Salesforce-Data-Cloud Practice Exam Questions with Answers Salesforce Data CloudAccredited Professional Exam (SU24) Certification

The maximum number of calculated insights that can be created per tenant is 50. A calculated insight is a metric that defines and calculates a multidimensional measure on your data. You can use calculated insights to create segments and analyze your data in Data Cloud. You can also use calculated insights to create dashboards and reports in Tableau CRM. References: Calculated Insights

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

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

This feature can help Northern Trail Outfitters calculate each customer’s lifetime value (LTV) and create breakdowns of the revenue sourced by different channels. Streaming data transformations allow you to transform and enrich streaming data from different sources using formulas and operators. References: https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_streaming_data_transform.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.c om/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

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 action should be performed to accommodate the request to delete personal data in Data Cloud. The Consent API allows you to set a consent flag for an individual that prevents further processing of their data and deletes their records from source data streams. References: https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_consent_ap i.htm&type=5

The Customer 360 data model is a conceptual model and a canonical model. A conceptual model is a high-level representation of the entities and relationships in a domain of interest, without specifying any implementation details. A canonical model is a common and consistent data model that can be used across different systems and applications. References: [Customer 360 Data Model Overview], [Conceptual Model], [Canonical Model]

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 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

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.

Numeric is the only type of measures that support aggregate functions. Measures are numeric fields that can be aggregated using functions such as SUM, AVG, MIN, MAX, or COUNT. For example, you can use a measure to calculate the total revenue or the average order value from your data. Date, Text, and Boolean are not types of measures, but types of dimensions. Dimensions are fields that can be used to group or filter data, but not to perform calculations. References: Measures and Dimensions

To track the daily transaction volume for each customer in real time and send out a notification as soon as it detects volume outside a customer’s normal range, the administrator should use a Streaming Insight paired with a Data Action. A Streaming Insight is a metric that is calculated on streaming data as it is ingested into Data Cloud, allowing near-real-time analysis of customer behavior. A Data Action is an action that is triggered by a Streaming Insight, such as sending an email, updating a record, or calling an API. By using these features, the administrator can monitor and respond to customer transactions in real time.

Reducing the number of matching rules can increase the consolidation rate for Identity Resolution, because it reduces the chances of finding multiple matches for the same individual. Matching rules tell Data Cloud which profiles to unify during the identity resolution process. If there are too many matching rules, Data Cloud might find more than one match for a given profile, resulting in a lower consolidation rate. References: Identity Resolution Match Rules

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

A Data Model Object (DMO) that inherits the name, shape, and semantics of the reference object is called a Standard DMO. A reference object is a predefined object in the Data Cloud data model that represents a common entity or concept, such as Individual, Order, or Product. A Standard DMO is a copy of a reference object that you can use to ingest data from a specific source without modifying the original reference object. A Standard DMO has the same fields and relationships as the reference object, but you can add custom fields or relationships to it if needed. References: Data Model Objects

This is the correct formula to display the value of the raw data column of “RetailPrice” plus an additional 5 percent. The formula uses the sourceField function to access the raw data column, and then multiplies it by 1.05 to add 5 percent. The formula is case-sensitive, so the column name must match exactly with the raw data column name. References: [Formula Editor], [sourceField Function]

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.c3 60_a_data_cloud_activation.htm&type=5

These two ways can help Data Cloud honor a request to be forgotten by a customer. The Consent API allows you to set a consent flag for an individual that prevents further processing of their data and deletes their records from source data streams. The delete from file functionality allows you to upload a file with individual IDs that will be deleted from Data Cloud. References: https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_consent_api.htm &type=5 https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_delete_from_file.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

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

This is how Data Cloud handles an individual’s right to be forgotten. It deletes the individual record from the Individual data model object (DMO) and any related records from the data stream objects (DSOs) that are mapped to it. References: https://help.salesforce.com/s/articleView?id=sf.c360_a_da ta_cloud_delete_individual.htm&type=5