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NEW QUESTION # 44
A Data Cloud consultant recently discovered that their identity resolution process is matching individuals that share email addresses or phone numbers, but are not actually the same individual.
What should the consultant do to address this issue?
- A. Create and run a new ruleset with stricter matching criteria, compare the two rulesets to review and verify the results, and then migrate to the new ruleset once approved.
- B. Modify the existing ruleset with stricter matching criteria, compare the two rulesets to review and verify the results, and then migrate to the new ruleset once approved.
- C. Modify the existing ruleset with stricter matching criteria, run the ruleset and review the updated results, then adjust as needed until the individuals are matching correctly.
- D. Create and run a new rules fewer matching rules, compare the two rulesets to review and verify the results, and then migrate to the new ruleset once approved.
Answer: A
Explanation:
Identity resolution is the process of linking source profiles from different data sources into unified individual profiles based on match and reconciliation rules. If the identity resolution process is matching individuals that share email addresses or phone numbers, but are not actually the same individual, it means that the match rules are too loose and need to be refined. The best way to address this issue is to create and run a new ruleset with stricter matching criteria, such as adding more attributes or increasing the match score threshold. Then, the consultant can compare the two rulesets to review and verify the results, and see if the new ruleset reduces the false positives and improves the accuracy of the identity resolution. Once the new ruleset is approved, the consultant can migrate to the new ruleset and delete the old one. The other options are incorrect because modifying the existing ruleset can affect the existing unified profiles and cause data loss or inconsistency. Creating and running a new ruleset with fewer matching rules can increase the false negatives and reduce the coverage of the identity resolution. References: Create Unified Individual Profiles, AI-based Identity Resolution: Linking Diverse Customer Data, Data Cloud Identiy Resolution.
NEW QUESTION # 45
What is the result of a segmentation criteria filtering on City | Is Equal To | 'San Jose'?
- A. Cities containing 'San Jose', 'San Jose', 'san jose', or 'san jose'
- B. Cities only containing 'San Jose' or 'san jose'
- C. Cities only containing 'San Jose' or 'san jose'
- D. Cities only containing 'San Jose' or 'San Jose'
Answer: C
Explanation:
The result of a segmentation criteria filtering on City | Is Equal To | 'San Jose' is cities only containing 'San Jose' or 'san jose'. This is because the segmentation criteria is case-sensitive and accent-sensitive, meaning that it will only match the exact value that is entered in the filter1. Therefore, cities containing 'San Jose', 'san jose', or 'San Jose' will not be included in the result, as they do not match the filter value exactly. To include cities with different variations of the name 'San Jose', you would need to use the OR operator and add multiple filter values, such as 'San Jose' OR 'San Jose' OR 'san jose' OR 'san jose'2. References: Segmentation Criteria, Segmentation Operators
NEW QUESTION # 46
Northern Trail Outfitters uses B2C Commerce and is exploring implementing Data Cloud to get a unifiedview of its customers and alltheir 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 does not ingest any historical data and only ingests new orders from that point on.
- B. The B2C Commerce Order Bundle ingests 6 months ofhistorical data.
- C. The B2C Commerce Order Bundle ingests 30 days ofhistorical data.
- D. The B2C Commerce Order Bundle ingests 12 months of historical data.
Answer: A
Explanation:
Explanation
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
NEW QUESTION # 47
Northern Trail Outfitters is using the Marketing Cloud Starter Data Bundles to bring Marketing Cloud data into Data Cloud.
What are two of the available datasets in Marketing Cloud Starter Data Bundles?
Choose 2 answers
- A. MobileConnect
- B. Loyalty Management
- C. MobilePush
- D. Personalization
Answer: A,C
Explanation:
Explanation
The Marketing Cloud Starter Data Bundles are predefined data bundles that allow you to easily ingest data from Marketing Cloud into Data Cloud1. The available datasets in Marketing Cloud Starter Data Bundles are Email, MobileConnect, and MobilePush2. These datasets contain engagement events and metrics from different Marketing Cloud channels, such as email, SMS, and push notifications2. By using these datasets, you can enrich your Data Cloud data model with Marketing Cloud data and create segments and activations based on your marketing campaigns and journeys1. The other options are incorrect because they are not available datasets in Marketing Cloud Starter Data Bundles. Option A is incorrect because Personalization is not a dataset, but a feature of Marketing Cloud that allows you to tailor your content and messages to your audience3. Option C is incorrect because Loyalty Management is not a dataset, but a product of Marketing Cloud that allows you to create and manage loyaltyprograms for your customers4. References: Marketing Cloud Starter Data Bundles in Data Cloud, Connect Your Data Sources, Personalization in Marketing Cloud, Loyalty Management in Marketing Cloud
NEW QUESTION # 48
Northern Trail Outfitters (NTO) is configuring an identity resolution ruleset based on Fuzzy Name and Normalized Email.
