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Salesforce Data-Cloud-Consultant Exam Overview:

Certification Vendor:Salesforce
Exam Name:Salesforce Certified Data 360 Consultant (formerly Salesforce Certified Data Cloud Consultant)
Exam Number:Data-Con-101 / Data-Cloud-Consultant
Certificate Validity Period:3 years
Exam Format:Multiple-select, Multiple-choice, Scenario-based questions
Exam Duration:105 minutes
Exam Price:USD $200 + applicable taxes
Passing Score:62% - 70%
Available Languages:English
Related Certifications:Salesforce Certified Marketing Cloud Consultant
Salesforce Certified Data Architect
Salesforce Certified Administrator
Real Exam Qty:60 (plus up to 5 unscored questions)
Recommended Training:Salesforce Trailhead - Data 360 / Data Cloud Learning Path
Exam Registration:Salesforce Webassessor Registration
Sample Questions:Salesforce Data-Cloud-Consultant Sample Questions
Exam Way:Online proctored or onsite at authorized testing centers
Pre Condition:No mandatory prerequisites; recommended: 1–2 years experience in data management, Salesforce implementation, or CDP solutions
Official Syllabus URL:https://help.salesforce.com/s/articleView?id=005298940&language=en_US

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Salesforce Data-Cloud-Consultant Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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 3
  • 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 4
  • 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 5
  • 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.

Salesforce Certified Data 360 Consultant (Data-Con-101) Sample Questions (Q89-Q94):

NEW QUESTION # 89
A company wants to test its marketing campaigns with different target populations.
What should the consultant adjust in the Segment Canvas interface to get different populations?

Answer: A

Explanation:
Segmentation in Salesforce Data Cloud:
* The Segment Canvas interface is used to define and adjust target populations for marketing campaigns.


NEW QUESTION # 90
A consultant needs to update a field in CRM as soon as a record gets updated in the DMO.
Which feature should the consultant use?

Answer: D


NEW QUESTION # 91
A global fashion retailer operates online sales platforms across AMFR, FMFA, and APAC. the data formats for customer, order, and product Information vary by region, and compliance regulations require data to remain unchanged in the original data sources They also require a unified view of customer profiles for real-time personalization and analytics.
Given these requirement, which transformation approach should the company implement to standardise and cleanse incoming data streams?

Answer: B

Explanation:
Given the requirements to standardize and cleanse incoming data streams while keeping the original data unchanged in compliance with regional regulations, the best approach is to implement batch data transformations . Here's why:
Understanding the Requirements
The global fashion retailer operates across multiple regions (AMER, EMEA, APAC), each with varying data formats for customer, order, and product information.
Compliance regulations require the original data to remain unchanged in the source systems.
The company needs a unified view of customer profiles for real-time personalization and analytics.
Why Batch Data Transformations?
Batch Transformations for Standardization :
Batch data transformations allow you to process large volumes of data at scheduled intervals.
They can standardize and cleanse data (e.g., converting different date formats, normalizing product names) without altering the original data in the source systems.
Compliance with Regulations :
Since the original data remains unchanged in the source systems, batch transformations comply with regional regulations.
The transformed data is stored in a separate layer (e.g., a new Data Lake Object or Unified Profile) for downstream use.
Unified Customer Profiles :
After transformation, the cleansed and standardized data can be used to create a unified view of customer profiles in Salesforce Data Cloud.
This enables real-time personalization and analytics across regions.
Steps to Implement This Solution
Step 1: Identify Transformation Needs
Analyze the differences in data formats across regions (e.g., date formats, currency, product IDs).
Define the rules for standardization and cleansing (e.g., convert all dates to ISO format, normalize product names).
Step 2: Create Batch Transformations
Use Data Cloud's Batch Transform feature to apply the defined rules to incoming data streams.
Schedule the transformations to run at regular intervals (e.g., daily or hourly).
Step 3: Store Transformed Data Separately
Store the transformed data in a new Data Lake Object (DLO) or Unified Profile.
Ensure the original data remains untouched in the source systems.
Step 4: Enable Unified Profiles
Use the transformed data to create a unified view of customer profiles in Salesforce Data Cloud.
Leverage this unified view for real-time personalization and analytics.
Why Not Other Options?
A . Implement streaming data transformations :
Streaming transformations are designed for real-time processing but may not be suitable for large-scale standardization and cleansing tasks. Additionally, they might not align with compliance requirements to keep the original data unchanged.
C . Transform data before ingesting into Data Cloud :
Transforming data before ingestion would require modifying the original data in the source systems, violating compliance regulations.
D . Use Apex to transform and cleanse data :
Using Apex is overly complex and resource-intensive for this use case. Batch transformations are a more efficient and scalable solution.
Conclusion
By implementing batch data transformations , the global fashion retailer can standardize and cleanse its data while complying with regional regulations and enabling a unified view of customer profiles for real-time personalization and analytics.


NEW QUESTION # 92
What is the result of a segmentation criteria filtering on City | Is Equal To | 'San Jose'?

Answer: A

Explanation:
The result of a segmentation criteria filtering on City | Is Equal To | 'San Jose' is cities only containing 'San Jose' or 'san jose'. This is because the segmentation criteria is case-sensitive and accent-sensitive, meaning that it will only match the exact value that is entered in the filter1. Therefore, cities containing 'San Jose', 'san jose', or 'San Jose' will not be included in the result, as they do not match the filter value exactly. To include cities with different variations of the name 'San Jose', you would need to use the OR operator and add multiple filter values, such as 'San Jose' OR 'San Jose' OR 'san jose' OR 'san jose'2. References: Segmentation Criteria, Segmentation Operators


NEW QUESTION # 93
How does Data Cloud ensure data privacy and security?

Answer: A


NEW QUESTION # 94
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