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Salesforce Data-Cloud-Consultant Exam Overview:

Certification Vendor:Salesforce
Exam Name:Salesforce Certified Data 360 Consultant
Exam Number:Data-Con-101
Exam Format:Multiple Choice, Multiple Select
Available Languages:English
Related Certifications:Salesforce Certified Data Architect
Salesforce Certified Administrator
Passing Score:63%
Real Exam Qty:60
Exam Duration:90 minutes
Exam Price:$200 USD
Certificate Validity Period:3 years
Sample Questions:Salesforce Data-Cloud-Consultant Sample Questions
Exam Way:Online proctored exam
Pre Condition:Recommended: Salesforce Administrator certification and hands-on experience with Data Cloud implementation
Official Syllabus URL:https://trailhead.salesforce.com/credentials/data360consultant

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Salesforce Data-Cloud-Consultant Exam Syllabus Topics:

TopicDetails
Topic 1
  • Identity Resolution: It describes matching and how its rule sets are applied. Furthermore, it discusses reconciling data and its rule sets, the results of identity resolution, and use cases.
Topic 2
  • 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.
Topic 3
  • 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 4
  • 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 5
  • 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.

Salesforce Certified Data 360 Consultant (Data-Con-101) Sample Questions (Q66-Q71):

NEW QUESTION # 66
A Data Cloud consultant tries to save a new 1-to-l relationship between the Account DMO and Contact Point Address DMO but gets an error.
What should the consultant do to fix this error?

Answer: C

Explanation:
Relationship Cardinality: In Salesforce Data Cloud, defining the correct relationship cardinality between data model objects (DMOs) is crucial for accurate data representation and integration.
1-to-1 Relationship Error: The error occurs because the relationship between Account DMO and Contact Point Address DMO is set as 1-to-1, which implies that each account can only have one contact point address.
Solution:
* Change Cardinality: Modify the relationship cardinality to many-to-one. This allows multiple contact point addresses to be associated with a single account, reflecting real-world scenarios more accurately.
* Steps:
* Go to the data model configuration in Data Cloud.
* Locate the relationship between Account DMO and Contact Point Address DMO.
* Change the relationship type from 1-to-1 to many-to-one.
Benefits:
* Accurate Representation: Accommodates real-world data scenarios where an account may have multiple contact points.
* Error Resolution: Resolves the error and ensures smooth data integration.
References:
* Salesforce Data Cloud Documentation: Relationships
* Salesforce Help: Data Modeling in Data Cloud


NEW QUESTION # 67
A consultant wants to ensure that every segment managed by multiple brand teams adheres to the same set of exclusion criteria, that are updated on a monthly basis.
What is the most efficient option to allow for this capability?

Answer: B

Explanation:
The most efficient option to allow for this capability is to create a reusable container block with common criteria. A container block is a segment component that can be reused across multiple segments. A container block can contain any combination of filters, nested segments, and exclusion criteria. A consultant can create a container block with the exclusion criteria that apply to all the segments managed by multiple brand teams, and then add the container block to each segment. This way, the consultant can update the exclusion criteria in one place and have them reflected in all the segments that use the container block.
The other options are not the most efficient options to allow for this capability. Creating, publishing, and deploying a data kit is a way to share data and segments across different data spaces, but it does not allow for updating the exclusion criteria on a monthly basis. Creating a nested segment is a way to combine segments using logical operators, but it does not allow for excluding individuals based on specific criteria. Creating a segment and copying it for each brand is a way to create multiple segments with the same exclusion criteria, but it does not allow for updating the exclusion criteria in one place.
Reference:
Create a Container Block
Create a Segment in Data Cloud
Create and Publish a Data Kit
Create a Nested Segment


NEW QUESTION # 68
A consultant is planning the ingestion of a data stream that has profile information including a mobile phone number.
To ensure that the phone number can be used for future SMS campaigns, they need to confirm the phone number field is in the proper E164 Phone Number format. However, the phone numbers in the file appear to be in varying formats.
What is the most efficient way to guarantee that the various phone number formats are standardized?

Answer: C

Explanation:
The most efficient way to guarantee that the various phone number formats are standardized is to assign the PhoneNumber field type when creating the data stream. The PhoneNumber field type is a special field type that automatically converts phone numbers into the E164 format, which is the international standard for phone numbers. The E164 format consists of a plus sign (+), the country code, and the national number. For example, +1-202-555-1234 is the E164 format for a US phone number. By using the PhoneNumber field type, the consultant can ensure that the phone numbers are consistent and can be used for future SMS campaigns. The other options are either more time-consuming, require manual intervention, or do not address the formatting issue. Reference: Data Stream Field Types, E164 Phone Number Format, Salesforce Data Cloud Exam Questions


NEW QUESTION # 69
Cumulus Financial (CF) wants to target loyal and engaged customers. When a platinum tier customer visits their Investment pages more than three times in a 24-hour period, CF wants to Immediately Send an email that offers a private consultation.
What should a consultant recommend for this business requirement?

Answer: A


NEW QUESTION # 70
The recruiting team at Cumulus Financial wants to identify which candidates have browsed the jobs page on its website at least twice within the last 24 hours. They want the information about these candidates to be available for segmentation in Data Cloud and the candidates added to their recruiting system.
Which feature should a consultant recommend to achieve this goal?

Answer: C

Explanation:
Explanation
A streaming insight is a feature that allows users to create and monitor real-time metrics from streaming data sources, such as web and mobile events. A streaming insight can also trigger data actions, such as sending notifications, creating records, or updating fields, based on the metric values and conditions. Therefore, a streaming insight is the best feature to achieve the goal of identifying candidates who have browsed the jobs page on the website at least twice within the last 24 hours, and adding them to the recruiting system. The other options are incorrect because:
* A streaming data transform is a feature that allows users to transform and enrich streaming data using SQL expressions, such as filtering, joining, aggregating, or calculating values. However, a streaming data transform does not provide the ability to monitor metrics or trigger data actions based on conditions.
* A calculated insight is a feature that allows users to define and calculate multidimensional metrics from data using SQL expressions, such as LTV, CSAT, or average order value. However, a calculated insight is not suitable for real-time data analysis, as it runs on a scheduled basis and does not support data actions.
* A batch data transform is a feature that allows users to create and schedule complex data transformations using a visual editor, such as joining, aggregating, filtering, or appending data.
However, a batch data transform is not suitable for real-time data analysis, as it runs on a scheduled basis and does not support data actions. References: Streaming Insights, Create a Streaming Insight, Use Insights in Data Cloud, Learn About Data Cloud Insights, Data Cloud Insights Using SQL, Streaming Data Transforms, Get Started with Batch Data Transforms in Data Cloud, Transformations for Batch Data Transforms, Batch Data Transforms in Data Cloud: Quick Look, Salesforce Data Cloud: AI CDP.


NEW QUESTION # 71
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