What should NTO do to ensure the best email address is activated?
- A. Include Contact Point Email object Is Active field as a match rule.
- B. Set the default reconciliation rule to Last Updated.
- C. Ensure Marketing Cloud is prioritized as the first data source in the Source Priority reconciliation rule.
- D. Use the source priority order in activations to make sure a contact point from the desired source is delivered to the activation target.
Answer: D
Explanation:
NTO is using Fuzzy Name and Normalized Email as match rules to link together data from different sources into a unified individual profile. However, there might be cases where the same email address is available from more than one source, and NTO needs to decide which one to use for activation. For example, if Rachel has the same email address in Service Cloud and Marketing Cloud, but prefers to receive communications from NTO via Marketing Cloud, NTO needs to ensure that the email address from Marketing Cloud is activated. To do this, NTO can use the source priority order in activations, which allows them to rank the data sources in order of preference for activation. By placing Marketing Cloud higher than Service Cloud in the source priority order, NTO can make sure that the email address from Marketing Cloud is delivered to the activation target, such as an email campaign or a journey. This way, NTO can respect Rachel's preference and deliver a better customer experience. References: Configure Activations, Use Source Priority Order in Activations
NEW QUESTION # 49
A customer has a calculated insight about lifetime value.
What does the consultant need to be aware of if the calculated insight.
needs to be modified?
- A. Existing measures can be removed.
- B. Mew measures can be added.
- C. Existing dimensions can be removed.
- D. Mew dimensions can be added.
Answer: C
Explanation:
A calculated insight is a multidimensional metric that is defined and calculated from data using SQL expressions. A calculated insight can include dimensions and measures. Dimensions are the fields that are used to group or filter the data, such as customer ID, product category, or region. Measures are the fields that are used to perform calculations or aggregations, such as revenue, quantity, or average order value. A calculated insight can be modified by editing the SQL expression or changing the data space. However, the consultant needs to be aware of the following limitations and considerations when modifying a calculated insight12:
* Existing dimensions cannot be removed. If a dimension is removed from the SQL expression, the calculated insight will fail to run and display an error message. This is because the dimension is used to create the primary key for the calculated insight object, and removing it will cause a conflict with the existing data. Therefore, the correct answer is B.
* New dimensions can be added. If a dimension is added to the SQL expression, the calculated insight will run and create a new field for the dimension in the calculated insight object. However, the consultant should be careful not to add too many dimensions, as this can affect the performance and usability of the calculated insight.
* Existing measures can be removed. If a measure is removed from the SQL expression, the calculated insight will run and delete the field for the measure from the calculated insight object. However, the consultant should be aware that removing a measure can affect the existing segments or activations that use the calculated insight.
* New measures can be added. If a measure is added to the SQL expression, the calculated insight will run and create a new field for the measure in the calculated insight object. However, the consultant should be careful not to add too many measures, as this can affect the performance and usability of the calculated insight. References: Calculated Insights, Calculated Insights in a Data Space.
NEW QUESTION # 50
A retail customer wants to bring customer data from different sources
and wants to take advantage of identity resolution so that it can be
used in segmentation.
On which entity should this be segmented for activation membership?
