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| Section | Objectives |
|---|---|
| Topic 1: Data Ingestion and Data Modeling | - Data mapping and transformation - Data spaces and object modeling concepts - Data ingestion methods and connectors |
| Topic 2: Data Cloud Implementation and Use Cases | - Integration with Salesforce ecosystem - Common business use cases and solutions |
| Topic 3: Identity Resolution | - Profile unification and resolution process - Identity resolution rules and matching strategies |
| Topic 4: Segmentation and Activation | - Activation to downstream systems - Segment creation and audience building |
| Topic 5: Data Cloud Fundamentals | - Core concepts of Salesforce Data Cloud - Data model and architecture overview |
| Topic 6: Data Governance and Compliance | - Data access controls and permissions - Data privacy and compliance considerations |
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NEW QUESTION # 30
A user is not seeing suggested values from newly-modeled data when building a segment.
What is causing this issue?
Answer: B
Explanation:
Value suggestion is a feature that allows users to see suggested values for data model object (DMO) fields when creating segment filters. However, this feature can take up to 24 hours to process and display the values for newly-modeled data. Therefore, if a user is not seeing suggested values from newly-modeled data, it is likely that the value suggestion is still processing and will be available soon. The other options are incorrect because value suggestion does not require any specific permissions, can work on both direct and related attributes, and can return more than 50 values for a specific attribute, depending on the data type and frequency of the values. References: Use Value Suggestions in Segmentation, Data Cloud Limits and Guidelines
NEW QUESTION # 31
A Data Cloud consultant recently added a new data source and mapped some of the data to a new custom data model object (DMO) that they want to use for creating segments. However, they cannot view the newly created DMO when trying to create a new segment.
What is the cause of this issue?
Answer: D
Explanation:
The cause of this issue is that the new custom data model object (DMO) is not of category Profile. A category is a property of a DMO that defines its purpose and functionality in Data Cloud. There are three categories of DMOs: Profile, Event, and Other. Profile DMOs are used to store attributes of individuals or entities, such as name, email, address, etc. Event DMOs are used to store actions or interactions of individuals or entities, such as purchases, clicks, visits, etc. Other DMOs are used to store any other type of data that does not fit into the Profile or Event categories, such as products, locations, categories, etc. Only Profile DMOs can be used for creating segments in Data Cloud, as segments are based on the attributes of individuals or entities. Therefore, if the new custom DMO is not of category Profile, it will not appear in the segmentation canvas. The other options are not correct because they are not the cause of this issue. Data ingestion is not a prerequisite for creating segments, as segments can be created based on the data model schema without actual data. The new DMO does not need to have a relationship to the individual DMO, as segments can be created based on any Profile DMO, regardless of its relationship to other DMOs. Segmentation is not only supported for the Individual and Unified Individual DMOs, as segments can be created based on any Profile DMO, including custom ones. References: Create a Custom Data Model Object from an Existing Data Model Object, Create a Segment in Data Cloud, Data Model Object Category
NEW QUESTION # 32
Which method should a consultant use when performing aggregations in windows of 15 minutes on data collected via the Interaction SDK or Mobile SDK?
Answer: D
Explanation:
Streaming insight is a method that allows you to perform aggregations in windows of 15 minutes on data collected via the Interaction SDK or Mobile SDK. Streaming insight is a feature that enables you to create real-time metrics and insights based on streaming data from various sources, such as web, mobile, or IoT devices. Streaming insight allows you to define aggregation rules, such as count, sum, average, min, max, or percentile, and apply them to streaming data in time windows of 15 minutes. For example, you can use streaming insight to calculate the number of visitors, the average session duration, or the conversion rate for your website or app in 15-minute intervals. Streaming insight also allows you to visualize and explore the aggregated data in dashboards, charts, or tables. Reference: Streaming Insight, Create Streaming Insights
NEW QUESTION # 33
The leadership team at Cumulus Financial has determined that customers who deposited more than $250,000 in the last five years and are not using advisory services will be the central focus for all new campaigns in the next year.
Which features support this use case?
Answer: A
Explanation:
* Understanding the Use Case:
The leadership team wants to focus on customers who have deposited more than $250,000 in the last five years and are not using advisory services.
Reference:
* Features Involved:
Calculated Insight: This feature helps derive metrics and values based on existing data. In this case, it can calculate total deposits over the last five years.
Segment: Segmentation allows targeting specific groups of customers based on defined criteria, such as total deposits and usage of advisory services.
* Steps to Implement:
Create a Calculated Insight:
Navigate to Visual Insights Builder in Salesforce Data Cloud.
Create a new calculated insight to sum deposits for each customer over the last five years.
Create a Segment:
Use the Segment Canvas to create a new segment.
Apply filters to include customers with deposits over $250,000 and exclude those using advisory services.
* Practical Application:
Example: Identify high-value customers who are not leveraging additional services and target them with personalized marketing campaigns to promote advisory services.
NEW QUESTION # 34
A consultant is setting up Data Cloud for a multi-brand organization and is using data spaces to segregate its data for various brands.
While starting the mapping of a data stream, the consultant notices that they cannot map the object for one of the brands.
What should the consultant do to make the object available for a new data space?
Answer: D
NEW QUESTION # 35
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