2024年最新の有効なSalesforce-AI-Associateテスト解答とSalesforce試験PDF問題を試そう
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質問 # 60
Salesforce defines bias as using a person's Immutable traits to classify them or market to them.
Which potentially sensitive attribute is an example of an immutable trait?
- A. Email address
- B. Nickname
- C. Financial status
正解：C
解説：
Explanation
"Financial status is an example of an immutable trait. Immutable traits are characteristics that are inherent, fixed, or unchangeable. For example, financial status is an immutable trait because it is determined by factors beyond one's control, such as birth, inheritance, or economic conditions. Nickname and email address are not immutable traits because they can be changed by choice or preference."
質問 # 61
What is a Key consideration regarding data quality in AI implementation?
- A. Integration process of AI models with Salesforce workflows
- B. Techniques from customizing AI features in Salesforce
- C. Data's role in training and fine-tuning Salesforce AI models
正解：C
解説：
Explanation
"Data's role in training and fine-tuning Salesforce AI models is a key consideration regarding data quality in AI implementation. Data quality is the degree to which data is accurate, complete, consistent, relevant, and timely for the AI task. Data quality can affect the performance and reliability of AI systems, as they depend on the quality of the data they use to learn from and make predictions. Data's role in training and fine-tuning Salesforce AI models means understanding how data is used to build, train, test, and improve AI models in Salesforce, such as Einstein Prediction Builder or Einstein Discovery."
質問 # 62
What is the best method to safeguard customer data privacy?
- A. Track customer data consent preferences.
- B. Archive customer data on a recurring schedule.
- C. Automatically anonymize all customer data.
正解：A
解説：
Explanation
"Tracking customer data consent preferences is the best method to safeguard customer data privacy. Data privacy is the right of individuals to control how their personal data is collected, used, shared, or stored by others. Tracking customer data consent preferences means respecting and honoring the choices and preferences of customers regarding their personal data. Tracking customer data consent preferences can help ensure compliance with data privacy laws and regulations, as well as build trust and loyalty with customers."
質問 # 63
How does data quality impact the trustworthiness of Al-driven decisions?
- A. High-quality data improves the reliability and credibility of Al-driven decisions, fostering trust among users.
- B. Low-quality data reduces the risk of overfitting the model, improving the trustworthiness of the predictions.
- C. The use of both low-quality and high-quality data can improve the accuracy and reliability of AI-driven decisions.
正解：A
解説：
"High-quality dataimproves the reliability and credibility of AI-driven decisions, fostering trust among users.
High-quality data means that the data is accurate, complete, consistent, relevant, and timely for the AI task.
High-quality data can improve the performance and reliability of AI systems, as they have enough and correct information to learn from and make accurate predictions. High-quality data can also improve the trustworthiness of AI-driven decisions, as users can have more confidence and satisfaction in using AIsystems."
質問 # 64
Cloud Kicks implements a new product recommendation feature for its shoppers that recommends shoes of a given color to display to customers based on the color of the products from their purchase history.
Which type of bias is most likely to be encountered in this scenario?
- A. Survivorship
- B. Societal
- C. Confirmation
正解：C
解説：
"Confirmation bias is most likely to be encountered in this scenario. Confirmation bias is a type of bias that occurs when data or information confirms or supports one'sexisting beliefs or expectations. For example, confirmation bias can occur when a product recommendation feature only recommends shoes of a given color based on the customer's purchase history, without considering other factors or preferences that may influence their choice."
質問 # 65
Which type of bias imposes a system 's values on others?
- A. Societal
- B. Association
- C. Automation
正解：A
質問 # 66
How does an organization benefit from using AI to personalize the shopping experience of online customers?
- A. Customers are more likely to visit competitor sites that personalize their experience.
- B. Customers are morelikely to share personal information with a site that personalizes their experience.
- C. Customers are more likely to be satisfied with their shopping experience.
正解：C
解説：
"An organization benefits from using AI to personalize the shopping experience of online customers by increasing customer satisfaction. AI can help provide customized and relevant product recommendations, offers, or content based on the customers' preferences, behavior, or needs. AI can also help create a more engaging and interactive shopping experience by using natural language processing (NLP) or computer vision techniques. Personalized shopping experiences can improve customer satisfaction by meeting their expectations, needs, and interests."
質問 # 67
What are some key benefits of AI in improving customer experiences in CRM?