- A. Individual
- B. Subscriber
- C. Unified Individual
- D. Unified Contact
Answer: C
Explanation:
The correct answer is B, Unified Individual. A Unified Individual is a record that represents a customer across different data sources, created by applying identity resolution rulesets. Identity resolution rulesets are sets of match and reconciliation rules that define how to link and merge data from different sources based on common attributes. Data Cloud uses identity resolution rulesets to resolve data across multiple data sources and helps you create one record for each customer, regardless of where the data came from1. A retail customer who wants to bring customer data from different sources and use identity resolution for segmentation should segment on the Unified Individual entity, which contains the resolved and consolidated customer data. The other options are incorrect because they do not represent the resolved customer data across different sources. A Subscriber is a record that represents a customer who has opted in to receive marketing communications. A Unified Contact is a record that represents a customer who has a relationship with a specific business unit. An Individual is a record that represents a customer's profile data from a single data source. References:
* Identity Resolution Ruleset Processing Results
* Consider Data Implications for Segmentation
* Prepare for your Salesforce Data Cloud Consultant Credential
* AI-based Identity Resolution: Linking Diverse Customer Data
NEW QUESTION # 51
A customer is trying to activate data from Data Cloud to an Amazon S3 Cloud File Storage Bucket.
Which authentication type should the consultant recommend to connect to the S3 bucket from Data Cloud?
- A. Use an S3 Private Key Certificate.
- B. Use an S3 Encrypted Username and Password.
- C. Use an S3 Access Key and Secret Key.
- D. Use a JWT Token generated on S3.
Answer: C
Explanation:
To use the Amazon S3 Storage Connector in Data Cloud, the consultant needs to provide the S3 bucket name, region, and access key and secret key for authentication. The access key and secret key are generated by AWS and can be managed in the IAM console. The other options are not supported by the S3 Storage Connector or by Data Cloud. References: Amazon S3 Storage Connector - Salesforce, How to Use the Amazon S3 Storage Connector in Data Cloud | Salesforce Developers Blog Learn more
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NEW QUESTION # 52
A customer has a requirement to be able to view the last time each segment was published within their Data Cloud org.
Which two features should the consultant recommend to best address this requirement?
Choose 2 answers
- A. Profile Explorer
- B. Calculated insight
- C. Report
- D. Dashboard
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 # 53
A consultant needs to publish segment data to the Audience DMO that can be retrieved using the Query APIs.
When creating the activation target, which type of target should the consultant select?
- A. Marketing Cloud Personalization
- B. External Activation Target
- C. Data Cloud
- D. Marketing Cloud
Answer: B
Explanation:
Purpose of Activation Targets:
* Activation targets define where and how segment data is published for use in various applications and platforms.
NEW QUESTION # 54
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. Harmonization
- B. Identity Resolution
- C. Data Consolidation
- D. Data Cleansing
Answer: B
Explanation:
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 # 55
Which permission setting should a consultant check if the custom Salesforce CRM object is not available in New Data Stream configuration?
- A. Confirm that the Modify Object permission is enabled in the Data Cloud org.
- B. Confirm the Create object permission is enabled in the Data Cloud org.
- C. Confirm the Ingest Object permission is enabled in the Salesforce CRM org.
- D. Confirm the View All object permission is enabled in the source Salesforce CRM org.
Answer: D
Explanation:
Explanation
To create a new data stream from a custom Salesforce CRM object, the consultant needs to confirm that the View All object permission is enabled in the source Salesforce CRM org. This permission allows the user to view all records associated with the object, regardless of sharing settings1. Without this permission, the custom object will not be available in the New Data Stream configuration2. References:
* Manage Access with Data Cloud Permission Sets
* Object Permissions
NEW QUESTION # 56
A Data Cloud consultant recently added a new data source and mapped some of the data to a new custom data model object (DMO) that they want to use for creating segments. However, they cannot view the newly created DMO when trying to create a new segment.
What is the cause of this issue?
- A. Data has not yes been ingested into the DMO.
- B. The new DMO is not of category Profile.
- C. The new DMO does not have a relationship to the individual DMO
- D. Segmentation is only supported for the Individual and Unified Individual DMOs.
