Salesforce-Data-Cloud Sample Questions Answers

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 create segments of users based on their Customer Lifetime Value, the customer needs to first ingest the source data into Data Cloud, then map the data to the Customer 360 data model, then create a calculated insight using the formula editor, and finally use the calculated insight in segmentation. References: [Data Ingestion], [Data Mapping], [Calculated Insights], [Segmentation]

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.

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 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 custom ‘Customer_Email_c’ object related to the standard ‘Contact’ object in Salesforce CRM 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]

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 party subject area should be used for any organization, individual, or member in the Customer 360 data model. It includes information such as name, address, email, phone, and loyalty membership. References: https://help.salesforce.com/s/articleView?id=sf.c360_a_data_clou d_party.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

The Unified Individual entity represents the result of Identity Resolution, which links together multiple records of an individual from different sources into a single profile4. This entity can be used for Segmentation and Activation, as it provides a complete and accurate view of each customer.

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.

To create a multi-dimensional metric to identify unified individual lifetime value (LTV), the administrator needs to join the following data model objects (DMOs) in the Calculated Insight:

• Unified Individual: This DMO represents the unified profile of an individual, which contains attributes from multiple sources.
• Unified Link Individual: This DMO represents the link between an Individual DMO and a Unified Individual DMO.
• Sales Order: This DMO represents a transaction or purchase made by an individual.

The sequence of joins should start from the Unified Individual DMO, then join the Unified Link Individual DMO using the UnifiedIndividualId field, and then join the Sales Order DMO using the IndividualId field. This way, the administrator can access the sales order data for each unified individual and calculate their lifetime value.

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

These are the three data categories to select from when setting up the data source object or schema for data ingestion. Engagement data includes information about how customers interact with a brand or product, such as clicks, views, likes, etc. Order data includes information about transactions or purchases made by customers, such as order ID, amount, date, etc. Profile data includes information about customers’ attributes or preferences, such as name, email, gender, etc. References: [Data Categories]

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_insigh ts.htm&type=5

This permission set should be assigned to a user who needs permissions to access Data Cloud to create, manage, and publish segments, but not to create reports or manage data sources. This permission set allows the user to create and edit segments, calculated insights, streaming insights, and activations, but not to access data streams, data model, identity resolution, or reports. References: https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_permission_sets.htm &type=5

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.

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

If no file name is specified in AWS S3 data stream during ingestion, the system does not fetch any file and the data stream shows an error. AWS S3 data stream is a feature that allows you to stream data from Amazon Web Services Simple Storage Service (AWS S3) to Data Cloud in near real time. You need to specify the file name or prefix of the files that you want to ingest from your S3 bucket. If you leave this field blank, the system cannot find any matching files and returns an error message. References: AWS S3 Data Stream

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 ?

The relationship between Individual and Contact Point Objects is 1: Many. This means that one Individual can have many Contact Points, such as email addresses, phone numbers, or postal addresses, but each Contact Point can only belong to one Individual. References: Data Model Overview

The type of the Event Time Field while ingesting Engagement data should be Immutable. Immutable means that the field value cannot be changed once it is ingested. The Event Time Field is a mandatory field for Engagement data that represents the timestamp of when an event occurred. It is important to keep this field immutable to ensure the accuracy and consistency of the event data. References: Engagement Data Model

These two steps are required when configuring a Marketing Cloud activation. You need to select an activation target that represents a Marketing Cloud business unit and a contact point that represents a Marketing Cloud data extension. References: https://help.sales force.com/s/articleView?id=sf.c360_a_data_cloud_marketing_cloud.htm&type=5