUESTION # 52
How does Data Cloud ensure high availability and fault tolerance for customer data?
- A. By limiting data access to essential personnel
- B. By using a data center with robust backups
- C. By Implementing automatic data recovery procedures
- D. By distributing data across multiple regions and data centers
Answer: D
Explanation:
Ensuring High Availability and Fault Tolerance:
* High availability refers to systems that are continuously operational and accessible, while fault tolerance is the ability to continue functioning in the event of a failure.
NEW QUESTION # 53
Which data model subject area defines the revenue or quantity for an opportunity by product family?
- A. Party
- B. Engagement
- C. Product
- 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 # 54
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. Use the Consent API to suppress processing and delete the Individual and related records from source data streams.
- C. Add the Individual ID to a headerless file and use the delete from file functionality.
- 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 # 55
A Data Cloud consultant is evaluating the initial phase of the Data Cloud lifecycle for a company.
Which action is essential to effectively begin the Data Cloud lifecycle?
- A. Migrate the existing data into the Customer 360 Data Model.
- B. Use calculated insights determine the benefits of Data Cloud for this company.
- C. Identify use cases and the required data sources and data quality.
- D. Analyze and partition the data into data spaces.
Answer: C
Explanation:
Data Cloud Lifecycle: The initial phase of the Salesforce Data Cloud lifecycle is critical for setting the foundation for successful data integration and utilization.
Identifying Use Cases:
* Importance: Defining clear use cases helps in understanding the business objectives and how Data Cloud can address them.
* Required Data Sources: Identifying the necessary data sources ensures that relevant data is ingested into Data Cloud.
* Data Quality: Assessing data quality is essential for accurate and reliable data analysis and insights.
Actions:
* Step 1: Engage with stakeholders to define specific use cases for Data Cloud.
* Step 2: Identify and catalog the required data sources for these use cases.
* Step 3: Evaluate the quality of data from these sources to ensure they meet the standards for effective data analysis.
References:
* Salesforce Data Cloud Implementation Guide
* Salesforce Data Cloud Lifecycle
NEW QUESTION # 56
A customer notices that their consolidation rate has recently increased. They contact the consultant to ask why.
What are two likely explanations for the increase?
Choose 2 answers
- A. Identity resolution rules have been added to the ruleset to increase the number of matched
- B. New data sources have been added to Data Cloud that largely overlap with the existing profiles.
- C. Identity resolution rules have been removed to reduce the number of matched profiles.
- D. Duplicates have been removed from source system data streams.
Answer: A,B
Explanation:
profiles.
Explanation:
The consolidation rate is a metric that measures the amount by which source profiles are combined to produce unified profiles in Data Cloud, calculated as 1 - (number of unified profiles / number of source profiles). A higher consolidation rate means that more source profiles are matched and merged into fewer unified profiles, while a lower consolidation rate means that fewer source profiles are matched and more unified profiles are created. There are two likely explanations for why the consolidation rate has recently increased for a customer:
New data sources have been added to Data Cloud that largely overlap with the existing profiles. This means that the new data sources contain many profiles that are similar or identical to the profiles from the existing data sources. For example, if a customer adds a new CRM system that has the same customer records as their old CRM system, the new data source will overlap with the existing one. When Data Cloud ingests the new data source, it will use the identity resolution ruleset to match and merge the overlapping profiles into unified profiles, resulting in a higher consolidation rate.
Identity resolution rules have been added to the ruleset to increase the number of matched profiles. This means that the customer has modified their identity resolution ruleset to include more match rules or more match criteria that can identify more profiles as belonging to the same individual. For example, if a customer adds a match rule that matches profiles based on email address and phone number, instead of just email address, the ruleset will be able to match more profiles that have the same email address and phone number, resulting in a higher consolidation rate.
NEW QUESTION # 57
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. Commerce Cloud Connector
- C. Marketing Cloud Personalization Connector
- D. Cloud Storage 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 # 58
The Salesforce CRM Connector is configured and the Case object data stream is set up. Subsequently, a new custom field named Business Priority is created on the Case object in Salesforce CRM. However, the new field is not available when trying to add it to the data stream.
Which statement addresses the cause of this issue?
- A. After 24 hourswhen the data stream refreshesit will automatically include any new fields that were added to the Salesforce CRM.
- B. Customfields on the Case object are not supportedfor ingesting into Data Cloud.
- C. The Salesforce Data Loader application should beused to perform a bulk upload from a desktop.
- D. The Salesforce Integration User Is missing Rad permissions on the newly created field.
Answer: D
Explanation:
Explanation
The Salesforce CRM Connector uses the Salesforce Integration User to access the data from the Salesforce CRM org. The Integration User must have the Read permission on the fields that are included in the data stream. If the Integration User does not have the Read permission on the newly created field, the field will not be available for selection in the data stream configuration. To resolve this issue, the administrator should assign the Read permission on the new field to the Integration User profile or permission set. References: Create a Salesforce CRM Data Stream, Edit a Data Stream, Salesforce Data Cloud Full Refresh for CRM, SFMC, or Ingestion API Data Streams
NEW QUESTION # 59
A marketing manager at Northern Trail Outfitters wants to Improve marketing return on investment (ROI) by tapping into Insights from Data Cloud Segment Intelligence.
Which permission set does a user need to set this up?
- A. Cloud Marketing Manager
- B. Data Cloud Admin
- C. Data Cloud User
- D. Data Cloud Data Aware Specialist
Answer: B
NEW QUESTION # 60
Cumulus Financial uses Service Cloud as its CRM and stores mobile phone, home phone, and work phone as three separate fields for its customers on the Contact record. The company plans to use Data Cloud and ingest the Contact object via the CRM Connector.
