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| Section | Weight | Objectives |
|---|---|---|
| Data Model Setup and Configuration | 15% | - Map source data to harmonized data model - Set up and configure Data Lake objects - Understand data types and field mapping - Describe Harmonized Data Model concepts - Configure custom objects, fields, and relationships |
| Data Sharing and Security | 8% | - Configure data sharing settings - Manage user access and permissions - Implement row-level security - Understand data governance requirements |
| Data Cloud Monitoring and Troubleshooting | 22% | - Manage data retention and cleanup - Debug common configuration errors - Troubleshoot data quality issues - Monitor data ingestion and sync status - Use Data Cloud analytics and reports - Analyze identity resolution results |
| 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 Actions | 8% | - Set up segmentation and target audiences - Create and manage data bundles - Configure data sync to external systems - Configure data actions for activation |
| Identity Resolution and Data Unification | 17% | - Manage data overlap and deduplication - Configure match rules and strategies - Understand unified records creation - Configure identity resolution rules - Configure contact and account matching |
| Data Ingestion | 15% | - Configure data sync and refresh schedules - Configure streaming data ingestion - Configure batch data ingestion - Set up and manage data connectors - Troubleshoot ingestion issues |
| Calculated Insights | 8% | - Define metrics and measurements - Publish insights to Data Cloud - Create and configure calculated insights - Use formulas and functions in calculations |
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NEW QUESTION # 33
A customer wants to use the transactional data from their data warehouse in Data Cloud.
They are only able to export the data via an SFTP site.
How should the file be brought into Data Cloud?
Answer: A
Explanation:
The SFTP Connector is a data source connector that allows Data Cloud to ingest data from an SFTP server.
The customer can use the SFTP Connector to create a data stream from their exported file and bring it into Data Cloud as a data lake object. The other options are not the best ways to bring the file into Data Cloud because:
* B. The Cloud Storage Connector is a data source connector that allows Data Cloud to ingest data from cloud storage services such as Amazon S3, Azure Storage, or Google Cloud Storage. The customer does not have their data in any of these services, but only on an SFTP site.
* C. The Data Import Wizard is a tool that allows users to import data for many standard Salesforce objects, such as accounts, contacts, leads, solutions, and campaign members. It is not designed to import data from an SFTP site or for custom objects in Data Cloud.
* D. The Dataloader is an application that allows users to insert, update, delete, or export Salesforce records. It is not designed to ingest data from an SFTP site or into Data Cloud. References: SFTP Connector - Salesforce, Create Data Streams with the SFTP Connector in Data Cloud - Salesforce, Data Import Wizard - Salesforce, Salesforce Data Loader
NEW QUESTION # 34
Northern Trail Outfitters (NTO) wants to create a segment where a unique record is created in the published audience for every transaction a customer completes. If a customer makes three separate purchases, the resulting segment should contain three distinct entries for that customer to allow for transaction- specific messaging. All transactions are mapped to the Sales Order data model object (DMO), and NTO is using Identity Resolution to unify customers on the Unified Individual DMO. Which configuration should a Data
360 Consultant use to meet this requirement?
Answer: D
Explanation:
The identity logic is about linking source profiles safely, then choosing the best surviving values for the unified profile. Segment on the Sales Order DMO is appropriate because identity resolution needs reliable match inputs, qualified identifiers, and controlled reconciliation. It is not just deduplication; it is a rules-driven process that connects source records into a trusted unified profile. The distractors fall short because they either move the problem into the wrong system, add needless duplication, ignore Data 360 object relationships, or rely on a feature built for a different lifecycle stage. In a real implementation, those choices usually create brittle pipelines, stale data, security exposure, or segments that look correct on paper but fail when activated. Thinking like an architect, the selected option places the logic where Data 360 can govern it and reuse it reliably. This is the nuance exam questions often test: the platform capability must match both the technical layer and the business timing requirement, not just sound related to data.
NEW QUESTION # 35
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: B,D
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.
References: Identity Resolution Calculated Insight: Consolidation Rates for Unified Profiles, Configure Identity Resolution Rulesets
NEW QUESTION # 36
Which two dependencies prevent a data stream from being deleted?
Choose 2 answers
Answer: B,D
Explanation:
To delete a data stream in Data Cloud, the underlying data lake object (DLO) must not have any dependencies or references to other objects or processes. The following two dependencies prevent a data stream from being deleted1:
Data transform: This is a process that transforms the ingested data into a standardized format and structure for the data model. A data transform can use one or more DLOs as input or output. If a DLO is used in a data transform, it cannot be deleted until the data transform is removed or modified2.
Data model object: This is an object that represents a type of entity or relationship in the data model. A data model object can be mapped to one or more DLOs to define its attributes and values. If a DLO is mapped to a data model object, it cannot be deleted until the mapping is removed or changed3.
1: Delete a Data Stream article on Salesforce Help
2: [Data Transforms in Data Cloud] unit on Trailhead
3: [Data Model in Data Cloud] unit on Trailhead
NEW QUESTION # 37
What are the two minimum requirements needed when using the Visual Insights Builder to create a calculated insight?
Choose 2 answers
Answer: C,D
Explanation:
Introduction to Visual Insights Builder:
The Visual Insights Builder in Salesforce Data Cloud is a tool used to create calculated insights, which are custom metrics derived from the existing data.
Reference: Salesforce Visual Insights Builder Documentation
Requirements for Creating Calculated Insights:
Measure: A measure is a quantitative value that you want to analyze, such as revenue, number of purchases, or total time spent on a platform.
Dimension: A dimension is a qualitative attribute that you use to categorize or filter the measures, such as date, region, or customer segment.
Reference: Salesforce Insights Builder Guide
Steps to Create a Calculated Insight:
Navigate to the Visual Insights Builder within Salesforce Data Cloud.
Select "Create New Insight" and choose the dataset.
Add at least one measure: This could be any metric you want to analyze, such as "Total Sales." Add at least one dimension: This helps to break down the measure, such as "Sales by Region." Reference: Salesforce Calculated Insights Creation Tutorial Practical Application:
Example: To create an insight on "Average Purchase Value by Region," you would need:
A measure: Total Purchase Value.
A dimension: Customer Region.
This allows for actionable insights, such as identifying high-performing regions.
NEW QUESTION # 38
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