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NEW QUESTION # 85
What is the result of a segmentation criteria filtering on City | Is Equal To | 'San Jose'?
Answer: B
Explanation:
The result of a segmentation criteria filtering on City | Is Equal To | 'San Jose' is cities only containing 'San Jose' or 'san jose'. This is because the segmentation criteria is case-sensitive and accent-sensitive, meaning that it will only match the exact value that is entered in the filter1. Therefore, cities containing 'San Jose', 'san jose', or 'San Jose' will not be included in the result, as they do not match the filter value exactly. To include cities with different variations of the name 'San Jose', you would need to use the OR operator and add multiple filter values, such as 'San Jose' OR 'San Jose' OR 'san jose' OR 'san jose'2. Reference: Segmentation Criteria, Segmentation Operators
NEW QUESTION # 86
A user wants to be able to create a multi-dimensional metric to identify unified individual lifetime value (LTV).
Which sequence of data model object (DMO) joins is necessary within the calculated Insight to enable this calculation?
Answer: B
Explanation:
To create a multi-dimensional metric to identify unified individual lifetime value (LTV), the sequence of data model object (DMO) joins that is necessary within the calculated Insight is Unified Individual > Unified Link Individual > Sales Order. This is because the Unified Individual DMO represents the unified profile of an individual or entity that is created by identity resolution1. The Unified Link Individual DMO represents the link between a unified individual and an individual from a source system2. The Sales Order DMO represents the sales order information from a source system3. By joining these three DMOs, you can calculate the LTV of a unified individual based on the sales order data from different source systems. The other options are incorrect because they do not join the correct DMOs to enable the LTV calculation. Option B is incorrect because the Individual DMO represents the source profile of an individual or entity from a source system, not the unified profile4. Option C is incorrect because the join order is reversed, and you need to start with the Unified Individual DMO to identify the unified profile. Option D is incorrect because it is missing the Unified Link Individual DMO, which is needed to link the unified profile with the source profile. Reference: Unified Individual Data Model Object, Unified Link Individual Data Model Object, Sales Order Data Model Object, Individual Data Model Object
NEW QUESTION # 87
A Data Cloud consultant is working with data that is clean and organized. However, the various schemas refer to a person by multiple names - such as user; contact, and subscriber - and need a standard mapping.
Which term describes the process of mapping these different schema points into a standard data model?
Answer: C
Explanation:
Introduction to Data Harmonization:
Data harmonization is the process of bringing together data from different sources and making it consistent.
Reference: Salesforce Data Harmonization Overview
Mapping Different Schema Points:
In Data Cloud, different schemas may refer to the same entity using different names (e.g., user, contact, subscriber).
Harmonization involves standardizing these different terms into a single, consistent schema.
Reference: Salesforce Schema Mapping Guide
Process of Harmonization:
Identify Variations: Recognize the different names and fields referring to the same entity across schemas.
Standard Mapping: Create a standard data model and map the various schema points to this model.
Example: Mapping "user", "contact", and "subscriber" to a single standard entity like "Customer." Reference: Salesforce Data Model Harmonization Documentation Steps to Harmonize Data:
Define a standard data model.
Map the fields from different schemas to this standard model.
Ensure consistency across the data ecosystem.
Reference: Salesforce Data Harmonization Best Practices
NEW QUESTION # 88
Which two dependencies need to be removed prior to disconnecting a data source?
Choose 2 answers
Answer: A,C
Explanation:
Dependencies in Data Cloud:
Before disconnecting a data source, all dependencies must be removed to prevent data integrity issues.
Reference: Salesforce Data Source Management Documentation
Identifying Dependencies:
Segment: Segments using data from the source must be deleted or reassigned.
Data Stream: The data stream must be disconnected, as it directly relies on the data source.
Reference: Salesforce Segment and Data Stream Management Guide
Steps to Remove Dependencies:
Remove Segments:
Navigate to the Segmentation interface in Salesforce Data Cloud.
Identify and delete segments relying on the data source.
Disconnect Data Stream:
Go to the Data Stream settings.
Locate and disconnect the data stream associated with the source.
Reference: Salesforce Segment Deletion and Data Stream Disconnection Tutorial Practical Application:
Example: When preparing to disconnect a legacy CRM system, ensure all segments and data streams using its data are properly removed or migrated.
Reference: Salesforce Data Source Disconnection Best Practices
NEW QUESTION # 89
Which solution provides an easy way to ingest Marketing Cloud subscriber profile attributes into Data Cloud on a daily basis?
Answer: D
Explanation:
The solution that provides an easy way to ingest Marketing Cloud subscriber profile attributes into Data Cloud on a daily basis is the Marketing Cloud Data extension Data Stream. The Marketing Cloud Data extension Data Stream is a feature that allows customers to stream data from Marketing Cloud data extensions to Data Cloud data spaces. Customers can select which data extensions they want to stream, and Data Cloud will automatically create and update the corresponding data model objects (DMOs) in the data space. Customers can also map the data extension fields to the DMO attributes using a user interface or an API. The Marketing Cloud Data extension Data Stream can help customers ingest subscriber profile attributes and other data from Marketing Cloud into Data Cloud without writing any code or setting up any complex integrations.
The other options are not solutions that provide an easy way to ingest Marketing Cloud subscriber profile attributes into Data Cloud on a daily basis. Automation Studio and Profile file API are tools that can be used to export data from Marketing Cloud to external systems, but they require customers to write scripts, configure file transfers, and schedule automations. Marketing Cloud Connect API is an API that can be used to access data from Marketing Cloud in other Salesforce solutions, such as Sales Cloud or Service Cloud, but it does not support streaming data to Data Cloud. Email Studio Starter Data Bundle is a data kit that contains sample data and segments for Email Studio, but it does not contain subscriber profile attributes or stream data to Data Cloud.
Reference:
Marketing Cloud Data Extension Data Stream
Data Cloud Data Ingestion
[Marketing Cloud Data Extension Data Stream API]
[Marketing Cloud Connect API]
[Email Studio Starter Data Bundle]
NEW QUESTION # 90
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