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[General] Ensured Exam Success with Salesforce Data-Con-101 Exam Questions

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【General】 Ensured Exam Success with Salesforce Data-Con-101 Exam Questions

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If you want to pass Salesforce Data-Con-101 exam and get a high paying job in the industry; if you are searching for the perfect Data-Con-101 exam prep material to get your dream job, then you must consider using our Salesforce Certified Data Cloud Consultant exam products to improve your skillset. We have curated new Data-Con-101 Questions Answers to help you prepare for the exam. It can be your golden ticket to pass the Salesforce Data-Con-101 test on the first attempt. We are providing latest Data-Con-101 PDF question answers to help you prepare exam while working in the office to save your time.
Salesforce Data-Con-101 Exam Syllabus Topics:
TopicDetails
Topic 1
  • Identity Resolution: This domain explores creating unified customer profiles through matching and reconciliation processes. It covers how rule sets determine when records link together, how conflicting data is resolved, and understanding the outcomes and use cases of unified identities.
Topic 2
  • Data Cloud Overview: This domain covers the foundational understanding of Data Cloud including its core purpose, terminology, business value, and technical architecture. It also addresses typical use cases and the essential principles of ethical data handling when working with customer data.
Topic 3
  • Data Cloud Setup and Administration: This domain focuses on configuring and managing Data Cloud environments through permissions, data streams, data bundles, and data spaces. It also covers administrative tools and techniques for diagnosing and exploring data using reports, dashboards, flows, APIs, and explorer tools.
Topic 4
  • Act on Data: This domain focuses on leveraging Data Cloud data for downstream actions through activations and data actions. It covers working with attributes, managing timing dependencies, troubleshooting activation issues like errors and rejected counts, and understanding requirements for triggering automated processes.

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Salesforce Certified Data Cloud Consultant Sample Questions (Q82-Q87):NEW QUESTION # 82
A consultant is connecting sales order data to Data Cloud and considers whether to use the Profile, Engagement, or Other categories to map the DLO. The consultant chooses to map the DLO called Order- Headers to the Sales Order DMO using the Engagement category.
What is the impact of this action on future mappings?
  • A. A DLO with category Engagement can be mapped to any DMO using either Profile. Engagement, or Other categories.
  • B. Only Engagement category DLOs can be mapped to the Sales Order DMO. Sales Order gets assigned to the Engagement Category.
  • C. When mapping a Profile DLO to the Sales Order DMO, the category gets updated to Profile.
  • D. Sales Order DMO gets assigned to both the Profile and Engagement categories when mapping a Profile DLO.
Answer: B
Explanation:
Data Lake Objects (DLOs) and Data Model Objects (DMOs): In Salesforce Data Cloud, DLOs are mapped to DMOs to organize and structure data. Categories like Profile, Engagement, and Other define how these mappings are used.
Engagement Category: Mapping a DLO to the Engagement category indicates that the data is related to customer interactions and activities.
Impact on Future Mappings:
Engagement Category Restriction: When a DLO like Order-Headers is mapped to the Sales Order DMO under the Engagement category, future mappings of the Sales Order DMO are restricted to Engagement category DLOs.
Category Assignment: The Sales Order DMO is assigned to the Engagement category, meaning only DLOs categorized as Engagement can be mapped to it in the future.
Benefits:
Consistency: Ensures consistent data categorization and usage, aligning data with its intended purpose.
Accuracy: Helps in maintaining the integrity of data mapping and ensures that engagement-related data is accurately captured and utilized.
References:
Salesforce Data Cloud Mapping
Salesforce Data Cloud Categories

