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Question No. 1
In the context of Salesforce's Trusted Al Principles, what does the principle of Responsibility primarily focus on?
A. Ensuring ethical use of Al
B. Outlining the technical specifications for Al integration
C. Providing a framework for data model accuracy |
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Definition
| A. Ensuring ethical use of Al |
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Question No. 2
Cloud Kicks wants to evaluate the quality of its sales data.
Which first step should they take for the data quality assessment?
A. Plan and align territories,
B. Run a new report or dashboard.
C. Identify business objectives. |
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Definition
| C. Identify business objectives. |
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Question No. 3
What is the societal implication of excluding ethics in AI development?
A. Faster and cheaper development
B. More innovation and creativity
C. Harm to marginalized communities |
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Definition
| C. Harm to marginalized communities |
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Question No. 4
What is Salesforce's Trusted AI Principle of Transparency?
A. The customization of AT features to meet specific business requirements
B. The integration of AT models with Salesforce workflows
C. The clear and understandable explanation of Al decisions and actions |
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Definition
| C. The clear and understandable explanation of Al decisions and actions |
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Question No. 5
A sales manager wants to use AI to help sales representatives log their calls quicker and more accurately.
Which functionality provides the best solution?
A. Call Summaries
B. Sales Dialer
C. Auto-Generated Sales Tasks |
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Question No. 6
Cloud Kicks prepares a dataset for an AI model and identifies some inconsistencies in the data.
What is the most appropriate action the company should take?
A. Adjust the Al model to account for the data inconsistencies.
B. Increase the quantity of data being used for training the model
C. Investigate the data inconsistencies and apply data quality techniques. |
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Definition
| C. Investigate the data inconsistencies and apply data quality techniques. |
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Question No. 7
Cloud Kicks relies on data analysis to optimize its product recommendations for customers.
How will incomplete data quality impact the company's recommendations?
A. The response time for the product
B. The accuracy of the product
C. The diversity of the product |
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Definition
| The accuracy of the product |
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Question No. 8
How does AI assist in lead qualification?
A.Scores leads based on customer data
B.Creates personalized SMS campaigns
C.Automatically interacts with prospects |
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Definition
| A.Scores leads based on customer data |
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Question No. 9
Cloud Kicks wants to improve the quality of its AI model's predictions with the use of a large amount of data.
Which data quality element should the company focus on?
A.Accuracy
B.Location
C.Volume |
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Question No. 10
Which action introduces bias in the training data used for AI algorithms?
A. Using a large dataset that is computationally expensive
B. Using a dataset that represents diverse perspectives and populations
C. Using a dataset that underrepresents perspectives and populations |
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Definition
| C. Using a dataset that underrepresents perspectives and populations |
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Question No. 11
What should an organization do to enforce consistency across accounts for newly entered records?
A. Merge all duplicate accounts into a single record when duplicate entries are detected.
B. Input the data exactly as it appears from the source, such as the company's website or social media,
C. Implement naming conventions or a predefined list of user-selectable values for organization-wide records. |
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Definition
| C. Implement naming conventions or a predefined list of user-selectable values for organization-wide records. |
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Question No. 12
Which best describes the difference between predictive AI and generative Al?
A. Predictive AT uses machine learning to classify or predict outputs from its input data whereas generative Al does not use machine learning to generate its output.
B. Predictive Al uses machine learning to classify or predict outputs from its input data whereas generative Al uses machine learning to generate new and original output for a given input
C. Predictive Al and generative Al have the same capabilities but differ in the type of input they receive; predictive AT receives raw data whereas generative AT receives natural language. |
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Definition
| B. Predictive Al uses machine learning to classify or predict outputs from its input data whereas generative Al uses machine learning to generate new and original output for a given input |
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Question No. 13
How does poor data quality affect predictive and generative AI models?
A. Creates inaccurate results
B. Increases raw data volume
C. Decreases storage efficiency |
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Definition
| A. Creates inaccurate results |
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Question No. 14
Which AI tool is a web of connections, guided by weights and biases?
A.Neural networks
B.Predictive Analytics
C.Rules- based systems
D.Mark this item for later review, |
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Question No. 15
Which type of AI can enhance customer service agents' email responses by analyzing the written content of previous emails?
