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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Act on Data | 18% | - Use attributes and related attributes - Define activations and their basic use cases - Use data actions and identify their requirements and intended use cases - Troubleshoot common problems with activations - Identify and analyze timing dependencies affecting the Data Cloud lifecycle |
| Topic 2: Data Ingestion and Modeling | 20% | - Transformation capabilities (streaming and batch) - Inspect and validate ingested and modeled data - Data ingestion from different sources into Data Cloud - Define, map, and model data for identity resolution |
| Topic 3: Segmentation and Insights | 18% | - Configure, refine, and maintain segments within Data Cloud - Identify scenarios for analyzing segment membership - Define basic concepts of segmentation and use cases - Identify and differentiate between calculated and streaming insights |
| Topic 4: Solution Overview | 18% | - Identify typical use cases for Data Cloud - Articulate how Data Cloud works and its dependencies - Describe and apply the principles of data ethics - Describe Data Cloud's function, key terminology, and business value |
| Topic 5: Identity Resolution | 14% | - Reconcile data and rule sets - Matching and rule sets |
| Topic 6: Data Cloud Setup and Administration | 12% | - Manage and administer Data Cloud using reports, dashboards, flows, packaging, and data kits - Apply Data Cloud permissions, permission sets, and org-wide settings - Identify use cases for data spaces and create data spaces based on requirements - Diagnose and explore data using Data Explorer, Profile Explorer, and APIs - Describe and configure the available data stream types and data bundles |
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NEW QUESTION # 138
Northern Trail Outfitters (NTO) is getting ready to start ingesting its CRM data into Data Cloud.
While setting up the connector, which type of refresh should NTO expect when the data stream is deployed for the first time?
Answer: C
Explanation:
Data Stream Deployment: When setting up a data stream in Salesforce Data Cloud, the initial deployment requires a comprehensive data load.
Types of Refreshes:
Incremental Refresh: Only updates with new or changed data since the last refresh.
Manual Refresh: Requires a user to manually initiate the data load.
Partial Refresh: Only a subset of the data is refreshed.
Full Refresh: Loads the entire dataset into the system.
First-Time Deployment: For the initial deployment of a data stream, a full refresh is necessary to ensure all data from the source system is ingested into Salesforce Data Cloud.
References:
Salesforce Documentation: Data Stream Setup
Salesforce Data Cloud Guide
NEW QUESTION # 139
A customer has outlined requirements to trigger a journey for an abandoned browse behavior. Based on the requirements, the consultant determines they will use streaming insights to trigger a data action to Journey Builder every hour.
How should the consultant configure the solution to ensure the data action is triggered at the cadence required?
Answer: D
Explanation:
Explanation:
NEW QUESTION # 140
A consultant is ingesting a list of employees from their human resources database that they want to segment on.
Which data stream category should the consultant choose when ingesting this data?
Answer: C
Explanation:
Categories of Data Streams:
Profile Data: Customer profiles and demographic information.
Contact Data: Contact points like email and phone numbers.
Other Data: Miscellaneous data that doesn't fit into the other categories.
Engagement Data: Interactions and behavioral data.
Reference: Salesforce Data Stream Categories
Ingesting Employee Data:
Employee data typically doesn't fit into profile, contact, or engagement categories meant for customer data.
"Other Data" is appropriate for non-customer-specific data like employee information.
Reference: Salesforce Data Ingestion Guide
Steps to Ingest Employee Data:
Navigate to the data ingestion settings in Salesforce Data Cloud.
Select "Create New Data Stream" and choose the "Other Data" category.
Map the fields from the HR database to the corresponding fields in Data Cloud.
Reference: Salesforce Data Ingestion Tutorial
Practical Application:
Example: A company ingests employee data to segment internal communications or analyze workforce metrics.
Choosing the "Other Data" category ensures that this non-customer data is correctly managed and utilized.
Reference: Salesforce Data Management Case Studies
NEW QUESTION # 141
A consultant wants to make sure address details from customer orders are selected as best to save to the unified profile.
What should the consultant do to achieve this?
Answer: D
Explanation:
Unified Profile: Creating a unified customer profile in Salesforce Data Cloud involves consolidating data from various sources.
Reconciliation Rules: These rules determine which data source is considered the "best" when conflicting data is encountered. Changing reconciliation rules allows prioritizing specific sources.
Source Priority: Setting source priority involves defining which data source should be preferred over others for specific attributes.
Process:
Step 1: Access the Data Cloud settings for reconciliation rules.
Step 2: Select the Contact Point Address details.
Step 3: Change the reconciliation rules for address attributes to "Source Priority." Step 4: Move the Order DMO to the top of the priority list. This ensures that address details from customer orders are prioritized and selected as the best data to save to the unified profile.
Benefits:
Accuracy: Ensures the most accurate and reliable address data is used in the unified profile.
Relevance: Gives priority to the most relevant and frequently updated source (customer orders).
References:
Salesforce Data Cloud Reconciliation Rules
Salesforce Unified Customer Profile
NEW QUESTION # 142
A customer has a Master Customer table from their CRM to ingest into Data Cloud. The table contains a name and primary email address, along with other personally Identifiable information (Pll).
How should the fields be mapped to support identity resolution?
Answer: D
Explanation:
To support identity resolution in Data Cloud, the fields from the Master Customer table should be mapped to the standard data model objects that are designed for this purpose. The Individual object is used to store the name and other personally identifiable information (PII) of a customer, while the Contact Phone Email object is used to store the primary email address and other contact information of a customer. These objects are linked by a relationship field that indicates the contact information belongs to the individual. By mapping the fields to these objects, Data Cloud can use the identity resolution rules to match and reconcile the profiles from different sources based on the name and email address fields. The other options are not recommended because they either create a new custom object that is not part of the standard data model, or map all fields to the Customer object that is not intended for identity resolution, or map all fields to the Individual object that does not have a standard email address field. References: Data Modeling Requirements for Identity Resolution, Create Unified Individual Profiles
NEW QUESTION # 143
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