NEW QUESTION # 83
Which tool allows users to visualize and analyze unified customer data in Data Cloud?
  • A. Einstein Analytics
  • B. Salesforce CLI
  • C. Tableau
  • D. Heroku
Answer: C
Explanation:
Salesforce Data Cloud Overview: Salesforce Data Cloud enables organizations to unify and manage customer data from multiple sources, providing a comprehensive view of customer interactions and behaviors.
Visualization and Analysis: For visualizing and analyzing this unified data, Salesforce provides multiple tools, each serving different purposes. Tableau is particularly noted for its advanced analytics and visualization capabilities.
Tableau Integration: Tableau is integrated with Salesforce, allowing users to create detailed and interactive visualizations. It can connect directly to Salesforce Data Cloud, pulling in unified data for comprehensive analysis.
Capabilities: Tableau supports a wide range of data sources and formats, offering drag-and-drop features to create complex charts and dashboards. This makes it an ideal tool for analyzing the rich datasets managed within Salesforce Data Cloud.
References:
Salesforce Help: Tableau Integration
Salesforce Data Cloud Overview

NEW QUESTION # 84
A consultant has an activation that is set to publish every 12 hours, but has discovered that updates to the data prior to activation are delayed by up to 24 hours.
Which two areas should a consultant review to troubleshoot this issue?
Choose 2 answers
  • A. Review calculated insights to make sure they're run after the segments are refreshed.
  • B. Review data transformations to ensure they're run after calculated insights.
  • C. Review calculated insights to make sure they're run before segments are refreshed.
  • D. Review segments to ensure they're refreshed after the data is ingested.
Answer: C,D
Explanation:
The correct answer is B and C because calculated insights and segments are both dependent on the data ingestion process. Calculated insights are derived from the data model objects and segments are subsets of data model objects that meet certain criteria. Therefore, both of them need to be updated after the data is ingested to reflect the latest changes. Data transformations are optional steps that can be applied to the data streams before they are mapped to the data model objects, so they are not relevant to the issue. Reviewing calculated insights to make sure they're run after the segments are refreshed (option D) is also incorrect because calculated insights are independent of segments and do not need to be refreshed after them. References: Salesforce Data Cloud Consultant Exam Guide, Data Ingestion and Modeling, Calculated Insights, Segments

NEW QUESTION # 85
What are the two minimum requirements needed when using the Visual Insights Builder to create a calculated insight?
Choose 2 answers
  • A. At least one dimension
  • B. A WHERE clause
  • C. At least two objects to Join
  • D. At least one measure
Answer: A,D
Explanation:
Introduction to Visual Insights Builder:
The Visual Insights Builder in Salesforce Data Cloud is a tool used to create calculated insights, which are custom metrics derived from the existing data.
Reference: Salesforce Visual Insights Builder Documentation
Requirements for Creating Calculated Insights:
Measure: A measure is a quantitative value that you want to analyze, such as revenue, number of purchases, or total time spent on a platform.
Dimension: A dimension is a qualitative attribute that you use to categorize or filter the measures, such as date, region, or customer segment.
Reference: Salesforce Insights Builder Guide
Steps to Create a Calculated Insight:
Navigate to the Visual Insights Builder within Salesforce Data Cloud.
Select "Create New Insight" and choose the dataset.
Add at least one measure: This could be any metric you want to analyze, such as "Total Sales." Add at least one dimension: This helps to break down the measure, such as "Sales by Region." Reference: Salesforce Calculated Insights Creation Tutorial Practical Application:
Example: To create an insight on "Average Purchase Value by Region," you would need:
A measure: Total Purchase Value.
A dimension: Customer Region.
This allows for actionable insights, such as identifying high-performing regions.

NEW QUESTION # 86
An organization wants to enable users with the ability to identify and select text attributes from a picklist of options.
Which Data Cloud feature should help with this use case?
  • A. Value suggestion
  • B. Data harmonization
  • C. Transformation formulas
  • D. Global picklists
Answer: A
Explanation:
Value suggestion is a Data Cloud feature that allows users to see and select the possible values for a text field when creating segment filters. Value suggestion can be enabled or disabled for each data model object (DMO) field in the DMO record home. Value suggestion can help users to identify and select text attributes from a picklist of options, without having to type or remember the exact values. Value suggestion can also reduce errors and improve data quality by ensuring consistent and valid values for the segment filters. References: Use Value Suggestions in Segmentation, Considerations for Selecting Related Attributes

NEW QUESTION # 87
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