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NEW QUESTION # 11
A system admin recognizes the need to put a data management strategy in place.
What is a key component of data management strategy?
- A. Naming Convention
- B. Color Coding
- C. Data Backup
Answer: C
Explanation:
Explanation
Data Backup is a key component of a data management 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 damagein 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.
NEW QUESTION # 12
A sales manager wants to improve their processes using AI in Salesforce?
Which application of AI would be most beneficial?
- A. Data modeling and management
- B. Lead soring and opportunity forecasting
- C. Sales dashboards and reporting
Answer: B
Explanation:
Explanation
"Lead scoring and opportunity forecasting are applications of AI that would be most beneficial for a sales manager who wants to improve their processes using AI in Salesforce. Lead scoring can help prioritize leads based on their likelihood to convert, while opportunity forecasting can help predict future sales or revenue based on historical data and trends. These applications of AI can help optimize sales processes by providing insights and recommendations that can increase sales efficiency and effectiveness."
NEW QUESTION # 13
What is the main focus of the Accountability principle in Salesforce's Trusted AI Principles?
- A. Ensuring transparency In Al-driven recommendations and predictions
- B. Taking responsibility for one's actions toward customers, partners, and society
- C. Safeguarding fundamental human rights and protecting sensitive data
Answer: B
Explanation:
Explanation
"The main focus of the Accountability principle in Salesforce's Trusted AI Principles is taking responsibility for one's actions toward customers, partners, and society. Accountability means that AI systems should be designed and developed with respect for the impact and consequences of their actions on others.
Accountability also means that AI developers and users should be aware of and adhere to the ethical, legal, and regulatory standards and expectations of their industry and domain."
NEW QUESTION # 14
What is an example of ethical debt?
- A. Violating a data privacy law and falling to pay fines
- B. Launching an AI feature after discovering a harmful bias
- C. Delaying an AI product launch to retrain an AI data model
Answer: B
Explanation:
Explanation
"Launching an AI feature after discovering a harmful bias is an example of ethical debt. Ethical debt is a term that describes the potential harm or risk caused by unethical or irresponsible decisions or actions related to AI systems. Ethical debt can accumulate over time and have negative consequences for users, customers, partners, or society. For example, launching an AI feature after discovering a harmful bias can create ethical debt by exposing users to unfair or inaccurate results that may affect their trust, satisfaction, or well-being."
NEW QUESTION # 15
Which statement exemplifies Salesforces honesty guideline when training AI models?
- A. Ensure appropriate consent and transparency when using AI-generated responses.
- B. Control bias, toxicity, and harmful content with embedded guardrails and guidance.
- C. Minimize the AI models carbon footprint and environment impact during training.
Answer: A
Explanation:
Explanation
"Ensuring appropriate consent and transparency when using AI-generated responses is a statement that exemplifies Salesforce's honesty guideline when training AI models. Salesforce's honesty guideline is one of the Trusted AI Principles that states that AI systems should be designed and developed with respect for honesty and integrity in how they work and what they produce. Ensuring appropriate consent and transparency means respecting and honoring the choices and preferences of users regarding how their data is used or generated by AI systems. Ensuring appropriate consent and transparency also means providing clear and accurate information and documentation about the AI systems and their outputs."
NEW QUESTION # 16
Which best describes the different between predictive AI and generative AI?
- A. Predictive AI uses machine learning to classes or predict output from its input data whereas generative AI does not use machine learning to generate its output
- B. Predictive new and original output for a given input.
- C. Predictive AI and generative have the same capabilities differ in the type of input they receive:
predictive AI receives raw data whereas generation AI receives natural language.
Answer: B
Explanation:
Explanation
"The difference between predictive AI and generative AI is that predictive AI analyzes existing data to make predictions or recommendations based on patterns or trends, while generative AI creates new content based on existing data or inputs. Predictive AI is a type of AI that uses machine learning techniques to learn from existing data and make predictions or recommendations based on the data. For example, predictive AI can be used to forecast sales, revenue, or demand based on historical data and trends. Generative AI is a type of AI that uses machine learning techniques togenerate novel content such as images, text, music, or video based on existing data or inputs. For example, generative AI can be used to create realistic faces, write summaries, compose songs, or produce videos."
NEW QUESTION # 17
A business analyst (BA) wants to improve business by enhancing their sales processes and customer..
Which AI application should the BA use to meet their needs?
- A. Sales data cleansing and customer support data governance
- B. Machine learning models and chatbot predictions
- C. Lead scoring, opportunity forecasting, and case classification
Answer: C
Explanation:
Explanation
"Lead scoring, opportunity forecasting, and case classification are AI applications that can help a business analyst improve their sales processes and customer support. Lead scoring can help prioritize leads based on their likelihood to convert, opportunity forecasting can help predict future sales or revenue based on historical data and trends, and case classification can help categorize and route cases based on their attributes."
NEW QUESTION # 18
What are some key benefits of AI in improving customer experiences in CRM?
- A. Fully automates the customer service experience, ensuring seamless automated interactions with customers
- B. Streamlines case management by categorizing and tracking customer support cases, identifying topics, and summarizing case resolutions
- C. Improves CRM security protocols, safeguarding sensitive customer data from potential breaches and threats
Answer: B
Explanation:
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."
NEW QUESTION # 19
What is machine learning?
- A. AI that creates new content
- B. A data model used in Salesforce
- C. AI that can grow its intelligence
Answer: B
Explanation:
Explanation
"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."
