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| Section | Objectives |
|---|---|
| Identity Resolution and Unification | - Unified customer profile concepts - Identity resolution rules |
| Salesforce Data Cloud Fundamentals | - Core concepts and architecture - Data Cloud value and use cases |
| Segmentation and Activation | - Activation to Salesforce and external systems - Segmentation logic and audience building |
| Data Ingestion and Data Modeling | - Data model objects and harmonization - Data sources and ingestion methods |
| Data Governance and Privacy | - Data privacy and compliance concepts - Security and data access controls |
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23. Frage
Which match criteria is only available as custom in order to perform an exact match in Identity Resolution?
Antwort: B
Begründung:
Party Identification Id is the only match criteria that is only available as custom in order to perform an exact match in Identity Resolution. Party Identification Id is a unique identifier for each Party Identification record in the data model. It is not one of the standard match criteria that Data Cloud provides out of the box, so it has to be created as a custom match criteria. Custom match criteria allow you to use any field from the data model as a match rule. Reference: Create Custom Match Criteria
24. Frage
A customer wants to create segments of users based on their Customer Lifetime Value.
However, the source data that will be brought into Data Cloud does not include that key performance indicator (KPI).
Which sequence of steps should the consultant follow to achieve this requirement?
Antwort: D
Begründung:
To create segments of users based on their Customer Lifetime Value (CLV), the sequence of steps that the consultant should follow is Ingest Data > Map Data to Data Model > Create Calculated Insight > Use in Segmentation. This is because the first step is to ingest the source data into Data Cloud using data streams1. The second step is to map the source data to the data model, which defines the structure and attributes of the data2. The third step is to create a calculated insight, which is a derived attribute that is computed based on the source or unified data3. In this case, the calculated insight would be the CLV, which can be calculated using a formula or a query based on the sales order data4. The fourth step is to use the calculated insight in segmentation, which is the process of creating groups of individuals or entities based on their attributes and behaviors. By using the CLV calculated insight, the consultant can segment the users by their predicted revenue from the lifespan of their relationship with the brand. The other options are incorrect because they do not follow the correct sequence of steps to achieve the requirement. Option B is incorrect because it is not possible to create a calculated insight before ingesting and mapping the data, as the calculated insight depends on the data model objects3. Option C is incorrect because it is not possible to create a calculated insight before mapping the data, as the calculated insight depends on the data model objects3. Option D is incorrect because it is not recommended to create a calculated insight before mapping the data, as the calculated insight may not reflect the correct data model structure and attributes3. References: Data Streams Overview, Data Model Objects Overview, Calculated Insights Overview, Calculating Customer Lifetime Value (CLV) With Salesforce, [Segmentation Overview]
25. Frage
Which of these is present in Identity Resolution Summary?
Antwort: D
Begründung:
The Identity Resolution Summary page shows all the above information: Unified Individuals, Last Processing Status, and Matched Individuals. Unified Individuals are the profiles that Data Cloud creates by linking multiple source profiles based on match rules. Last Processing Status shows the date and time of the last identity resolution run and whether it was successful or not. Matched Individuals shows the number and percentage of source profiles that were matched to a unified individual profile. References: Identity Resolution Summary
26. Frage
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?
Antwort: C
Begründung:
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
27. Frage
Which two applications automatically create activation targets at the time the application is connected to Data Cloud?
Antwort: C,D
Begründung:
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
28. Frage
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