This page was exported from Free Exams Dumps Materials [ http://exams.dumpsmaterials.com ] Export date:Fri Dec 27 3:46:15 2024 / +0000 GMT ___________________________________________________ Title: [May-2024 Newly Released] Data-Cloud-Consultant Dumps for Salesforce Data Cloud Certified [Q30-Q52] --------------------------------------------------- [May-2024 Newly Released] Data-Cloud-Consultant Dumps for Salesforce Data Cloud Certified Updated Verified Data-Cloud-Consultant dumps Q&As - 100% Pass Salesforce Data-Cloud-Consultant Exam Syllabus Topics: TopicDetailsTopic 1Describe Data Cloud's function, key terminology, and business value Define activations and their basic use casesTopic 2Define basic concepts of segmentation and use cases Diagnose and explore data using Data Explorer, Profile Explorer, and APIsTopic 3Identify typical use cases for Data Cloud Describe and configure the available data stream types and data bundlesTopic 4Identify the different transformation capabilities within Data Cloud Use available tools to inspect and validate ingested and modeled data   NO.30 A consultant has an activation that is set to publish every 12 hours, but has discovered that updates to the data prior to activation are delayed by up to 24 hours.Which two areas should a consultant review to troubleshoot this issue?Choose 2 answers  Review data transformations to ensure they’re run after calculated insights.  Review calculated insights to make sure they’re run before segments are refreshed.  Review segments to ensure they’re refreshed after the data is ingested.  Review calculated insights to make sure they’re run after the segments are refreshed. The correct answer is B and C because calculated insights and segments are both dependent on the data ingestion process. Calculated insights are derived from the data model objects and segments are subsets of data model objects that meet certain criteria. Therefore, both of them need to be updated after the data is ingested to reflect the latest changes. Data transformations are optional steps that can be applied to the data streams before they are mapped to the data model objects, so they are not relevant to the issue. Reviewing calculated insights to make sure they’re run after the segments are refreshed (option D) is also incorrect because calculated insights are independent of segments and do not need to be refreshed after them. References: Salesforce Data Cloud Consultant Exam Guide, Data Ingestion and Modeling, Calculated Insights, SegmentsNO.31 Northern Trail Outfitters is using the Marketing Cloud Starter Data Bundles to bring Marketing Cloud data into Data Cloud.What are two of the available datasets in Marketing Cloud Starter Data Bundles?Choose 2 answers  Personalization  MobileConnect  Loyalty Management  MobilePush ExplanationThe 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 CloudNO.32 Which statement about Data Cloud’s Web and Mobile ApplicationConnector is true?  A standard schemacontaining event, profile, andtransaction data is created at the time the connector is configured.  The Tenant Specific Endpoint is auto-generated in Data Cloud when setting the connector.  Any data streams associated with the connector will be automatically deleted upon deleting the app from Data Cloud Setup.  The connector schema can be updated to delete an existing field. ExplanationThe Web and Mobile Application Connector allows you to ingest data from your websites and mobile apps into Data Cloud. To use this connector, you need to set up a Tenant Specific Endpoint (TSE) in Data Cloud, which is a unique URL that identifies your Data Cloud org. The TSE is auto-generated when you create a connector app in Data Cloud Setup. You can then use the TSE to configure the SDKs for your websites and mobile apps, which will send data to DataCloud through the TSE. References: Web and Mobile Application Connector, Connect Your Websites and Mobile Apps, Create a Web or Mobile App Data StreamNO.33 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  Map the primary key from the two systems to Party Identification, using CRM ID as the identification name for both.  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.  Create a custom matching rule for an exact match on the Individual ID attribute.  Create a matching rule based on party identification that matches on CRM ID as the party identification name. ExplanationTo address this new use case, the consultant should map the primary key from the two systems to Party Identification, using CRM ID as the identification name for both, and create a matching rule based on party identification that matches on CRM ID as the party identification name. This way, the consultant can ensure that the CRM Contacts and Marketing Contacts are matched based on their CRM ID, which is a unique identifier for each individual. By using Party Identification, the consultant can also leverage the benefits of this attribute, such as being able to match across different entities and sources, and being able to handle multiple values for the same individual. The other options are incorrect because they either do not use the CRM ID as the primary key, or they do not use Party Identification as the attribute type. References: Configure Identity Resolution Rulesets, Identity Resolution Match Rules, Data Cloud Identity Resolution Ruleset, Data Cloud Identity Resolution Config InputNO.34 A consultant is setting up a data stream with transactional data,Which field type should the consultant choose to ensure that leadingzeros in the purchase order number are preserved?  