What is the most efficient approach that a consultant should take when ingesting this data to ensure all the different phone numbers are properly mapped and available for use in activation?
- A. Ingest the Contact object and map the Work Phone, Mobile Phone, and Home Phone to the Contact Point Phone data map object from the Contact data stream.
- B. Ingest the Contact object and use streaming transforms to normalize the phone numbers from the Contact data stream into a separate Phone data lake object (DLO) that contains three rows, and then map this new DLO to the Contact Point Phone data map object.
- C. Ingest the Contact object and create formula fields in the Contact data stream on the phone numbers, and then map to the Contact Point Phone data map object.
- D. Ingest the Contact object and then create a calculated insight to normalize the phone numbers, and then map to the Contact Point Phone data map object.
Answer: B
Explanation:
The most efficient approach that a consultant should take when ingesting this data to ensure all the different phone numbers are properly mapped and available for use in activation is B. Ingest the Contact object and use streaming transforms to normalize the phone numbers from the Contact data stream into a separate Phone data lake object (DLO) that contains three rows, and then map this new DLO to the Contact Point Phone data map object. This approach allows the consultant to use the streaming transforms feature of Data Cloud, which enables data manipulation and transformation at the time of ingestion, without requiring any additional processing or storage. Streaming transforms can be used to normalize the phone numbers from the Contact data stream, such as removing spaces, dashes, or parentheses, and adding country codes if needed. The normalized phone numbers can then be stored in a separate Phone DLO, which can have one row for each phone number type (work, home, mobile). The Phone DLO can then be mapped to the Contact Point Phone data map object, which is a standard object that represents a phone number associated with a contact point.
This way, the consultant can ensure that all the phone numbers are available for activation, such as sending SMS messages or making calls to the customers.
The other options are not as efficient as option B. Option A is incorrect because it does not normalize the phone numbers, which may cause issues with activation or identity resolution. Option C is incorrect because it requires creating a calculated insight, which is an additional step that consumes more resources and time than streaming transforms. Option D is incorrect because it requires creating formula fields in the Contact data stream, which may not be supported by the CRM Connector or may cause conflicts with the existing fields in the Contact object. References: Salesforce Data Cloud Consultant Exam Guide, Data Ingestion and Modeling, Streaming Transforms, Contact Point Phone
NEW QUESTION # 61
A new user of Data Cloud only needs to be able to review individual rows of ingested data and validate that it has been modeled successfully to its linked data model object. The user will also need to make changes if required.
What is the minimum permission set needed to accommodate this use case?
- A. Data Cloud for Marketing Specialist
- B. Data Cloud for Marketing Data Aware Specialist
- C. Data Cloud User
- D. Data Cloud Admin
Answer: C
Explanation:
The Data Cloud User permission set is the minimum permission set needed to accommodate this use case. The Data Cloud User permission set grants access to the Data Explorer feature, which allows the user to review individual rows of ingested data and validate that it has been modeled successfully to its linked data model object. The user can also make changes to the data model object fields, such as adding or removing fields, changing field types, or creating formula fields. The Data Cloud User permission set does not grant access to other Data Cloud features or tasks, such as creating data streams, creating segments, creating activations, or managing users. The other permission sets are either too restrictive or too permissive for this use case. The Data Cloud for Marketing Specialist permission set only grants access to the segmentation and activation features, but not to the Data Explorer feature. The Data Cloud Admin permission set grants access to all Data Cloud features and tasks, including the Data Explorer feature, but it is more than what the user needs. The Data Cloud for Marketing Data Aware Specialist permission set grants access to the Data Explorer feature, but also to the segmentation and activation features, which are not required for this use case. Reference: Data Cloud Standard Permission Sets, Data Explorer, Set Up Data Cloud Unit
NEW QUESTION # 62
A customer is concerned that the consolidation rate displayed in the identity resolution is quite low compared to their initial estimations.
Which configuration change should a consultant consider in order to increase the consolidation rate?
- A. Increase the number of matching rules.
- B. Include additional attributes in the existing matching rules.
- C. Change reconciliation rules to MostOccurring.
- D. Reduce the number of matching rules.
Answer: A
Explanation:
Explanation
The consolidation rate is the amount by which source profiles are combined to produce unified profiles, calculated as 1 - (number of unified individuals / number of source individuals). For example, if you ingest
100 source records and create 80 unified profiles, your consolidation rate is 20%. To increase the consolidation rate, you need to increase the number of matches between source profiles, which can be done by adding more match rules. Match rules define the criteria for matching source profiles based on their attributes.
By increasing the number of match rules, you can increase the chances of finding matches between source profiles and thus increase the consolidation rate. On the other hand, changing reconciliation rules, including additional attributes, or reducing the number of match rules can decrease the consolidation rate, as they can either reduce the number of matches or increase the number of unified profiles. References: Identity Resolution Calculated Insight: Consolidation Rates for Unified Profiles, Identity Resolution Ruleset Processing Results, Configure Identity Resolution Rulesets
NEW QUESTION # 63
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 matching rule based on party identification that matches on CRM ID as the party identification name.
- B. 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.
- C. Map the primary key from the two systems to Party Identification, using CRM ID as the identification name for both.
- D. Create a custom matching rule for an exact match on the Individual ID attribute.
Answer: A,C
Explanation:
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. Reference: Configure Identity Resolution Rulesets, Identity Resolution Match Rules, Data Cloud Identity Resolution Ruleset, Data Cloud Identity Resolution Config Input
NEW QUESTION # 64
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