NEW QUESTION # 20
A healthcare company implements an algorithm to analyze patient data and assist in medical diagnosis.
Which primary role does data Quality play In this AI application?
- A. Enhanced accuracy and reliability of medical predictions and diagnoses
- B. Reduced need for healthcare expertise in interpreting AI outouts
- C. Ensured compatibility of AI algorithms with the system's Infrastructure
Answer: A
Explanation:
Explanation
"Data quality plays a crucial role in enhancing the accuracy and reliability of medical predictions and diagnoses. Poor data quality can lead to inaccurate or misleading results, which can have serious consequences for patients' health and well-being. Therefore, it is important to ensure that the data used for AI applications in healthcare is accurate, complete, consistent, and relevant."
NEW QUESTION # 21
Cloud Kicks wants to optimize its business operations by incorporating AI into its CRM.
What should the company do first to prepare its data for use with AI?
- A. Determine data availability.
- B. Remove biased data.
- C. Determine data outcomes.
Answer: A
Explanation:
Explanation
Before using AI to optimize business operations, the company should first assess the availability and quality of its data. Data is the fuel for AI, and without sufficient and relevant data, AI cannot produce accurate and reliable results. Therefore, the company should identify what data it has, where it is stored, how it is accessed, and how it is maintained. This will help the company understand the feasibility and scope of its AI projects.
NEW QUESTION # 22
Cloud Kicks wants to create a custom service analytics application to analyze cases in Salesforce. The application should rely on accurate data to ensure efficient case resolution.
Which data quality dimension Is essential for this custom application?
- A. Duplication
- B. Age
- C. Consistency
Answer: C
Explanation:
Explanation
"Consistency is the data quality dimension that is essential for creating a custom service analytics application to analyze cases in Salesforce. Consistency means that the data values are uniform and follow a common standard or format across different records, fields, or sources. Consistent data can ensure that the custom application can accurately and efficiently analyze cases and provide meaningful insights."
NEW QUESTION # 23
What should organizations do to ensure data quality for their AI initiatives?
- A. Rely on AI algorithms to automatically handle data quality issues.
- B. Prioritize model fine-tuning over data quality improvements.
- C. Collect and curate high-quality data from reliable sources.
Answer: C
Explanation:
Explanation
"Organizations should collect and curate high-quality data from reliable sources to ensure data quality for their AI initiatives. High-quality data means that the data is accurate, complete, consistent, relevant, and timely for the AI task. Reliable sources mean that the data is trustworthy, credible, and authoritative. Collecting and curating high-quality data from reliable sources can improve the performance and reliability of AI systems."
NEW QUESTION # 24
What is a benefit of a diverse, balanced, and large dataset?
- A. Training time
- B. Data privacy
- C. Model accuracy
Answer: C
Explanation:
Explanation
"Model accuracy is a benefit of a diverse, balanced, and large dataset. A diverse dataset can capture a variety of features and patterns that are relevant for the AI task. A balanced dataset can avoid overfitting or underfitting the model to a specific subset of data. A large dataset can provide enough information for the model to learn from and generalize well to new data."
NEW QUESTION # 25
Cloud kicks wants to develop a solution to predict customers' interest based on historical data. The company found that employee region uses a text field to capture the product category while employee from all other locations use a picklist.
Which dimension of data quality is affected in this scenario?
- A. Consistency
- B. Accuracy
- C. Completeness
Answer: A
Explanation:
Explanation
"Consistency is the dimension of data quality that is affected in this scenario. Consistency means that the data values are uniform and follow a common standard or format across different records, fields, or sources.
Inconsistent data can cause confusion, errors, or duplication in data analysis andprocessing. For example, using different field types for the same attribute can affect the consistency of the data."
NEW QUESTION # 26
How does the "right of least privilege" reduce the risk of handling sensitive personal data?
- A. By applying data retention policies
- B. By reducing how many attributes are collected
- C. By limiting how many people have access to data
Answer: C
Explanation:
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."
NEW QUESTION # 27
To avoid introducing unintended bias to an AI model, which type of data should be omitted?
- A. Engagement
- B. Transactional
- C. Demographic
Answer: C
Explanation:
Explanation
"Demographic data should be omitted to avoid introducing unintended bias to an AI model. Demographic data is data that describes the characteristics of a population or a group of people, such as age, gender, race, ethnicity, income, education, or occupation. Demographic data can lead to bias if it is used to discriminate or treat people differently based on their identity or attributes. Demographic data can also reflect existing biases or stereotypes in society or culture, which can affect the fairness and ethics of AI systems."
NEW QUESTION # 28
Cloud Kicks discovered multiple variations of state and country values in contact records.
Which data quality dimension is affected by this issue?
- A. Consistency
- B. Accuracy
- C. Usage
Answer: A
Explanation:
Explanation
"Consistency is the data quality dimension that is affected by multiple variations of state and country values in contact records. Consistency means that the data values are uniform and follow a common standard or format across different records, fields, or sources. Inconsistent data can cause confusion, errors, or duplication in data analysis and processing."
NEW QUESTION # 29
A financial institution plans a campaign for preapproved credit cards?
How should they implement Salesforce's Trusted AI Principle of Transparency?
- A. Flag sensitive 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.
Answer: A
Explanation:
Explanation
"Flagging sensitive variables and their proxies to prevent discriminatory lending practices is 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 variables that 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."
NEW QUESTION # 30
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