A. Natural language processing
B. Machine learning
C. Deep learning |
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Definition
| A. Natural language processing |
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Question No. 16
What is one technique to mitigate bias and ensure fairness in AI applications?
A. Ongoing auditing and monitoring of data that is used in AI applications
B. Excluding data features from the Al application to benefit a population
C. Using data that contains more examples of minority groups than majority groups |
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Definition
| A. Ongoing auditing and monitoring of data that is used in AI applications |
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Question No. 17
A sales manager is looking to enhance the quality of lead data in their CRM system.
Which process will most likely help the team accomplish this goal?
A. Redesign the lead conversion process,
B. Review and update missing lead information.
C. Prioritize active leads quarterly. |
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Definition
| B. Review and update missing lead information. |
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Question No. 18
Cloud Kicks wants to evaluate its data quality to ensure accurate and up-to-date records.
Which type of records negatively impact data quality?
A. Structured
B. Complete
C. Duplicate |
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Question No. 19
A business analyst (BA) is preparing a new use case for Al. They run a report to check for null values in the attributes they plan to use.
Which data quality component Is the BA verifying by checking for null values?
A.Duplication
B.Usage
C.Completeness |
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Question No. 20
A developer has a large amount of data, but it is scattered across different systems and is not standardized.
Which key data quality element should they focus on to ensure the effectiveness of the AI models?
A. Performance
B. Consistency
C. Volume |
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Question No. 21
What are the potential consequences of an organization suffering from poor data quality?
A. Low employee morale, stock devaluation, and inability to attract top talent
B. Revenue loss, poor customer service, and reputational damage
C. Technical debt, monolithic system architecture, and slow ETL throughput |
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Definition
| B. Revenue loss, poor customer service, and reputational damage |
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Question No. 22
What is the significance of the explainability of trusted AI systems?
A. Increases the complexity of AI models
B. Enhances the security and accuracy of AI models
C. Describes how Al models make decisions |
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Definition
| C. Describes how Al models make decisions |
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Question No. 23
Cloud Kicks' latest email campaign is struggling to attract new customers.
How can AI increase the company's customer email engagement?
A. Create personalized emails
B. Resend emails to inactive recipients
C. Remove invalid email addresses |
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Definition
| A. Create personalized emails |
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Question No. 24
Cloud Kicks plans to use automated chat as its primary support channel.
Which Einstein feature should they use?
A. Discovery
B. Bots
C. Next Best Action |
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Question No. 25
What does the term 'data completeness' refer to in the context of data quality?
A. The degree to which all required data points are present in the dataset
B. The process of aggregating multiple datasets from various databases
C. The ability to access data from multiple sources in real-time |
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| A. The degree to which all required data points are present in the dataset |
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Question No. 26
What are predictive analytics, machine learning, natural language processing (NLP), and computer vision?
A. Different types of data models used in Salesforce
B. Different types of automation tools used in Salesforce
C. Different types of AI that can be applied in Salesforce |
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Definition
| C. Different types of AI that can be applied in Salesforce |
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Question No. 27
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. Data Backup
C. Color Coding |
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Question No. 2
What is a key challenge of human AI collaboration in decision-making?
A. Leads to move informed and balanced decision-making
B. Creates a reliance on AI, potentially leading to less critical thinking and oversight
C. Reduce the need for human involvement in decision-making processes |
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| B. Creates a reliance on AI, potentially leading to less critical thinking and oversight |
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Question No. 29
How does a data quality assessment impact business outcomes for companies using AI?
A. Improves the speed of AI recommendations
B. Accelerates the delivery of new AI solutions
C. Provides a benchmark for AI predictions |
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| C. Provides a benchmark for AI predictions |
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Question No. 30
Which data does Salesforce automatically exclude from marketing Cloud Einstein engagement model training to mitigate bias and ethic...
A. Geographic
B. Demographic
C. Cryptographic |
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Question No. 31
The Cloud technical team is assessing the effectiveness of their AI development processes.
Which established Salesforce Ethical Maturity Model should the team use to guide the development of trusted AI solution?
A. Ethical AI Prediction Maturity Model
B. Ethical AI Process Maturity Model
C. Ethical AI practice Maturity Model |
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Definition
| B. Ethical AI Process Maturity Model |
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Question No. 32
What is the potential outcome of using poor-quality data in AI applications?
