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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
Real Exam Qty:60
Related Certifications:Salesforce Certified Administrator
Salesforce Certified Data Architect
Exam Format:Multiple Select, Multiple Choice
Exam Price:$200 USD
Exam Duration:90 minutes
Passing Score:63%
Certificate Validity Period:3 years
Available Languages:English
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
  • 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
  • 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
  • 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 4
  • 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 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 360 Consultant (Data-Con-101) Sample Questions (Q23-Q28):

NEW QUESTION # 23
A consultant is discussing the benefits of Data Cloud with a customer that has multiple disjointed data sources.
Which two functional areas should the consultant highlight in relation to managing customer data?
Choose 2 answers

Answer: B,C

Explanation:
Explanation
Data Cloud is an open and extensible data platform that enables smarter, more efficient AI with secure access to first-party and industry data1. Two functional areas that the consultant should highlight in relation to managing customer data are:
* Data Harmonization: Data Cloud harmonizes data from multiple sources and formats into a common schema, enabling a single source of truth for customer data1. Data Cloud also applies data quality rules and transformations to ensure data accuracy and consistency.
* Unified Profiles: Data Cloud creates unified profiles of customers and prospects by linking data across different identifiers, such as email, phone, cookie, and device ID1. Unified profiles providea holistic view of customer behavior, preferences, and interactions across channels and touchpoints. The other options are not correct because:
* Master Data Management: Master Data Management (MDM) is a process of creating and maintaining a single, consistent, and trusted source of master data, such as product, customer, supplier, or location data. Data Cloud does not provide MDM functionality, but it can integrate with MDM solutions to enrich customer data.
* Data Marketplace: Data Marketplace is a feature of Data Cloud that allows users to discover, access, and activate data from third-party providers, such as demographic, behavioral, and intent data. Data Marketplace is not a functional area related to managing customer data, but rather a source of external data that can enhance customer data. References:
* Salesforce Data Cloud
* [Data Harmonization for Data Cloud]
* [Unified Profiles for Data Cloud]
* [What is Master Data Management?]
* [Integrate Data Cloud with Master Data Management]
* [Data Marketplace for Data Cloud]


NEW QUESTION # 24
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: D

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 # 25
The Salesforce CRM Connector is configured and the Case object data stream is set up. Subsequently, a new custom field named Business Priority is created on the Case object in Salesforce CRM. However, the new field is not available when trying to add it to the data stream.
Which statement addresses the cause of this issue?

Answer: C

Explanation:
The Salesforce CRM Connector uses the Salesforce Integration User to access the data from the Salesforce CRM org. The Integration User must have the Read permission on the fields that are included in the data stream. If the Integration User does not have the Read permission on the newly created field, the field will not be available for selection in the data stream configuration. To resolve this issue, the administrator should assign the Read permission on the new field to the Integration User profile or permission set. References: Create a Salesforce CRM Data Stream, Edit a Data Stream, Salesforce Data Cloud Full Refresh for CRM, SFMC, or Ingestion API Data Streams


NEW QUESTION # 26
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?

Answer: B

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 # 27
A user Is not seeing suggested values from newly-modeled data when building a segment.
What is causing this issue?

Answer: D

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 # 28
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