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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 Ingestion and Modeling: This topic covers the different transformation capabilities within Data Cloud. It includes describing processes and considerations for data ingestion from various sources, defining, mapping, and modeling data using best practices aligned with identity resolution. Lastly, it discusses using available tools to inspect and validate ingested and modeled data.
Topic 3	Solution 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 4	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 5	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.

Salesforce Certified Data Cloud Consultant Sample Questions (Q26-Q31):

NEW QUESTION # 26
Luxury Retailers created a segment targeting high value customers that it activates through Marketing Cloud for email communication. The company notices that the activated count is smaller than the segment count.
What is a reason for this?

A. Marketing Cloud activations automatically suppress individuals who are unengaged and have not opened or clicked on an email in the last six months.
B. Data Cloud enforces the presence of Contact Point for Marketing Cloud activations. If the individual does not have a related Contact Point, it will not be activated.
C. Marketing Cloud activations apply a frequency cap and limit the number of records that can be sent in an activation.
D. Marketing Cloud activations only activate those individuals that already exist in Marketing Cloud. They do not allow activation of new records.

Answer: B

Explanation:
Explanation
Data Cloud requires a Contact Point for Marketing Cloud activations, which is a record that links an individual to an email address. This ensures that the individual has given consent to receive email communications and that the email address is valid. If the individual does not have a related Contact Point, they will not be activated in Marketing Cloud. This may result in a lower activated count than the segment count. References: Data Cloud Activation, Contact Point for Marketing Cloud

NEW QUESTION # 27
How does identity resolution select attributes for unified individuals when there Is conflicting information in the data model?

A. Creates additional contact points
B. Leverages match rules
C. Leverages reconciliation rules
D. Creates additional rulesets

Answer: C

Explanation:
Explanation
Identity resolution is the process of creating unified profiles of individuals by matching and merging data from different sources. When there is conflicting information in the data model, such as different names, addresses, or phone numbers for the same person, identity resolution leverages reconciliation rules to select the most accurate and complete attributes for the unified profile. Reconciliation rules are configurable rules that define how to resolve conflicts based on criteria such as recency, frequency, source priority, or completeness.
For example, a reconciliation rule can specify that the most recent name or the most frequent phone number should be selected for the unified profile. Reconciliation rules can be applied at the attribute level or the contact point level. References: Identity Resolution, Reconciliation Rules, Salesforce Data Cloud Exam Questions

NEW QUESTION # 28
Cloud Kicks wants to be able to build a segment of customers who have visited its website within the previous
7 days.
Which filter operator on the Engagement Date field fits this use case?

A. Greater than Last Number of
B. Last Number of Days
C. Next Number of Days
D. Is Between

Answer: B

Explanation:
Explanation
The filter operator Last Number of Days allows you to filter on date fields using a relative date range that specifies the number of days before today. For example, you can use this operator to filter on customers who have visited your website in the last 7 days, or the last 30 days, or any number of days you want. This operator is useful for creating dynamic segments that update automatically based on the current date12. References:
* Relative Date Filter Reference
* Create Filtered Segments

NEW QUESTION # 29
A consultant is working in a customer's Data Cloud org and is asked to delete the existing identity resolution ruleset.
Which two impacts should the consultant communicate as a result of this action?
Choose 2 answers

A. Dependencies on data model objects will be removed.
B. Unified customer data associated with this ruleset will be removed.
C. All individual data will be removed.
D. All source profile data will be removed

Answer: A,B

Explanation:
Explanation
Deleting an identity resolution ruleset has two major impacts that the consultant should communicate to the customer. First, it will permanently remove all unified customer data that was created by the ruleset, meaning that the unified profiles and their attributes will no longer be available in Data Cloud1. Second, it will eliminate dependencies on data model objects that were used by the ruleset, meaning that the data model objects can be modified or deleted without affecting the ruleset1. These impacts can have significant consequences for the customer's data quality, segmentation, activation, and analytics, so the consultant should advise the customer to carefully consider the implications of deleting a ruleset before proceeding. The other options are incorrect because they are not impacts of deleting a ruleset. Option A is incorrect because deleting a ruleset will not remove all individual data, but only the unified customer data. The individual data from the source systems will still be available in Data Cloud1. Option D is incorrect because deleting a ruleset will not remove all source profile data, but only the unified customer data. The source profile data from the data streams will still be available in Data Cloud1. References: Delete an Identity Resolution Ruleset

NEW QUESTION # 30
A consultant is building a segment to announce a new product launch for customers that have previously purchased black pants.
How should the consultant place attributes for product color and product type from the Order Product object to meet this criteria?

A. Place an attribute for the "black" calculated insight to dynamically apply
B. Place the attribute for product color in onecontainer and the attribute for product type in another container.
C. Place the attributes for product color and product type in a single container.
D. Place the attributes for product and product type as direct attributes.

Answer: C

Explanation:
Explanation
To create a segment based on the product color and product type from the Order Product object, the consultant should place the attributes for product color and product type in a single container. This way, the segment will include only the customers who have purchased black pants, and not those who have purchased black shirts or blue pants. A container is a grouping of attributes that defines a segment of individuals based on a logical AND operation. Placing the attributes in separate containers would result in a segment that includes customers who have purchased any black product or any pants product, which is not the desired criteria. Placing an attribute for the "black" calculated insight would not work, because calculated insights are based on aggregated data and not individual-level data. Placing the attributes as direct attributes would not work, because direct attributes are used to filter individuals based on their profile data, not their order data. References:
* Create a Segment in Data Cloud
* Learn About Segmentation Tools
* Salesforce Launches: Data Cloud Consultant Certification

NEW QUESTION # 31
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You will need to pass the Salesforce Certified Data Cloud Consultant (Data-Cloud-Consultant) exam to achieve the Salesforce Certified Data Cloud Consultant (Data-Cloud-Consultant) certification. Due to extremely high competition, passing the Salesforce Data-Cloud-Consultant exam is not easy; however, possible. You can use ITPassLeader products to pass the Data-Cloud-Consultant Exam on the first attempt. The Salesforce Certified Data Cloud Consultant (Data-Cloud-Consultant) practice exam gives you confidence and helps you understand the criteria of the testing authority and pass the Salesforce Data-Cloud-Consultant exam on the first attempt.

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