Text  Number  Decimal  Serial 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 symbolNO.35 Northern Trail Outfitters (NTD) creates a calculated insight to computerecency, frequency, monetary {RFM) scores on its unified individuals. NTO then creates a segment based on these scores that it activates to a Marketing Cloud activation target.Which two actions are required when configuring the activation?Choose 2 answers  Add additional attributes.  Choose a segment.  Select contact points.  Add the calculated insight in the activation. ExplanationTo configure an activation to a Marketing Cloud activation target, you need to choose a segment and select contact points. Choosing a segment allows you to specify which unified individuals you want to activate.Selecting contact points allows you to map the attributes from the segment to the fields in the Marketing Cloud data extension. You do not need to add additional attributes or add the calculated insight in the activation, as these are already part of the segment definition. References: Create a Marketing Cloud Activation Target; Types of Data Targets in Data CloudNO.36 Which two dependencies prevent a data stream from being deleted?Choose 2 answers  The underlying data lake object is used in activation.  The underlying data lake object is used in a data transform.  The underlying data lake object is mapped to a data model object.  The underlying data lake object is used in segmentation. To delete a data stream in Data Cloud, the underlying data lake object (DLO) must not have any dependencies or references to other objects or processes. The following two dependencies prevent a data stream from being deleted1:* Data transform: This is a process that transforms the ingested data into a standardized format and structure for the data model. A data transform can use one or more DLOs as input or output. If a DLO is used in a data transform, it cannot be deleted until the data transform is removed or modified2.* Data model object: This is an object that represents a type of entity or relationship in the data model. A data model object can be mapped to one or more DLOs to define its attributes and values. If a DLO is mapped to a data model object, it cannot be deleted until the mapping is removed or changed3.References:* 1: Delete a Data Stream article on Salesforce Help* 2: [Data Transforms in Data Cloud] unit on Trailhead* 3: [Data Model in Data Cloud] unit on TrailheadNO.37 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?  Set the activation schedule to hourly.  Configure the data to be ingested in hourly batches.  Set the journey entry schedule to run every hour.  Set the insights aggregation time window to 1 hour. 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 CampaignsNO.38 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  New data sources have been added to Data Cloud that largely overlap with the existing profiles.  Duplicates have been removed from source system data streams.  Identity resolution rules have been removed to reduce the number of matched profiles.  Identity resolution rules have been added to the ruleset to increase the number of matched profiles. 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.References: Identity Resolution Calculated Insight: Consolidation Rates for Unified Profiles, Configure Identity Resolution RulesetsNO.39 A customer has multiple team members who create segment audiences that work in different time zones. One team member works at the home office in the Pacific time zone,that matches the org Time Zonesetting.Another team member works remotely in the Eastern time zone.Which user will see their home time zone in the segment and activation schedule areas?  The team member in the Pacific time zone.  The team member in the Eastern time zone.  Neither team member; Data Cloud showsall schedules in GMT.  Both team members; Data Cloud adjusts the segment and activation schedules to the time zone of the logged-in user ExplanationThe correct answer is D, both team members; Data Cloud adjusts the segment and activation schedules to the time zone of the logged-in user. Data Cloud uses the time zone settings of the logged-in user to display the segment and activation schedules. This means that each user will see the schedules in their own home time zone, regardless of the org time zone setting or the location of other team members. This feature helps users to avoid confusion and errors when scheduling segments and activations across different time zones. The other options are incorrect because they do not reflect how Data Cloud handles time zones. The team member in the Pacific time zone will not see the same time zone as the org time zone setting, unless their personal time zone setting matches the org time zone setting. The team member in the Eastern time zone will not see the schedules in the org time zone setting, unless their personal time zone setting matches the org time zone setting. Data Cloud does not show all schedules in GMT, but rather in the user’s local time zone. References:* Data Cloud Time Zones* Change default time zones for Users and the organization* Change your time zone settings in Salesforce, Google & Outlook* DateTime field and Time Zone Settings in SalesforceNO.40 A consultant wants to ensure that every segment managed by multiple brand teams adheres to the same set of exclusion criteria, that are updated on a monthly basis.What is the most efficient option to allow for this capability?  Create, publish, and deploy a data kit.  Create a reusable container block with common criteria.  Create a nested segment.  