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Salesforce Data-Con-101 考試大綱：

主題	簡介
主題 1	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.
主題 2	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.
主題 3	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.
主題 4	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.

>> Data-Con-101認證 <<

Data-Con-101考古題介紹 - Data-Con-101指南

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最新的 Salesforce Data Cloud Data-Con-101 免費考試真題 (Q28-Q33):

問題 #28
Which two common use cases can be addressed with Data Cloud?
Choose 2 answers

A. Understand and act upon customer data to drive more relevant experiences.
B. Safeguard critical business data by serving as a centralized system for backup and disasterrecovery.
C. Govern enterprise data lifecycle through a centralized set of policies and processes.
D. Harmonize data from multiple sources with a standardized and extendable data model.

答案：A,D

解題說明：
Data Cloud is a data platform that can help customers connect, prepare, harmonize, unify, query, analyze, and act on their data across various Salesforce and external sources. Some of the common use cases that can be addressed with Data Cloud are:
Understand and act upon customer data to drive more relevant experiences. Data Cloud can help customers gain a 360-degree view of their customers by unifying data from different sources and resolving identities across channels. Data Cloud can also help customers segment their audiences, create personalized experiences, and activate data in any channel using insights and AI.
Harmonize data from multiple sources with a standardized and extendable data model. Data Cloud can help customers transform and cleanse their data before using it, and map it to a common data model that can be extended and customized. Data Cloud can also help customers create calculated insights and related attributes to enrich their data and optimize identity resolution.
The other two options are not common use cases for Data Cloud. Data Cloud does not provide data governance or backup and disaster recovery features, as these are typically handled by other Salesforce or external solutions.
Learn How Data Cloud Works
About Salesforce Data Cloud
Discover Use Cases for the Platform
Understand Common Data Analysis Use Cases

問題 #29
How should a Data Cloud consultant successfully apply consent during segmentation?

A. Include the Consent Status for any applicable channels of engagement in the filter criteria for each segment.
B. Include the Unified Profile during segmentation for any applicable channels of engagement.
C. Include Party Identification for any applicable channels of engagement in the filter criteria for each segment.
D. Include the Consent Status from the golden record during activation for any applicable channels of engagement.

答案：A

解題說明：
Understanding Consent Management in Salesforce Data Cloud:
Consent management is crucial for maintaining compliance with data protection regulations like GDPR and CCPA. It ensures that customer data is used in accordance with their given permissions.
Reference: Salesforce Consent Management Documentation
Role of Consent Status in Segmentation:
The Consent Status indicates whether a customer has agreed or opted-in to specific types of communication or data processing activities.
During segmentation, applying the correct consent status ensures that only those customers who have provided the necessary permissions are included in targeted campaigns.
Reference: Salesforce Data Cloud Consent Management Overview
Implementation of Consent Status in Segmentation:
When creating segments, including the Consent Status in the filter criteria helps to dynamically segment the audience based on their consent preferences.
This ensures compliance and improves the relevance and personalization of communications.
Example: If creating a marketing campaign for email outreach, the segment would only include customers who have a consent status allowing email communication.
Reference: Salesforce Data Cloud Segmentation Guide
Practical Application:
Go to the segmentation tool within Salesforce Data Cloud.
In the filter criteria, add the Consent Status attribute relevant to the channel of engagement.
Define the values (e.g., Opted-in, Subscribed) to ensure only compliant customer profiles are included.

問題 #30
Northern Trail Outfitters (NTO) is getting ready to start ingesting its CRM data into Data Cloud.
While setting up the connector, which type of refresh should NTO expect when the data stream is deployed for the first time?

A. Full refresh
B. Manual refresh
C. Partial refresh
D. Incremental

答案：A

解題說明：
Data Stream Deployment: When setting up a data stream in Salesforce Data Cloud, the initial deployment requires a comprehensive data load.
Types of Refreshes:
Incremental Refresh: Only updates with new or changed data since the last refresh.
Manual Refresh: Requires a user to manually initiate the data load.
Partial Refresh: Only a subset of the data is refreshed.
Full Refresh: Loads the entire dataset into the system.
First-Time Deployment: For the initial deployment of a data stream, a full refresh is necessary to ensure all data from the source system is ingested into Salesforce Data Cloud.
References:
Salesforce Documentation: Data Stream Setup
Salesforce Data Cloud Guide

問題 #31
A customer notices that their consolidation rate is low across their account unification. They have mapped Account to the Individual and Contact Point Email DMOs.
What should they do to increase their consolidation rate?

A. Increase the number of matching rules.
B. Update their account address details in the data source
C. Disable the individual identity ruleset.
D. Change reconciliation rules to Most Occurring.

答案：A

解題說明：
Consolidation Rate: The consolidation rate in Salesforce Data Cloud refers to the effectiveness of unifying records into a single profile. A low consolidation rate indicates that many records are not being successfully unified.
Matching Rules: Matching rules are critical in the identity resolution process. They define the criteria for identifying and merging duplicate records.
Solution:
Increase Matching Rules: Adding more matching rules improves the system's ability to identify duplicate records. This includes matching on additional fields or using more sophisticated matching algorithms.
Steps:
Access the Identity Resolution settings in Data Cloud.
Review the current matching rules.
Add new rules that consider more fields such as phone number, address, or other unique identifiers.
Benefits:
Improved Unification: Higher accuracy in matching and merging records, leading to a higher consolidation rate.
Comprehensive Profiles: Enhanced customer profiles with consolidated data from multiple sources.
References:
Salesforce Data Cloud Identity Resolution
Salesforce Help: Matching Rules

問題 #32
A customer has a calculated insight about lifetime value.
What does the consultant need to be aware of if the calculated insight.
needs to be modified?

A. New measures can be added.
B. Existing dimensions can be removed.
C. Existing measures can be removed.
D. New dimensions can be added.

答案：D

解題說明：
A calculated insight is a multidimensional metric that is defined and calculated from data using SQL expressions. A calculated insight can include dimensions and measures. Dimensions are the fields that are used to group or filter the data, such as customer ID, product category, or region. Measures are the fields that are used to perform calculations or aggregations, such as revenue, quantity, or average order value. A calculated insight can be modified by editing the SQL expression or changing the data space. However, the consultant needs to be aware of the following limitations and considerations when modifying a calculated insight12:
Existing dimensions cannot be removed. If a dimension is removed from the SQL expression, the calculated insight will fail to run and display an error message. This is because the dimension is used to create the primary key for the calculated insight object, and removing it will cause a conflict with the existing data.
Therefore, the correct answer is B.
New dimensions can be added. If a dimension is added to the SQL expression, the calculated insight will run and create a new field for the dimension in the calculated insight object. However, the consultant should be careful not to add too many dimensions, as this can affect the performance and usability of the calculated insight.
Existing measures can be removed. If a measure is removed from the SQL expression, the calculated insight will run and delete the field for the measure from the calculated insight object. However, the consultant should be aware that removing a measure can affect the existing segments or activations that use the calculated insight.
New measures can be added. If a measure is added to the SQL expression, the calculated insight will run and create a new field for the measure in the calculated insight object. However, the consultant should be careful not to add too many measures, as this can affect the performance and usability of the calculated insight. References: Calculated Insights, Calculated Insights in a Data Space.

問題 #33
......

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