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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Segmentation and Insights | 18% | - Segment creation and configuration - Insight implementation - Segment membership analysis - Calculated vs streaming insights |
| Topic 2: Data Cloud Overview | 18% | - Architecture and ecosystem - Core concepts and terminology - Business value and use cases |
| Topic 3: Act on Data | 18% | - Troubleshooting activations - Activation concepts and use cases - Attribute usage and management - Process automation and triggering |
| Topic 4: Data Cloud Setup and Administration | 12% | - Data spaces and configuration - Monitoring and maintenance tools - Permissions and access control - Data streams and data bundles |
| Topic 5: Data Ingestion and Modeling | 20% | - Data modeling best practices - Data validation and inspection - Transformation and mapping - Ingestion from various sources |
| Topic 6: Identity Resolution | 14% | - Unified profile creation - Conflict resolution - Matching and reconciliation rules - Identity use cases |
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NEW QUESTION # 111
Which two steps are required when configuring a Marketing Cloud activation?
Answer: B,D
Explanation:
These two steps are required when configuring a Marketing Cloud activation. You need to select an activation target that represents a Marketing Cloud business unit and a contact point that represents a Marketing Cloud data extension.References:https://help.salesforce.com/s/articleView?id=sf.
c360_a_data_cloud_marketing_cloud.htm&type=5
NEW QUESTION # 112
A customer notices that their consolidation rate has recently increased. They contact the consultant to ask why.
What are two likely explanations for the increase?
Choose 2 answers
Answer: A,B
Explanation:
The consolidation rate is a metric that measures the amount by which source profiles are combined to produce unified profiles in Data Cloud, calculated as 1 - (number of unified profiles / number of source profiles). A higher consolidation rate means that more source profiles are matched and merged into fewer unified profiles, while a lower consolidation rate means that fewer source profiles are matched and more unified profiles are created. There are two likely explanations for why the consolidation rate has recently increased for a customer:
New data sources have been added to Data Cloud that largely overlap with the existing profiles. This means that the new data sources contain many profiles that are similar or identical to the profiles from the existing data sources. For example, if a customer adds a new CRM system that has the same customer records as their old CRM system, the new data source will overlap with the existing one. When Data Cloud ingests the new data source, it will use the identity resolution ruleset to match and merge the overlapping profiles into unified profiles, resulting in a higher consolidation rate.
Identity resolution rules have been added to the ruleset to increase the number of matched profiles. This means that the customer has modified their identity resolution ruleset to include more match rules or more match criteria that can identify more profiles as belonging to the same individual. For example, if a customer adds a match rule that matches profiles based on email address and phone number, instead of just email address, the ruleset will be able to match more profiles that have the same email address and phone number, resulting in a higher consolidation rate.
Identity Resolution Calculated Insight: Consolidation Rates for Unified Profiles, Configure Identity Resolution Rulesets
NEW QUESTION # 113
When setting up the data source object or schema for data ingestion, what are the three data categories to select from?
Answer: B,D,E
Explanation:
These are the three data categories to select from when setting up the data source object or schema for data ingestion. Engagement data includes information about how customers interact with a brand or product, such as clicks, views, likes, etc. Order data includes information about transactions or purchases made by customers, such as order ID, amount, date, etc. Profile data includes information about customers' attributes or preferences, such as name, email, gender, etc. Reference: [Data Categories]
NEW QUESTION # 114
Which two common use cases can be addressed with Data Cloud?
Answer: C,D
Explanation:
Data Cloud can address these two common use cases by providing a platform that allows customers to ingest, map, enrich, and activate data from various sources using the Customer 360 data model, and by enabling customers to create segments, insights, and activations based on their customer data. Reference: [Data Cloud Overview], [Customer 360 Data Model], [Data Activation]
NEW QUESTION # 115
Cloud Kicks plans to do a full deletion of one of its existing data streams and its underlying data lake object (DLO).
What should the consultant consider before deleting the data stream?
Answer: C
Explanation:
Data Streams and DLOs: In Salesforce Data Cloud, data streams are used to ingest data, which is then stored in Data Lake Objects (DLOs).
Deletion Considerations: Before deleting a data stream, it's crucial to consider the dependencies and usage of the underlying DLO.
Data Transform Usage:
Impact of Deletion: If the underlying DLO is used in a data transform, deleting the data stream will affect any transforms relying on that DLO.
Dependency Check: Ensure that the DLO is not part of any active data transformations or processes that could be disrupted by its deletion.
References:
Salesforce Data Cloud Documentation: Data Streams
Salesforce Data Cloud Documentation: Data Transforms
NEW QUESTION # 116
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