Create a segment and copy it for each brand. ExplanationThe most efficient option to allow for this capability is to create a reusable container block with common criteria. A container block is a segment component that can bereused across multiple segments. A container block can contain any combination of filters, nested segments, and exclusion criteria. A consultant can create a container block with the exclusion criteria that apply to all the segments managed by multiple brand teams, and then add the container block to each segment. This way, the consultant can update the exclusion criteria in one place and have them reflected in all the segments that use the container block.The other options are not the most efficient options to allow for this capability. Creating, publishing, and deploying a data kit is a way to share data and segments across different data spaces, but it does not allow for updating the exclusion criteria on a monthly basis. Creating a nested segment is a way to combine segments using logical operators, but it does not allow for excluding individuals based on specific criteria. Creating a segment and copying it for each brand is a way to create multiple segments with the same exclusion criteria, but it does not allow for updating the exclusion criteria in one place.References:* Create a Container Block* Create a Segment in Data Cloud* Create and Publish a Data Kit* Create a Nested SegmentNO.41 A consultant is integrating an Amazon 53 activated campaign with the customer’s destination system.In order for the destination system to find the metadata about the segment, which file on the 53 will contain this information for processing?  The .txt file  The json file  The .csv file  The .zip file The file on the Amazon S3 that will contain the metadata about the segment for processing is B. The json file.The json file is a metadata file that is generated along with the csv file when a segment is activated to Amazon S3. The json file contains information such as the segment name, the segment ID, the segment size, the segment attributes, the segment filters, and the segment schedule. The destination system can use this file to identify the segment and its properties, and to match the segment data with the corresponding fields in the destination system. References: Salesforce Data Cloud Consultant Exam Guide, Amazon S3 ActivationNO.42 A retailer wants to unify profiles using Loyalty ID which is different than the unique ID of their customers.Which object should the consultant use in identity resolution to perform exact match rules on the Loyalty ID?  Party Identification object  Loyalty Identification object  Individual object  Contact Identification object ExplanationThe Party Identification object is the correct object to use in identity resolution to perform exact match rules on the Loyalty ID. The Party Identification object is a child object of the Individual object that stores different types of identifiers for an individual, such as email, phone, loyalty ID, social media handle, etc. Each identifier has a type, a value, and a source. The consultant can use the Party Identification object to create a match rule that compares the Loyalty ID type and value across different sources and links the corresponding individuals.The other options are not correct objects to use in identity resolution to perform exact match rules on the Loyalty ID. The Loyalty Identification object does not exist in Data Cloud. The Individual object is the parent object that represents a unified profile of an individual, but it does not store the Loyalty ID directly. The Contact Identification objectis a child object of the Contact object that stores identifiers for a contact, such as email, phone, etc., but it does not store the Loyalty ID.References:* Data Modeling Requirements for Identity Resolution* Identity Resolution in a Data Space* Configure Identity Resolution Rulesets* Map Required Objects* Data and Identity in Data CloudNO.43 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  All individual data will be removed.  Unified customer data associated with this ruleset will be removed.  Dependencies on data model objects will be removed.  All source profile data will be removed 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 RulesetNO.44 What does the Ignore Empty Value option do in identity resolution?  Ignores empty fields when running any custom match rules  Ignores empty fields when running reconciliation rules  Ignores Individual object records with empty fields when running identity resolution rules  Ignores empty fields when running the standard match rules ExplanationThe 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 CloudNO.45 How can a consultant modify attribute names to match a naming convention in Cloud File Storage targets?  Use a formula field to update the field name in an activation.  Update attribute names in the data stream configuration.  Set preferred attribute names when configuring activation.  Update field names in the data model object. ExplanationA 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 TargetNO.46 Which operator should a consultant use to create a segment for a birthday campaign that is evaluated daily?  