- A. Streamlines case management by categorizing and tracking customer support cases, identifying topics, and summarizing case resolutions
- B. Improves CRM security protocols, safeguarding sensitive customer data from potential breaches and threats
- C. Fully automates the customer service experience, ensuring seamless automated interactions with customers
正解：A
解説：
Explanation
"Streamlining case management by categorizing and tracking customer support cases, identifying topics, and summarizing case resolutions are some key benefits of AI in improving customer experiences in CRM. AI can help automate and optimize various aspects of customer service, such as routing cases to the right agents, providing relevant information or suggestions, and generating reports or insights. AI can also help enhance customer satisfaction and loyalty by reducing wait times, improving response quality, and providing personalized solutions."
質問 # 68
How does the "right of least privilege" reduce the risk of handling sensitive personal data?
- A. By reducing how many attributes are collected
- B. By limiting how many people have access to data
- C. By applying data retention policies
正解：B
解説：
Explanation
"The "right of least privilege" reduces the risk of handling sensitive personal data by limiting how many people have access to data. The "right of least privilege" is a security principle that states that each user or system should have the minimum level of access or privilege necessary to perform their tasks or functions.
The "right of least privilege" can help protect sensitive personal data from unauthorized access, misuse, or leakage."
質問 # 69
What does the term "data completeness" refer to in the context of data quality?
- A. The ability to access data from multiple sources in real time
- B. The process of aggregating multiple datasets from various databases
- C. The degree to which all required data points are present in the dataset
正解：C
解説：
Data completeness is a measure of data quality that assesses whether all required data points are present in a dataset. It checks for missing values or gaps in data necessary for accurate analysis and decision-making. In the context of Salesforce, ensuring data completeness is crucial for the effectiveness of CRM operations, reporting, and AI-driven applications like Salesforce Einstein, which rely on complete data to function optimally. Salesforce provides various tools and features, such as data validation rules and batch data import processes, that help maintain data completeness across its platform. Detailed guidance on managing data quality in Salesforce can be found in the Salesforce Help documentation on data management at Salesforce Help Data Management.
質問 # 70
A data quality expert at Cloud Kicks want to ensure that each new contact contains at least an email address
...
Which feature should they use to accomplish this?
- A. Autofill
- B. Validation rule
- C. Duplicate matching rule
正解：B
解説：
"A validation rule should be used to ensure that each new contact contains at least an email address or phone number. A validation rule is a feature that checks the data entered by users for errors before saving it to Salesforce. A validation rule can help ensure data quality by enforcing certain criteria or conditions for the data values."
質問 # 71
A system admin recognizes the need to put a data management strategy in place.
What is a key component of data management strategy?
- A. Data Backup
- B. Color Coding
- C. Naming Convention
正解：A
解説：
Data Backup is a key component of a datamanagement strategy. A data backup is a process of creating and storing copies of data in a separate location or device to prevent data loss or damage in case of a disaster, accident, or malicious attack. A data backup can help ensure data availability, reliability, and security by allowing data to be restored or recovered in the event of a data breach, corruption, or deletion. A data management strategy should include a data backup plan that defines the frequency, scope, method, and location of data backups, as well as the roles and responsibilities of the data backup team.
質問 # 72
Cloud Kicks plans to use automated chat as its primary support channel.
Which Einstein feature should they use?
- A. Bots
- B. Next Best Action
- C. Discovery
正解：A
解説：
For Cloud Kicks, using automated chat as the primary support channel, the recommended Einstein feature is Bots. Einstein Bots are designed to automate customer interactions on common issues through chat and messaging platforms. They can handle routine requests, provide quick answers to frequently asked questions, and escalate more complex issues to human agents. Using Einstein Bots helps improve customer service efficiency and speed, leading to enhanced customer satisfaction. To learn more about setting up and optimizing Einstein Bots for a business, you can visit the Salesforce documentation on Einstein Bots at Salesforce Einstein Bots.
質問 # 73
A financial institution plans a campaign for preapproved credit cards?
How should they implement Salesforce's Trusted AI Principle of Transparency?
- A. Flagsensitive variables and their proxies to prevent discriminatory lending practices.
- B. Communicate how risk factors such as credit score can impact customer eligibility.
- C. Incorporate customer feedback into the model's continuous training.
正解：A
解説：
"Flagging sensitive variables and their proxies to prevent discriminatory lending practicesis how they should implement Salesforce's Trusted AI Principle of Transparency. Transparency is one of the Trusted AI Principles that states that AI systems should be designed and developed with respect for clarity and openness in how they work and why they make certain decisions. Transparency also means that AI users should be able to access relevant information and documentation about the AI systems they interact with. Flagging sensitive variables and their proxies means identifying and marking variablesthat can potentially cause discrimination or unfair treatment based on a person's identity or characteristics, such as age, gender, race, income, or credit score. Flagging sensitive variables and their proxies can help implement Transparency by allowing users to understand and evaluate the data used or generated by AI systems."