Answer: B
Explanation:
Explanation
The cause of this issue is that the new custom data model object (DMO) is not of category Profile. A category is a property of a DMO that defines its purpose and functionality in Data Cloud. There are three categories of DMOs: Profile, Event, and Other. Profile DMOs are used to store attributes of individuals or entities, such as name, email, address, etc. Event DMOs are used to store actions or interactions of individuals or entities, such as purchases, clicks, visits, etc. Other DMOs are used to store any other type of data that does not fit into the Profile or Event categories, such as products, locations, categories, etc. Only Profile DMOs can be used for creating segments in Data Cloud, as segments are based on the attributes of individuals or entities. Therefore, if the new custom DMO is not of category Profile, it will not appear in the segmentation canvas. The other options are not correct because they are not the cause of this issue. Data ingestion is not a prerequisite for creating segments, as segments can be created based on the data model schema without actual data. The new DMO does not need to have a relationship to the individual DMO, as segments can be created based on any Profile DMO, regardless of its relationship to other DMOs. Segmentation is not only supported for the Individual and Unified Individual DMOs, as segments can be created based on any Profile DMO, including custom ones. References: Create a Custom Data Model Object from an Existing Data Model Object, Create a Segment in Data Cloud, Data Model Object Category
NEW QUESTION # 57
A customer has outlined requirements to trigger a journey for an abandoned browse behavior. Based on the requirements, the consultant determines they will use streaming insights to trigger a data action to Journey Builder every hour.
How should the consultant configure the solution to ensure the data action is triggered at the cadence required?
- A. Set the journey entry schedule to run every hour.
- B. Set the activation schedule to hourly.
- C. Configure the data to be ingested in hourly batches.
- D. Set the insights aggregation time window to 1 hour.
Answer: D
Explanation:
Streaming insights are computed from real-time engagement events and can be used to trigger data actions based on pre-set rules. Data actions are workflows that send data from Data Cloud to other systems, such as Journey Builder. To ensure that the data action is triggered every hour, the consultant should set the insights aggregation time window to 1 hour. This means that the streaming insight will evaluate the events that occurred within the last hour and execute the data action if the conditions are met. The other options are not relevant for streaming insights and data actions. References: Streaming Insights and Data Actions Limits and Behaviors, Streaming Insights, Streaming Insights and Data Actions Use Cases, Use Insights in Data Cloud, 6 Ways the Latest Marketing Cloud Release Can Boost Your Campaigns
NEW QUESTION # 58
Which permission setting should a consultant check if the custom Salesforce CRM object is not available in New Data Stream configuration?
- A. Confirm that the Modify Object permission is enabled in the Data Cloud org.
- B. Confirm the Create object permission is enabled in the Data Cloud org.
- C. Confirm the Ingest Object permission is enabled in the Salesforce CRM org.
- D. Confirm the View All object permission is enabled in the source Salesforce CRM org.
Answer: D
Explanation:
To create a new data stream from a custom Salesforce CRM object, the consultant needs to confirm that the View All object permission is enabled in the source Salesforce CRM org. This permission allows the user to view all records associated with the object, regardless of sharing settings1. Without this permission, the custom object will not be available in the New Data Stream configuration2. References:
* Manage Access with Data Cloud Permission Sets
* Object Permissions
NEW QUESTION # 59
What is Data Cloud's primary value to customers?
- A. To create personalized campaigns by listening, understanding, and acting on customer behavior
- B. To provide a unified view of a customer and their related data
- C. To create a single source of truth for all anonymous data
- D. To connect all systems with a golden record
Answer: B
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 # 60
How can a consultant modify attribute names to match a naming convention in Cloud File Storage targets?
- A. Use a formula field to update the field name in an activation.
- B. Update attribute names in the data stream configuration.
- C. Set preferred attribute names when configuring activation.
- D. Update field names in the data model object.
Answer: C
Explanation:
Explanation
A Cloud File Storage target is a type of data action target in Data Cloud that allows sending data to a cloud storage service such as Amazon S3 or Google Cloud Storage. When configuring an activation to a Cloud File Storage target, a consultant can modify the attribute names to match a naming convention by setting preferred attribute names in Data Cloud. Preferred attribute names are aliases that can be used to control the field names in the target file. They can be set for each attribute in the activation configuration, and they will override the default field names from the data model object. The other options are incorrect because they do not affect the field names in the target file. Using a formula field to update the field name in an activation will not change the field name, but only the field value. Updating attribute names inthe data stream configuration will not affect the existing data lake objects or data model objects. Updating field names in the data model object will change the field names for all data sources and activations that use the object, which may not be desirable or consistent. References: Preferred Attribute Name, Create a Data Cloud Activation Target, Cloud File Storage Target
NEW QUESTION # 61
Which data model subject area defines the revenue or quantity for an opportunity by product family?
