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| Section | Weight | Objectives |
|---|---|---|
| Calculated Insights | 8% | - Define metrics and measurements - Publish insights to Data Cloud - Create and configure calculated insights - Use formulas and functions in calculations |
| Data Model Setup and Configuration | 15% | - Map source data to harmonized data model - Configure custom objects, fields, and relationships - Understand data types and field mapping - Set up and configure Data Lake objects - Describe Harmonized Data Model concepts |
| Data Sharing and Security | 8% | - Implement row-level security - Understand data governance requirements - Configure data sharing settings - Manage user access and permissions |
| Identity Resolution and Data Unification | 17% | - Configure contact and account matching - Manage data overlap and deduplication - Configure identity resolution rules - Understand unified records creation - Configure match rules and strategies |
| Data Actions | 8% | - Configure data sync to external systems - Create and manage data bundles - Set up segmentation and target audiences - Configure data actions for activation |
| Data Ingestion | 15% | - Configure batch data ingestion - Configure data sync and refresh schedules - Set up and manage data connectors - Configure streaming data ingestion - Troubleshoot ingestion issues |
| Data Cloud Overview and Licensing | 7% | - Explain licensing model and capacity - Describe Data Cloud setup and configuration - Describe the business value of Data Cloud |
| Data Cloud Monitoring and Troubleshooting | 22% | - Monitor data ingestion and sync status - Manage data retention and cleanup - Debug common configuration errors - Analyze identity resolution results - Troubleshoot data quality issues - Use Data Cloud analytics and reports |
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NEW QUESTION # 102
Northern Trail Outfitters (NTO) wants to connect their B2C Commerce data with Data Cloud and bring two years of transactional history into Data Cloud.
What should NTO use to achieve this?
Answer: A
Explanation:
The B2C Commerce Starter Bundles are predefined data streams that ingest order and product data from B2C Commerce into Data Cloud. However, the starter bundles only bring in the last 90 days of data by default. To bring in two years of transactional history, NTO needs to use a custom extract from B2C Commerce that includes the historical data and configure the data stream to use the custom extract as the source. The other options are not sufficient to achieve this because:
A . B2C Commerce Starter Bundles only ingest the last 90 days of data by default.
B . Direct Sales Order entity ingestion is not a supported method for connecting B2C Commerce data with Data Cloud. Data Cloud does not provide a direct-access connection for B2C Commerce data, only data ingestion.
C . Direct Sales Product entity ingestion is not a supported method for connecting B2C Commerce data with Data Cloud. Data Cloud does not provide a direct-access connection for B2C Commerce data, only data ingestion. Reference: Create a B2C Commerce Data Bundle - Salesforce, B2C Commerce Connector - Salesforce, Salesforce B2C Commerce Pricing Plans & Costs
NEW QUESTION # 103
A Data Cloud Consultant Is in the process of setting up data streams for a new service-based data source.
When ingesting Case data, which field is recommended to be associated with the Event Time field?
Answer: A
Explanation:
The Event Time field is a special field type that captures the timestamp of an event in a data stream. It is used to track the chronological order of events and to enable time-based segmentation and activation. When ingesting Case data, the recommended field to be associated with the Event Time field is the Last Modified Date field. This field reflects the most recent update to the case and can be used to measure the case duration, resolution time, and customer satisfaction. The other fields, such as Resolution Date, Escalation Date, or Creation Date, are not as suitable for the Event Time field, as they may not capture the latest status of the case or may not be applicable for all cases. References: Data Stream Field Types, Salesforce Data Cloud Exam Questions
NEW QUESTION # 104
Which information is provided in a .csv file when activating to Amazon S3?
Answer: B
Explanation:
When activating to Amazon S3, the information that is provided in a .csv file is the activated data payload. The activated data payload is the data that is sent from Data Cloud to the activation target, which in this case is an Amazon S3 bucket1. The activated data payload contains the attributes and values of the individuals or entities that are included in the segment that is being activated2. The activated data payload can be used for various purposes, such as marketing, sales, service, or analytics3. The other options are incorrect because they are not provided in a .csv file when activating to Amazon S3. Option A is incorrect because an audit log is not provided in a .csv file, but it can be viewed in the Data Cloud UI under the Activation History tab4. Option C is incorrect because the metadata regarding the segment definition is not provided in a .csv file, but it can be viewed in the Data Cloud UI under the Segmentation tab5. Option D is incorrect because the manifest of origin sources within Data Cloud is not provided in a .csv file, but it can be viewed in the Data Cloud UI under the Data Sources tab. References: Data Activation Overview, Create and Activate Segments in Data Cloud, Data Activation Use Cases, View Activation History, Segmentation Overview, [Data Sources Overview]
NEW QUESTION # 105
A consultant is reviewing a recent activation using engagement-based related attributes but is not seeing any related attributes in their payload for the majority of their segment members.
Which two areas should the consultant review to help troubleshoot this issue?
Choose 2 answers
Answer: C,D
Explanation:
Engagement-based related attributes are attributes that describe the interactions of a person with an email message, such as opens, clicks, unsubscribes, etc. These attributes are stored in the Engagement data model object (DMO) and can be added to an activation to send more personalized communications. However, there are some considerations and limitations when using engagement-based related attributes, such as:
For engagement data, activation supports a 90-day lookback window. This means that only the attributes from the engagement events that occurred within the last 90 days are considered for activation. Any records outside of this window are not included in the activation payload. Therefore, the consultant should review the event time of the related engagement events and make sure they are within the lookback window.
The correct path to the related attributes must be selected for the activation. A path is a sequence of DMOs that are connected by relationships in the data model. For example, the path from Individual to Engagement is Individual -> Email -> Engagement. The path determines which related attributes are available for activation and how they are filtered. Therefore, the consultant should review the path selection and make sure it matches the desired related attributes and filters.
The other two options are not relevant for this issue. The activations can reference segments that segment on profile data rather than engagement data, as long as the activation target supports related attributes. The activated profiles do not need to have a Unified Contact Point, which is a unique identifier for a person across different data sources, to activate engagement-based related attributes. References: Add Related Attributes to an Activation, Related Attributes in Data Cloud activation have no values, Explore the Engagement Data Model Object
NEW QUESTION # 106
A new user of Data Cloud only needs to be able to review individual rows of ingested data and validate that it has been modeled successfully to its linked data model object. The user will also need to make changes if required.
What is the minimum permission set needed to accommodate this use case?
Answer: B
Explanation:
The Data Cloud User permission set is the minimum permission set needed to accommodate this use case. The Data Cloud User permission set grants access to the Data Explorer feature, which allows the user to review individual rows of ingested data and validate that it has been modeled successfully to its linked data model object. The user can also make changes to the data model object fields, such as adding or removing fields, changing field types, or creating formula fields. The Data Cloud User permission set does not grant access to other Data Cloud features or tasks, such as creating data streams, creating segments, creating activations, or managing users. The other permission sets are either too restrictive or too permissive for this use case. The Data Cloud for Marketing Specialist permission set only grants access to the segmentation and activation features, but not to the Data Explorer feature. The Data Cloud Admin permission set grants access to all Data Cloud features and tasks, including the Data Explorer feature, but it is more than what the user needs. The Data Cloud for Marketing Data Aware Specialist permission set grants access to the Data Explorer feature, but also to the segmentation and activation features, which are not required for this use case. Reference: Data Cloud Standard Permission Sets, Data Explorer, Set Up Data Cloud Unit
NEW QUESTION # 107
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