質問 # 74
What is a possible outcome of poor data quality?
- A. Biases in data can be inadvertently learned and amplified by AI systems.
- B. AI models maintain accuracy but have slower response times.
- C. AI predictions become more focused and less robust.
正解：A
解説：
Explanation
"A possible outcome of poor data quality is that biases in data can be inadvertently learned and amplified by AI systems. Poor data quality means that the data is inaccurate, incomplete, inconsistent, irrelevant, or outdated for the AI task. Poor data quality can affect the performance and reliability of AI systems, as they may not have enough or correct information to learn from or make accurate predictions. Poor data quality can also introduce or exacerbate biases in data, such as human bias, societal bias, or confirmation bias, which can affect the fairness and ethics of AI systems."
質問 # 75
Cloud Kicks wants to develop a solutionto predict customers product interests based on historical data. The company found that employees from one region use a text field to capture the product category, while employees from all other locations use a plckllst.
Which data quality dimension is affected in this scenario?
- A. Completeness
- B. Consistency
- C. Accuracy
正解：B
解説：
"Consistency is the data quality dimension that is affected in this scenario. Consistency means that the data values are uniform and follow a common standard or format acrossdifferent records, fields, or sources.
Inconsistent data can cause confusion, errors, or duplication in data analysis and processing. For example, using different field types for the same attribute can affect the consistency of the data."
質問 # 76
What is machine learning?
- A. AI that creates new content
- B. AI that can grow its intelligence
- C. A data model used in Salesforce
正解：C
解説：
"A data model is a machine learning feature used in Salesforce. A data model is a representation or abstraction of a real-world phenomenon or process using data structures and algorithms. A data model can be used to describe, analyze, or predict various aspects of the phenomenon or process using machine learning techniques."
質問 # 77
Cloud Kicks wants to use Einstein Prediction Builder to determine a customer's likelihood of buying specific products; however, data quality is a...
How can data quality be assessed quality?
- A. Build a Data Management Strategy.
- B. Leverage data quality apps from AppExchange
- C. Build reports to expire the data quality.
正解：B
解説：
Explanation
"Leveraging data quality apps from AppExchange is how data quality can be assessed. Data quality is the degree to which data is accurate, complete, consistent, relevant, and timely for the AI task. Data quality can affect the performance and reliability of AI systems, as they depend on the quality of the data they use to learn from and make predictions. Leveraging data quality apps from AppExchange means using third-party applications or solutions that can help measure, monitor, or improve data quality in Salesforce."
質問 # 78
An administrator at Cloud Kicks wants to ensure that a field is set up on the customer record so their preferred name can be captured.
Which Salesforce field type should the administrator use to accomplish this?
- A. Multi-Select Picklist
- B. Text
- C. Rich Text Area
正解：B
解説：
Explanation
"A text field type should be used to capture the customer's preferred name. A text field type allows the user to enter any combination of letters, numbers, or symbols. A text field type can be used to store names, addresses, phone numbers, or other personal information."
質問 # 79
What is the role of Salesforce Trust AI principles in the context of CRM system?
- A. Outlining the technical specifications for AI integration
- B. Guiding ethical and responsible use of AI
- C. Providing a framework for AI data model accuracy
正解：B
解説：
"The role of Salesforce Trust AI principles in the context of CRM systems is guiding ethical and responsible use of AI. Salesforce Trust AI principles are a set of guidelines and best practicesfor developing and using AI systems in a responsible and ethical way. The principles include Accountability, Fairness & Equality, Transparency & Explainability, Privacy & Security, Reliability & Safety, Inclusivity & Diversity, Empowerment & Education. The principles aim to ensure that AI systems are aligned with the values and interests of customers, partners, and society."
質問 # 80
Which features of Einstein enhance sales efficiency and effectiveness?
- A. Opportunity Scoring, Lead Scoring, Account Insights
- B. Opportunity Scoring, Opportunity List View, Opportunity Dashboard
- C. Opportunity List View, Lead List View, Account List view
正解：A
解説：
Explanation
"Opportunity Scoring, Lead Scoring, Account Insights are features of Einstein that enhance sales efficiency and effectiveness. Opportunity Scoring and Lead Scoring use predictive models to assign scores to opportunities and leads based on their likelihood to close or convert. Account Insights use natural language processing (NLP) to provide relevant news and insights about accounts based on their industry, location, or events."
質問 # 81
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