- A. Sales Order
- B. Product
- C. Engagement
- D. Party
Answer: A
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 # 62
A customer notices that their consolidation rate is low across their account unification. They have mapped Account to the Individual and Contact Point Email DMOs.
What should they do to increase their consolidation rate?
- A. Increase the number of matching rules.
- B. Change reconciliation rules to Most Occurring.
- C. Disable the individual identity ruleset.
- D. Update their account address details in the data source
Answer: A
Explanation:
Consolidation Rate: The consolidation rate in Salesforce Data Cloud refers to the effectiveness of unifying records into a single profile. A low consolidation rate indicates that many records are not being successfully unified.
Matching Rules: Matching rules are critical in the identity resolution process. They define the criteria for identifying and merging duplicate records.
Solution:
* Increase Matching Rules: Adding more matching rules improves the system's ability to identify duplicate records. This includes matching on additional fields or using more sophisticated matching algorithms.
* Steps:
* Access the Identity Resolution settings in Data Cloud.
* Review the current matching rules.
* Add new rules that consider more fields such as phone number, address, or other unique identifiers.
Benefits:
* Improved Unification: Higher accuracy in matching and merging records, leading to a higher consolidation rate.
* Comprehensive Profiles: Enhanced customer profiles with consolidated data from multiple sources.
References:
* Salesforce Data Cloud Identity Resolution
* Salesforce Help: Matching Rules
NEW QUESTION # 63
What does it mean to build a trust-based, first-party data asset?
- A. To obtain competitive data from reliable sources through interviews, surveys, and polls
- B. To provide transparency and security for data gathered from individuals who provide consent for its use and receive value in exchange
- C. To ensure opt-in consents are collected for all email marketing as required by law
- D. To provide trusted, first-party data in the Data Cloud Marketplace that follows all compliance regulations
Answer: B
Explanation:
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 # 64
A user is not seeing suggested values from newly-modeled data when building a segment.
What is causing this issue?
- A. Value suggestion will only return result for the first 50 values of a specific attribute.
- B. Value suggestion can only work on direct attributes and not related attributes.
- C. Value suggestion requires Data Aware Specialist permissions at a minimum.
- D. Value suggestion is still processing and to be available.
Answer: D
Explanation:
Explanation
Value suggestion is a feature that allows users to see suggested values for data model object (DMO) fields when creating segment filters. However, this feature can take up to 24 hours to process and display the values for newly-modeled data. Therefore, if a user is not seeing suggested values from newly-modeled data, it is likely that the value suggestion is still processing and will be available soon. The other options are incorrect because value suggestion does not require any specific permissions, can work on both direct and related attributes, and can return more than 50 values for a specific attribute, depending on the data type and frequency of the values. References: Use Value Suggestions in Segmentation, Data Cloud Limits and Guidelines
NEW QUESTION # 65
Which two dependencies need to be removed prior to disconnecting a data source?
Choose 2 answers
- A. Segment
- B. Activation
- C. Activation target
- D. Data stream
Answer: A,D
Explanation:
Dependencies in Data Cloud:
* Before disconnecting a data source, all dependencies must be removed to prevent data integrity issues.
NEW QUESTION # 66
What does the Ignore Empty Value option do in identity resolution?
- A. Ignores Individual object records with empty fields when running identity resolution rules
- B. Ignores empty fields when running any custom match rules
- C. Ignores empty fields when running reconciliation rules
- D. Ignores empty fields when running the standard 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 # 67
Cumulus Financial wants to segregate Salesforce CRM Account data based on Country for its Data Cloud users.
What should the consultant do to accomplish this?
- A. Use the data spaces feature and applying filtering on the Account data lake object based on Country.
- B. Use streaming transforms to filter out Account data based on Country and map to separate data model objects accordingly.
- C. Use Salesforce sharing rules on the Account object to filter and segregate records based on Country.
- D. Use formula fields based on the account Country field to filter incoming records.
Answer: A
Explanation:
Explanation
Data spaces are a feature that allows Data Cloud users to create subsets of data based on filters and permissions. Data spaces can be used to segregate data based on different criteria, such as geography, business unit, or product line. In this case, the consultant can use the dataspaces feature and apply filtering on the Account data lake object based on Country. This way, the Data Cloud users can access only the Account data that belongs to their respective countries. References: Data Spaces, Create a Data Space
NEW QUESTION # 68
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