Salesforce-Data-Cloud Salesforce Data CloudAccredited Professional Exam (SU24) Questions and Answers

 These three components of Data Cloud can be bundled within a Data Kit. A Data Kit is a package that contains data model objects, segments, and data streams that can be installed in another Data Cloud org. References: https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_data_kit.htm &type=5

These two statements are true about using consent API and exercising right to be forgotten. Data deletion requests are reprocessed at regular intervals to ensure that any new data related to the individual is deleted. Data deletion requests are submitted for individual profiles that represent unique identities in Data Cloud. References: https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_consent_api.htm &type=5

The Identity Resolution Summary page shows all the above information: Unified Individuals, Last Processing Status, and Matched Individuals. Unified Individuals are the profiles that Data Cloud creates by linking multiple source profiles based on match rules. Last Processing Status shows the date and time of the last identity resolution run and whether it was successful or not. Matched Individuals shows the number and percentage of source profiles that were matched to a unified individual profile. References: Identity Resolution Summary

When B2C Commerce Data Stream is created from the Order Bundle, 30 days of historical data is loaded. The Order Bundle is a preconfigured data bundle that contains order-related data from B2C Commerce Cloud. Data Stream is a feature that allows you to stream data from B2C Commerce Cloud to Data Cloud in near real time. References: B2C Commerce Data Stream

To pause a segment activation but with the intent of using that segment again, the administrator should stop the publish schedule for that segment. This will stop the segment from being refreshed and activated, but it will not delete or inactivate the segment. The administrator can resume the publish schedule at any time.

These two benefits Data Cloud provides a company in relation to managing customer data. Unified Identity Resolution allows a company to link data from different sources and create a single view of each customer. Data Harmonization allows a company to standardize and enrich data from different sources and improve data quality and usability. References: https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_identity_resolution.htm &type=5 https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_data_harmonization.htm &type=5

These two remedies can help resolve the error “Segment references too many Data Lake Objects (DLOs)”. Spacing out the segment schedules can reduce the concurrent load on the Data Lake Objects and improve performance. Splitting the segment into smaller segments can reduce the number of Data Lake Objects that are referenced by each segment. References: https://help.salesforce.com/s/articleView ?

Dimensions are attributes that can be used to group or filter data in calculated insights. You can include dimensions as attribute data in an activation by selecting them from the available attributes list. References: https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_calculated_insights.htm &type=5

This configuration will ensure that Data Cloud only ingests new files from the Amazon S3 bucket and updates or inserts new records into the data stream without deleting existing records. References: https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_amazon_s3.htm &type=5

These two features are impacted by the timezone setting in the org Data Cloud is provisioned in. The segment schedule determines how often a segment is refreshed based on the selected timezone. The activation schedule determines how often a segment is exported to an activation target based on the selected timezone. References: https://help.salesforce.com/s/articleView?id=sf.c360_a_segmentation_schedule.htm &type=5 https://help.salesforce.com/s/articleView?id=sf.c360_a_activation_schedule.htm &type=5

Data Cloud can address these two common use cases by providing a platform that allows customers to ingest, map, enrich, and activate data from various sources using the Customer 360 data model, and by enabling customers to create segments, insights, and activations based on their customer data. References: [Data Cloud Overview], [Customer 360 Data Model], [Data Activation]

These two applications automatically create activation targets when they are connected to Data Cloud. You can use these targets to activate segments or calculated insights to these applications. References: https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_activation.htm &type=5

These two features support the need to calculate each customer’s lifetime value (LTV) and create breakdowns of the revenue sourced by different channels. Calculated Insight allows you to create complex calculations based on stored data, such as LTV. Segment allows you to create audiences based on different criteria, such as revenue source. References: https://help.salesforce.com/s/articleView?id=sf.c360_a_calculated_insights.htm &type=5 https://help.salesforce.com/s/articleView?id=sf.c360_a_segmentation.htm &type=5

According to the Data Cloud documentation, when using two separate containers linked by an AND operator, the segment includes individuals who meet both conditions. In this case, the segment includes individuals who purchased at least one product with the color attribute equal to ‘red’, and also purchased at least one product with the primary product category attribute equal to ‘shoes’. The products do not have to be the same or in the same order line item.

This component should be recommended to achieve the goal of understanding which identified users have browsed the jobs page on their website at least twice within the last 12 hours. Streaming Insight allows you to query and filter data from real-time streams using window functions and aggregation functions. References: https://help.salesforce.com/s/articleView?id=sf.c360_a_streaming_insights.htm &type=5

You can customize the Data Cloud canonical model by adding, editing, or deleting objects, fields, and relationships. You can also modify the properties, labels, and descriptions of these components. References: https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_canonical_model.htm &type=5

Data Cloud’s primary value to customers is that it provides a platform that enables customers to create a unified view of a customer and their related data across different channels and systems, using the Customer 360 data model as the foundation. References: [Data Cloud Overview], [Customer 360 Data Model]

These three out-of-the-box connectors are available for Data Cloud. They allow you to ingest data from Marketing Cloud, B2C Commerce, or Amazon S3 into Data Cloud and map it to the Data Cloud data model. References: https://help.salesforce.com/s/articleView?id=sf.c360_a_connectors.htm &type=5

A data stream cannot be deleted if any of its attributes are mapped to a Data Model object or used in a Calculated Insight3. These dependencies need to be removed before deleting the data stream.

This is the first step to set up and configure a Data Cloud instance after it has been provisioned. The customer needs to connect to the Salesforce CRM org that Data Cloud is provisioned in, using the Salesforce CRM connector. This will allow Data Cloud to access the CRM data and map it to the Customer 360 data model. References: [Salesforce CRM Connector], [Data Cloud Setup]

These three features can be used to validate the data in the unified profile object. Data Explorer allows you to view the ingested data from different sources and how it is mapped to the unified profile object. Query API allows you to query the unified profile object using SOQL or SQL queries. Profile Explorer allows you to view the unified profile records and their attributes. References: https://help.salesforce.com/s/articleView?id=sf.c360_a_data_explorer.htm &type=5 https://help.salesforce.com/s/articleView?id=sf.c360_a_query_api.htm &type=5 https://help.salesforce.com/s/articleView?id=sf.c360_a_profile_explorer.htm &type=5

The Ignore Empty Value option is a setting for reconciliation rules, which determine the logic for data selection in a unified profile7. If this option is enabled, empty fields are ignored when applying the reconciliation rule. For example, if the rule is to select the most frequent value, and one of the values is empty, it will not be counted as a frequency.

The Source Sequence reconciliation rule allows you to sort your data sources in order of most to least preferred for inclusion in a unified profile9. For example, you can specify that data from Marketing Cloud should have higher priority than data from Service Cloud when selecting attributes such as first name or last name.

Only one metric can be present in one segment container. A segment container is a logical grouping of segments that share the same metric and granularity. A metric is a calculated insight that defines and calculates a multidimensional measure on your data. A granularity is the level of detail at which you want to analyze your data, such as daily, weekly, or monthly. You can create multiple segment containers with different metrics and granularities, but each segment container can only have one metric. References: Segment Containers