Is Today  Is Birthday  Is Between  Is Anniversary Of To create a segment for a birthday campaign that is evaluated daily, the consultant should use the Is Anniversary Of operator. This operator compares a date field with the current date and returns true if the month and day are the same, regardless of the year. For example, if the date field is 1990-01-01 and the current date is 2023-01-01, the operator returns true. This way, the consultant can create a segment that includes all the customers who have their birthday on the same day as the current date, and the segment will be updated daily with the new birthdays. The other options are not the best operators to use for this purpose because:* A. The Is Today operator compares a date field with the current date and returns true if the date is the same, including the year. For example, if the date field is 1990-01-01 and the current date is2023-01-01, the operator returns false. This operator is not suitable for a birthday campaign, as it will only include the customers who were born on the same day and year as the current date, which is very unlikely.* B. The Is Birthday operator is not a valid operator in Data Cloud. There is no such operator available in the segment canvas or the calculated insight editor.* C. The Is Between operator compares a date field with a range of dates and returns true if the date is within the range, including the endpoints. For example, if the date field is 1990-01-01 and the range is2022-12-25 to 2023-01-05, the operator returns true. This operator is not suitable for a birthday campaign, as it will only include the customers who have their birthday within a fixed range of dates, and the segment will not be updated daily with the new birthdays.NO.47 Which consideration related to the way Data Cloud ingests CRM data is true?  CRM data cannot be manually refreshed and must wait for the next scheduled synchronization,  The CRM Connector’s synchronization times can be customized to up to 15-minute intervals.  Formula fields are refreshed at regular sync intervals and are updated at the next full refresh.  The CRM Connector allows standard fields to stream into Data Cloud in real time. The correct answer is D. The CRM Connector allows standard fields to stream into Data Cloud in real time.This means that any changes to the standard fields in the CRM data source are reflected in Data Cloud almost instantly, without waiting for the next scheduled synchronization. This feature enables Data Cloud to have the most up-to-date and accurate CRM data for segmentation and activation1.The other options are incorrect for the following reasons:* A. CRM data can be manually refreshed at any time by clicking the Refresh button on the data stream detail page2. This option is false.* B. The CRM Connector’s synchronization times can be customized to up to 60-minute intervals, not15-minute intervals3. This option is false.* C. Formula fields are not refreshed at regular sync intervals, but only at the next full refresh4. A full refresh is a complete data ingestion process that occurs once every 24 hours or when manually triggered.This option is false.References:* 1: Connect and Ingest Data in Data Cloud article on Salesforce Help* 2: Data Sources in Data Cloud unit on Trailhead* 3: Data Cloud for Admins module on Trailhead* 4: [Formula Fields in Data Cloud] unit on Trailhead* : [Data Streams in Data Cloud] unit on TrailheadNO.48 A customer wants to use the transactional data from their data warehouse in Data Cloud.They are only able to export the data via an SFTP site.How should the file be brought into Data Cloud?  Ingest the file with the SFTP Connector.  Ingest the file through the Cloud Storage Connector.  Manually import the file using the Data Import Wizard.  Use Salesforce’s Dataloader application to perform a bulk upload from a desktop. ExplanationThe SFTP Connector is a data source connector that allows Data Cloud to ingest data from an SFTP server.The customer can use the SFTP Connector to create a data stream from their exported file and bring it into Data Cloud as a data lake object. The other options are not the best ways to bring the file into Data Cloud because:* B. The Cloud Storage Connector is a data source connector that allows Data Cloud to ingest data from cloud storage services such as Amazon S3, Azure Storage, or Google Cloud Storage. The customer does not have their data in any of these services, but only on an SFTP site.* C. The Data Import Wizard is a tool that allows users to import data for many standard Salesforce objects, such as accounts, contacts, leads, solutions, and campaign members. It is not designed to import data from an SFTP site or for custom objects in Data Cloud.* D. The Dataloader is an application that allows users to insert, update, delete, or export Salesforce records. It is not designed to ingest data from an SFTP site or into Data Cloud. References: SFTP Connector – Salesforce, Create Data Streams with the SFTP Connector in Data Cloud – Salesforce, Data Import Wizard – Salesforce, Salesforce Data LoaderNO.49 A customer wants to use the transactional data from their data warehouse in Data Cloud.They are only able to export the data via an SFTP site.How should the file be brought into Data Cloud?  Ingest the file with the SFTP Connector.  Ingest the file through the Cloud Storage Connector.  Manually import the file using the Data Import Wizard.  Use Salesforce’s Dataloader application to perform a bulk upload from a desktop. The SFTP Connector is a data source connector that allows Data Cloud to ingest data from an SFTP server.The customer can use the SFTP Connector to create a data stream from their exported file and bring it into Data Cloud as a data lake object. The other options are not the best ways to bring the file into Data Cloud because:* B. The Cloud Storage Connector is a data source connector that allows Data Cloud to ingest data from cloud storage services such as Amazon S3, Azure Storage, or Google Cloud Storage. The customer does not have their data in any of these services, but only on an SFTP site.