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Salesforce Data-Con-101 認定試験の出題範囲：

トピック	出題範囲
トピック 1	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.
トピック 2	Data Ingestion and Modeling: This domain addresses bringing data into Data Cloud and structuring it properly through transformation, ingestion from various sources, and data mapping. It emphasizes best practices for modeling data to support identity resolution and validating ingested data using available tools.
トピック 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.

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Salesforce Certified Data Cloud Consultant 認定 Data-Con-101 試験問題 (Q145-Q150):

質問 # 145
A consultant needs to minimize the difference between a Data Cloud segment population and Marketing Cloud data extension count to determine the true size of segments for campaign planning.
What should the consultant recommend to filter the segments by to accomplish this?

A. Geographical divisions
B. Business units
C. Marketing Cloud Journeys
D. User preferences for marketing outreach

正解：A

質問 # 146
What does the Source Sequence reconciliation rule do in identity resolution?

A. Identifies which data sources should be used in the process of reconcillation by prioritizing themost recently updated data source
B. Includes data from sources where the data is most frequently occurring
C. Identifies which individual records should be merged into a unified profile by setting a priority forspecific data sources
D. Sets the priority of specific data sources when building attributes in a unified profile, such as afirst or last name

正解：D

解説：
The Source Sequence reconciliation rule sets the priority of specific data sources when building attributes in a unified profile, such as a first or last name. This rule allows you to define which data source should be used as the primary source of truth for each attribute, and which data sources should be used as fallbacks in case the primary source is missing or invalid. For example, you can set the Source Sequence rule to use data from Salesforce CRM as the first priority, data from Marketing Cloud as the second priority, and data from Google Analytics as the third priority for the first name attribute. This way, the unified profile will use the first name value from Salesforce CRM if it exists, otherwise it will use the value from Marketing Cloud, and so on. This rule helps you to ensure the accuracy and consistency of the unified profile attributes across different data sources. References: Salesforce Data Cloud Consultant Exam Guide, Identity Resolution, Reconciliation Rules

質問 # 147
A user is not seeing suggested values from newly-modeled data when building a segment.
What is causing this issue?

A. Value suggestion is still processing and to be available.
B. Value suggestion can only work on direct attributes and not related attributes.
C. Value suggestion will only return result for the first 50 values of a specific attribute.
D. Value suggestion requires Data Aware Specialist permissions at a minimum.

正解：A

解説：
Value suggestion is a feature that allows users to see suggested values for data model object (DMO) fields when creating segment filters. However, this feature can take up to 24 hours to process and display the values for newly-modeled data. Therefore, if a user is not seeing suggested values from newly-modeled data, it is likely that the value suggestion is still processing and will be available soon. The other options are incorrect because value suggestion does not require any specific permissions, can work on both direct and related attributes, and can return more than 50 values for a specific attribute, depending on the data type and frequency of the values. References: Use Value Suggestions in Segmentation, Data Cloud Limits and Guidelines

質問 # 148
What is a typical use case for Salesforce Data Cloud?

A. Storing CRM data on promises
B. Data synchronization across the Salesforce ecosystem
C. Data harmonization across multiple platforms
D. Sending personalized emails at scale

正解：C

解説：
A typical use case for Salesforce Data Cloud is data harmonization across multiple platforms . Here's why:
Understanding Salesforce Data Cloud
Salesforce Data Cloud is designed to aggregate, unify, and analyze customer data from multiple sources, including CRM, Marketing Cloud, external systems, and third-party platforms.
Its primary purpose is to provide a unified view of customer data for personalized experiences and actionable insights.
Why Data Harmonization Across Multiple Platforms?
Data Harmonization :
Data Cloud harmonizes data by standardizing and cleansing it from disparate sources.
This ensures consistency and accuracy across platforms, enabling organizations to create a single source of truth for customer data.
Use Case Alignment :
Data harmonization is a core functionality of Data Cloud, making it the most relevant use case among the options provided.
Other Options Are Less Relevant :
A). Data synchronization across the Salesforce ecosystem : While Data Cloud integrates with Salesforce products, its primary focus is on unifying data from multiple platforms, not just Salesforce.
B). Storing CRM data on premises : Data Cloud is a cloud-based solution and does not support on-premises storage.
D). Sending personalized emails at scale : This is a use case for Marketing Cloud, not Data Cloud.
Steps to Achieve Data Harmonization
Step 1: Ingest Data
Bring in customer data from multiple sources (e.g., CRM, Marketing Cloud, external systems) into Data Cloud.
Step 2: Standardize and Cleanse Data
Use batch or streaming transformations to standardize formats, remove duplicates, and cleanse data.
Step 3: Create Unified Profiles
Use identity resolution to merge related records into a single unified profile.
Step 4: Activate Insights
Leverage the harmonized data for segmentation, personalization, and analytics.
Conclusion
The most typical use case for Salesforce Data Cloud is data harmonization across multiple platforms , enabling organizations to unify and leverage customer data effectively.

質問 # 149
Northern Trail Outfitters wants to implement Data Cloud and has several use cases in mind.
Which two use cases are considered a good fit for Data Cloud?
Choose 2 answers

A. To use harmonized data to more accurately understand the customer and business impact
B. To ingest and unify data from various sources to reconcile customer identity
C. To create and orchestrate cross-channel marketing messages
D. To eliminate the need for separate business intelligence and IT data management tools

正解：A、B

解説：
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 use cases that are considered a good fit for Data Cloud are:
To ingest and unify data from various sources to reconcile customer identity. Data Cloud can help customers bring all their data, whether streaming or batch, into Salesforce and map it to a common data model. Data Cloud can also help customers resolve identities across different channels and sources and create unified profiles of their customers.
To use harmonized data to more accurately understand the customer and business impact. Data Cloud can help customers transform and cleanse their data before using it, and enrich it with calculated insights and related attributes. Data Cloud can also help customers create segments and audiences based on their data and activate them in any channel. Data Cloud can also help customers use AI to predict customer behavior and outcomes.
The other two options are not use cases that are considered a good fit for Data Cloud. Data Cloud does not provide features to create and orchestrate cross-channel marketing messages, as this is typically handled by other Salesforce solutions such as Marketing Cloud. Data Cloud also does not eliminate the need for separate business intelligence and IT data management tools, as it is designed to work with them and complement their capabilities.
Learn How Data Cloud Works
About Salesforce Data Cloud
Discover Use Cases for the Platform
Understand Common Data Analysis Use Cases

質問 # 150
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