Salesforce-Data-Cloud Salesforce Data CloudAccredited Professional Exam (SP25) Free Practice Exam Questions (2025 Updated)

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.

These two remedies can help resolve the error “Segment references too many Data Lake Objects (DLOs)”. Spacing out the segmentschedules 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 ?

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 datafrom real-time streams using window functions. References:https://help.salesforce.com/s/articleView?id=sf.c360_a _streaming_insights.htm&type=5

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

According to the Salesforce Data Clouddocumentation1, 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.

The Source Sequence reconciliation rule allows you to sort your data sources in order of most to least preferred forinclusion 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.

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

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 three features can be used to validate the data in the unified profile object. Data Explorer allowsyou 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 andtheir 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=5https://help.salesforce.com/s/articleView?id=sf.c360_a_profile_explorer.htm &type=5

This operator can be used to create a segment for a birthday campaign that is evaluated daily. It compares a date attribute to the current date and returns true if they have the same month and day, regardless of the year. References:https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_segmentation_operators.htm &type=5

These two requirements are needed when using the Visual Insights Builder to create a Calculated Insight. A dimension is an attribute that can be used to group or filter data, such as product category or customer segment. A measure is an attribute that can be used toperform calculations, such as revenue or quantity.References:https://help.salesforce.com/s/articleView?id=sf.c360_a_calculated_insights_create.h tm&type=5

One possible reason why a new custom field is not available inthe data stream is that the Salesforce Integration User, which is used to connect to the CRM source, does not have “Read”permissions on that field2. To fix this issue, the administrator needs to grant the appropriate permissions to the Integration User profile or permission set.

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]

COALESCE is the function that returns the first value from a list that isn’t empty. It takes a list of values asarguments and returns the first non-empty value. For example, COALESCE(NULL, ‘’, ‘Hello’, ‘World’) returns ‘Hello’. If all values are empty, it returns NULL. References: COALESCE

This platform is going to present a challenge in terms of connection limits forData Cloud. Data Cloud supports up to 3 Marketing Cloud connections per org, which means that only 3 Marketing Cloud accounts can be connected as data sources or activation targets. The other platforms have higher or no limits for connections. References:https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_limits.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 thefrequency of the query execution. References:https://help.salesforce.com/s/articleView?id=sf.c360_a_streaming_insigh ts.htm&type=5

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.

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 datato 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 Data Cloud documentation, when using two separatecontainers 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.