* C. The Data Import Wizard is a tool that allows users to import data for many standard Salesforce objects, such as accounts, contacts, leads, solutions, and campaign members. It is not designed to import data from an SFTP site or for custom objects in Data Cloud.* D. The Dataloader is an application that allows users to insert, update, delete, or export Salesforce records. It is not designed to ingest data from an SFTP site or into Data Cloud. References: SFTP Connector – Salesforce, Create Data Streams with the SFTP Connector in Data Cloud – Salesforce, Data Import Wizard – Salesforce, Salesforce Data LoaderNO.50 Which method should a consultant use when performing aggregations in windows of 15 minutes on data collected via the Interaction SDK or Mobile SDK?  Batch transform  Calculated insight  Streaming insight  Formula fields ExplanationStreaming insight is a method that allows you to perform aggregations in windows of 15 minutes on data collected via the Interaction SDK or Mobile SDK. Streaming insight is a feature that enables you to create real-time metrics and insights based on streaming data from various sources, such as web, mobile, or IoT devices. Streaming insight allows you to define aggregation rules, such as count, sum, average, min, max, or percentile, and apply them to streaming data in time windows of 15 minutes. For example, you can use streaming insight to calculate the number of visitors, the average session duration, or the conversion rate for your website or app in 15-minute intervals. Streaming insight also allows you to visualize and explore the aggregated data in dashboards, charts, or tables. References: Streaming Insight, Create Streaming InsightsNO.51 How does Data Cloud handle an individual’s Right to be Forgotten?  Deletes the records from all data source objects, and any downstream data model objects are updated at the next scheduled ingestion  Deletes the specified Individual record and its Unified Individual Link record.  Deletes the specified Individual and records from any data source object mapped to the Individual data model object.  Deletes the specified Individual and records from any data model object/data lake object related to the Individual. Data Cloud handles an individual’s Right to be Forgotten by deleting the specified Individual and records from any data model object/data lake object related to the Individual. This means that Data Cloud removes all the data associated with the individual from the data space, including the data from the source objects, the unified individual profile, and any related objects. Data Cloud also deletes the Unified Individual Link record that links the individual to the source records. Data Cloud uses the Consent API to process the Right to be Forgotten requests, which are reprocessed at 30, 60, and 90 days to ensure a full deletion.The other options are not correct descriptions of how Data Cloud handles an individual’s Right to be Forgotten. Data Cloud does not delete the records from all data source objects, as this would affect the data integrity and availability of the source systems. Data Cloud also does not delete only the specified Individual record and its Unified Individual Link record, as this would leave the source records and the related records intact. Data Cloud also does not delete only the specified Individual and records from any data source object mapped to the Individual data model object, as this would leave the related records intact.References:* Requesting Data Deletion or Right to Be Forgotten* Data Deletion for Data Cloud* Use the Consent API with Data Cloud* Data and Identity in Data CloudNO.52 Northern Trail Outfitters (NTO) wants to connect their B2C Commerce data with Data Cloud and bring two years of transactional history into Data Cloud.What should NTO use to achieve this?  B2C Commerce Starter Bundles  Direct Sales Order entity ingestion  Direct Sales Product entity ingestion  B2C Commerce Starter Bundles plus a custom extract The B2C Commerce Starter Bundles are predefined data streams that ingest order and product data from B2C Commerce into Data Cloud. However, the starter bundles only bring in the last 90 days of data by default. To bring in two years of transactional history, NTO needs to use a custom extract from B2C Commerce that includes the historical data and configure the data stream to use the custom extract as the source. The other options are not sufficient to achieve this because:* A. B2C Commerce Starter Bundles only ingest the last 90 days of data by default.* B. Direct Sales Order entity ingestion is not a supported method for connecting B2C Commerce data with Data Cloud. Data Cloud does not provide a direct-access connection for B2C Commerce data, only data ingestion.* C. Direct Sales Product entity ingestion is not a supported method for connecting B2C Commerce data with Data Cloud. Data Cloud does not provide a direct-access connection for B2C Commerce data, only data ingestion. References: Create a B2C Commerce Data Bundle – Salesforce, B2C Commerce Connector – Salesforce, Salesforce B2C Commerce Pricing Plans & Costs Loading … Latest Data-Cloud-Consultant Exam Dumps Salesforce Exam from Training: https://www.dumpsmaterials.com/Data-Cloud-Consultant-real-torrent.html --------------------------------------------------- Images: https://exams.dumpsmaterials.com/wp-content/plugins/watu/loading.gif https://exams.dumpsmaterials.com/wp-content/plugins/watu/loading.gif --------------------------------------------------- --------------------------------------------------- Post date: 2024-05-30 13:37:54 Post date GMT: 2024-05-30 13:37:54 Post modified date: 2024-05-30 13:37:54 Post modified date GMT: 2024-05-30 13:37:54