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

These data sources are available from Marketing Cloud as a starter bundle. They provide basic contact data, such as email address, mobile number, and device ID, as well as engagement data, such as email opens, clicks, bounces, unsubscribes, SMS sends, deliveries, opt-outs, and push sends, opens, and opt-outs. References: https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_marketing_cloud_data_foundation.htm &type=5

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

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

Calculated Insights are predefined and calculated metrics that can help you build segments. Some of the benefits of Calculated Insights over Segmentation Operators are:

• Calculated Insights are better suited for non-trivial calculations, such as calculating a Net Promoter Score as a percentage, which would require multiple steps and operators in segmentation.
• Calculated Insights can query engagement data greater than 2 years, while segmentation operators are limited to 2 years of engagement data.
• Calculated Insights are better suited for complex queries over multiple objects, such as joining data from different sources or aggregating data across different levels.

This is the first thing a business stakeholder should focus on when considering a Data Cloud implementation. Obtaining cross-organizational buy-in involves aligning the goals and expectations of different teams and stakeholders who will use or contribute to Data Cloud. References: https://trailhead.salesforce.com/content/learn/modules/customer-data-platform-basics/get-started-with-customer-data-platform

According to the Data Cloud documentation, segments can only be created on the Unified Individual entity, which represents the result of Identity Resolution. The other data model object categories, such as Profile, Engagement, and Other, are not available for segmentation.

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

The Email field from a CRM Contact object should be mapped to the Contact Point Email entity in the Customer 360 data model. This entity represents an email address that is associated with an individual or an account contact. References: [Contact Point Email Entity]

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

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

This permission setting should be checked if the custom CRM object is not available in New Data Stream configuration. The user who connects the Salesforce CRM connector must have View All permission for the custom object in the source CRM org. References: https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_salesforce_crm.htm &type=5

This method should be used when performing aggregations in windows of 15 minutes on data collected via the Interactions SDK and Mobile SDK. Streaming Insight allows you to query and aggregate data from real-time streams using window functions. References: https://help.salesforce.com/s/articleView?id=sf.c360_a_streaming_insights.htm &type=5

The transaction data stream category should be assigned to use the data for time-based operations in segmentation and calculated insights. This category indicates that the data stream contains events that occur at a specific point in time and have a duration. References: https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_data_stream_category.htm &type=5

You can modify the attribute names in the data model by editing the field label or API name of the corresponding field. This will change how the attribute name appears in the Cloud File Storage target. References: https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_data_model.htm &type=5

To create a Cloud File Storage activation target, you need to provide access and secret keys for authentication5. These keys are generated by your cloud storage provider, such as Amazon S3 or Google Cloud Storage.

The Salesforce CRM connector supports ingestion of standard objects and custom objects from Salesforce CRM. Standard objects are predefined objects that are included with Salesforce CRM, such as Account, Contact, Lead, etc. Custom objects are objects that customers can create to store information that is specific to their organization or industry. References: [Salesforce CRM Connector], [Standard Objects], [Custom Objects]

These two phases are distinct phases of data model management in Data Cloud. Data ingestion is the process of bringing data from different sources into Data Cloud using connectors or APIs. Data modeling is the process of mapping the ingested data to the Data Cloud canonical model or creating custom data model objects. References: https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_data_model.htm &type=5

The data types can be changed during ingestion before the Data Source Object (DSO) is created. A DSO is a container for ingested data that defines the schema, format, and metadata of the data. Data types can be changed in the Data Explorer before creating a DSO by using the Edit Schema option. Once a DSO is created, the data types cannot be changed. References: Create a Data Source Object

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.

The data streams that use the Marketing Cloud Connector refresh data using Marketing Cloud’s Automation Studio. The Marketing Cloud Connector is a feature that allows you to stream data from Marketing Cloud to Data Cloud in near real time. The connector uses Automation Studio to schedule and run data extracts from Marketing Cloud data extensions and send them to Data Cloud via SFTP. You can configure the frequency and time of the data extracts in Automation Studio. References: Marketing Cloud Connector

The maximum limit of the number of records for Full Refresh Extract Method is 10 million. Full Refresh Extract Method is an option for extracting data from Marketing Cloud to Data Cloud. It extracts all records from a data extension regardless of when they were created or modified. If the number of records exceeds 10 million, an error occurs and no records are extracted. References: Extract Methods

According to the Salesforce Data Cloud documentation1, the timezone used for Segmentation and Activation is the one set by the Salesforce Data Cloud org, not by the individual user or admin. This ensures consistency and accuracy across different users and regions.

A window function is a unique requirement of a Streaming Insight query. It defines the time interval for the query to run on the streaming data and the frequency of the query execution. References: https://help.salesforce.com/s/articleView?id=sf.c360_a_streaming_insights.htm &type=5

A window function is a unique requirement of a Streaming Insight query. It defines the time interval for the query to run on the streaming data and the frequency of the query execution. References: https://help.salesforce.com/s/articleView?id=sf.c360_a_streaming_insights.htm &type=5