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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
Available Languages:English
Related Certifications:Salesforce Certified Data Architect
Salesforce Certified Administrator
Passing Score:63%
Exam Price:$200 USD
Real Exam Qty:60
Exam Format:Multiple Select, Multiple Choice
Exam Duration:90 minutes
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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Data-Cloud-Consultant Exam VCE: Salesforce Certified Data 360 Consultant (Data-Con-101) - Data-Cloud-Consultant Pass Guide & Data-Cloud-Consultant Study Guide

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Salesforce Data-Cloud-Consultant Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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 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
  • 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 360 Consultant (Data-Con-101) Sample Questions (Q49-Q54):

NEW QUESTION # 49
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:
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. References: Data Stream Field Types, E164 Phone Number Format, Salesforce Data Cloud Exam Questions


NEW QUESTION # 50
A user Is not seeing suggested values from newly-modeled data when building a segment.
What is causing this issue?

Answer: A

Explanation:
The most likely cause of this issue is that value suggestion is still processing and takes up to 24 hours to be available. Value suggestion is a feature that enables you to see suggested values for data model object (DMO) fields when creating segment filters. However, this feature needs to be enabled for each DMO field, and it can take up to 24 hours for the suggested values to appear after enabling the feature1. Therefore, if a user is not seeing suggested values from newly-modeled data, it could be that the data has not been processed yet by the value suggestion feature. Reference:
Use Value Suggestions in Segmentation


NEW QUESTION # 51
A consultant is setting up a data stream with transactional data,
Which field type should the consultant choose to ensure that leading
zeros in the purchase order number are preserved?

Answer: C

Explanation:
The field type Text should be chosen to ensure that leading zeros in the purchase order number are preserved. This is because text fields store alphanumeric characters as strings, and do not remove any leading or trailing characters. On the other hand, number, decimal, and serial fields store numeric values as numbers, and automatically remove any leading zeros when displaying or exporting the data123. Therefore, text fields are more suitable for storing data that needs to retain its original format, such as purchase order numbers, zip codes, phone numbers, etc. References:
Zeros at the start of a field appear to be omitted in Data Exports
Keep First '0' When Importing a CSV File
Import and export address fields that begin with a zero or contain a plus symbol


NEW QUESTION # 52
A Data 360 Consultant for Northern Trail Outfitters is observing Identity Resolution processing metrics. The consultant notices that the volume of source profiles processed in the most recent batch is less than the total volume of source profiles. What is the most likely mechanism that causes source profiles to be skipped during Identity Resolution processing?

Answer: D

Explanation:
The identity logic is about linking source profiles safely, then choosing the best surviving values for the unified profile. A profile is only processed if a pre-processing step confirms a change in its data since the last processing run. 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.


NEW QUESTION # 53
How should a Data 360 Consultant modify attribute names to match a naming convention in Cloud File Storage targets?

Answer: D

Explanation:
Data 360 allows the consultant to control the names exported to an activation target without changing the underlying source or DMO schema. Salesforce documents this capability as the Output Name, formerly described as the preferred attribute name. During activation configuration, the consultant can override the default API-derived attribute name with a custom output name that matches the target system ' s naming convention. Data 360 then uses that value as the column header or field name in the activation output.
Changing the data stream or DMO field name would unnecessarily alter the data-model layer, while a formula field is intended for deriving values rather than controlling exported column names. Therefore, setting the preferred/output attribute name during activation is the correct solution.


NEW QUESTION # 54
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