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Salesforce Data-Cloud-Consultant Exam Syllabus Topics:

Topic	Details
Topic 1	Data Cloud Setup and Administration: This topic includes applying Data Cloud permissions, permission sets, org-wide settings. It describes and configures data stream types, and data bundles. Moreover, it discusses use cases for data spaces, creating data spaces, managing and administering Data Cloud using reports, dashboards, flows, packaging, data kits, diagnosing and exploring data using Data Explorer, Profile Explorer, and APIs.
Topic 2	Data Cloud Overview: This topic covers Data Cloud's function, key terminology, business value, typical use cases, the Data Cloud lifecycle, dependencies, and principles of data ethics. These sub-topics provide an overview of Data Cloud's capabilities and applications.
Topic 3	Act on Data: This topic defines activations and their basic use cases, using attributes and related attributes, identifying and analyzing timing dependencies affecting the Data Cloud lifecycle. Additionally it focuses on troubleshooting common problems with activations, and using data actions, including their requirements and intended use cases.
Topic 4	Segmentation and Insights: This topic defines basic concepts of segmentation and use cases, identifies scenarios for analyzing segment membership, configuring, refining, and maintaining segments within Data Cloud, and differentiating between calculated and streaming insights.

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Salesforce Certified Data Cloud Consultant Sample Questions (Q57-Q62):

NEW QUESTION # 57
What is the role of artificial intelligence (AI) in Data Cloud?

A. Creating dynamic data-driven management dashboards
B. Automating data validation
C. Enhancing customer interactions through insights and predictions
D. Generating email templates for use cases

Answer: C

Explanation:
* Role of AI in Data Cloud: Artificial intelligence (AI) plays a crucial role in Salesforce Data Cloud by leveraging data to generate insights and predictions that enhance customer interactions.
* Insights and Predictions:
AI Algorithms: Use machine learning algorithms to analyze vast amounts of customer data.
Predictive Analytics: Provide predictive insights, such as customer behavior trends, preferences, and potential future actions.
* Enhancing Customer Interactions:
Personalization: AI helps in creating personalized experiences by predicting customer needs and preferences.
Efficiency: Enables proactive customer service by predicting issues and suggesting solutions before customers reach out.
Marketing: Improves targeting and segmentation, ensuring that marketing efforts are directed towards the most promising leads and customers.
* Use Cases:
Recommendation Engines: Suggest products or services based on past behavior and preferences.
Churn Prediction: Identify customers at risk of leaving and engage them with retention strategies.
* Reference:
Salesforce Data Cloud AI Capabilities
Salesforce AI for Customer Interaction

NEW QUESTION # 58
Which two dependencies prevent a data stream from being deleted?
Choose 2 answers

A. The underlying data lake object is used in segmentation.
B. The underlying data lake object is used in a data transform.
C. The underlying data lake object is used in activation.
D. The underlying data lake object is mapped to a data model object.

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.
References:
* 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 # 59
Northern Trail Outfitters is using the Marketing Cloud Starter Data Bundles to bring Marketing Cloud data into Data Cloud.
What are two of the available datasets in Marketing Cloud Starter Data Bundles?
Choose 2 answers

A. Loyalty Management
B. MobileConnect
C. Personalization
D. MobilePush

Answer: B,D

Explanation:
Explanation
The Marketing Cloud Starter Data Bundles are predefined data bundles that allow you to easily ingest data from Marketing Cloud into Data Cloud1. The available datasets in Marketing Cloud Starter Data Bundles are Email, MobileConnect, and MobilePush2. These datasets contain engagement events and metrics from different Marketing Cloud channels, such as email, SMS, and push notifications2. By using these datasets, you can enrich your Data Cloud data model with Marketing Cloud data and create segments and activations based on your marketing campaigns and journeys1. The other options are incorrect because they are not available datasets in Marketing Cloud Starter Data Bundles. Option A is incorrect because Personalization is not a dataset, but a feature of Marketing Cloud that allows you to tailor your content and messages to your audience3. Option C is incorrect because Loyalty Management is not a dataset, but a product of Marketing Cloud that allows you to create and manage loyaltyprograms for your customers4. References: Marketing Cloud Starter Data Bundles in Data Cloud, Connect Your Data Sources, Personalization in Marketing Cloud, Loyalty Management in Marketing Cloud

NEW QUESTION # 60
A segment fails to refresh with the error "Segment references too many data lake objects (DLOS)".
Which two troubleshooting tips should help remedy this issue?
Choose 2 answers

A. Space out the segment schedules to reduce DLO load.
B. Refine segmentation criteria to limit up to five custom data model objects (DMOs).
C. Use calculated insights in order to reduce the complexity of the segmentation query.
D. Split the segment into smaller segments.

Answer: C,D

Explanation:
The error "Segment references too many data lake objects (DLOs)" occurs when a segment query exceeds the limit of 50 DLOs that can be referenced in a single query. This can happen when the segment has too many filters, nested segments, or exclusion criteria that involve different DLOs. To remedy this issue, the consultant can try the following troubleshooting tips:
Split the segment into smaller segments. The consultant can divide the segment into multiple segments that have fewer filters, nested segments, or exclusion criteria. This can reduce the number of DLOs that are referenced in each segment query and avoid the error. The consultant can then use the smaller segments as nested segments in a larger segment, or activate them separately.
Use calculated insights in order to reduce the complexity of the segmentation query. The consultant can create calculated insights that are derived from existing data using formulas. Calculated insights can simplify the segmentation query by replacing multiple filters or nested segments with a single attribute. For example, instead of using multiple filters to segment individuals based on their purchase history, the consultant can create a calculated insight that calculates the lifetime value of each individual and use that as a filter.
The other options are not troubleshooting tips that can help remedy this issue. Refining segmentation criteria to limit up to five custom data model objects (DMOs) is not a valid option, as the limit of 50 DLOs applies to both standard and custom DMOs. Spacing out the segment schedules to reduce DLO load is not a valid option, as the error is not related to the DLO load, but to the segment query complexity.
Troubleshoot Segment Errors
Create a Calculated Insight
Create a Segment in Data Cloud

NEW QUESTION # 61
Which information is provided in a .csv file when activating to Amazon S3?

A. The activated data payload
B. An audit log showing the user who activated the segment and when it was activated
C. The manifest of origin sources within Data Cloud
D. The metadata regarding the segment definition

Answer: A

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. Reference: Data Activation Overview, Create and Activate Segments in Data Cloud, Data Activation Use Cases, View Activation History, Segmentation Overview, [Data Sources Overview]

NEW QUESTION # 62
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100% Pass Quiz Salesforce - High-quality Data-Cloud-Consultant - Exam Salesforce Certified Data Cloud Consultant Voucher

Salesforce Data-Cloud-Consultant Exam Syllabus Topics:

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Salesforce Certified Data Cloud Consultant Sample Questions (Q57-Q62):

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