A. AI model training becomes slower and less efficient
B. AI models may produce biased or erroneous results.
C. AI models become more interpretable |
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Definition
| B. AI models may produce biased or erroneous results. |
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Question No. 33
What is the role of data quality in achieving AI Business Objectives?
A. Data quality is unnecessary because AI can work with all data types.
B. Data quality is required to create accurate AI data insights.
C. Data quality is important for maintaining Ai data storage limits |
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| B. Data quality is required to create accurate AI data insights. |
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Question No. 34
Which type of bias imposes a system's values on others?
A. Societal
B. Automation
C. Association |
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Question No. 35
Which best describes the difference between predictive AI and generative AI?
A. Predictive new and original output for a given input.
B. Predictive AI and generative have the same capabilities but differ in the type of input they receive: predictive AI receives raw data whereas generation AI receives natural language.
C. 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 |
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| A. Predictive new and original output for a given input. |
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Question No. 36
What are the key components of the data quality standard?
A.Naming, formatting, Monitoring
B.Accuracy, Completeness, Consistency
C.Reviewing, Updating, Archiving |
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| B.Accuracy, Completeness, Consistency |
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Question No. 37
Cloud Kicks wants to decrease the workload for its customer care agents by implementing a chatbot on its website that partially deflects incoming cases by answering frequently asked questions
Which field of AI is most suitable for this scenario?
A. Natural language processing
B. Computer vision
C. Predictive analytics |
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| A. Natural language processing |
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Question No. 38
A financial institution plans a campaign for preapproved credit cards.
How should they implement Salesforce's Trusted AI Principle of Transparency?
A. Communicate how risk factors such as credit score can impact customer eligibility.
B. Flag sensitive variables and their proxies to prevent discriminatory lending practices.
C. Incorporate customer feedback into the model's continuous training. |
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Definition
| B. Flag sensitive variables and their proxies to prevent discriminatory lending practices. |
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Question No. 39
A consultant conducts a series of Consequence Scanning workshops to support testing diverse datasets.
Which Salesforce Trusted AI Principles is being practiced>
A.Transparency
B.Inclusivity
C.Accountability |
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Question No. 40
What is an example of ethical debt?
A. Violating a data privacy law and failing 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 |
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Definition
| B. Launching an AI feature after discovering a harmful bias |
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Question No. 41
What can bias in AI algorithms in CRM lead to?
A. Personalization and target marketing changes
B. Advertising cost increases
C. Ethical challenges in CRM systems |
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Definition
| C. Ethical challenges in CRM systems |
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Question No. 42
What role does data quality play in the ethical us of AI applications?
A. High-quality data is essential for ensuring unbased and for fair AI decisions, promoting ethical use, and preventing discrimi...
B. igh-quality data ensures the process of demographic attributes requires for personalized campaigns.
C. Low-quality data reduces the risk of unintended bias as the data is not overfitted to demographic groups. |
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| A. High-quality data is essential for ensuring unbased and for fair AI decisions, promoting ethical use, and preventing discrimi... |
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Question No. 43
What is the role of Salesforce Trust AI principles in the context of CRM system?
A. Guiding ethical and responsible use of AI
B. Providing a framework for AI data model accuracy
C. Outlining the technical specifications for AI integration |
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Definition
| A. Guiding ethical and responsible use of AI |
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Question No. 43
What is the role of Salesforce Trust AI principles in the context of CRM system?
A. Guiding ethical and responsible use of AI
B. Providing a framework for AI data model accuracy
C. Outlining the technical specifications for AI integration |
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Definition
| A. Guiding ethical and responsible use of AI |
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Question No. 44
What is the most likely impact that high-quality data will have on customer relationships?
A. Increased brand loyalty
B. Higher customer acquisition costs
C. Improved customer trust and satisfaction |
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Definition
| C. Improved customer trust and satisfaction |
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Question No. 45
How does AI which CRM help sales representatives better understand previous customer interactions?
A. Creates, localizes, and translates product descriptions
B. Triggers personalized service replies
C. Provides call summaries |
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Definition
| C. Provides call summaries |
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Question No. 46
A sales manager wants to improve their processes using AI in Salesforce.
Which application of AI would be most beneficial?
A. Lead scoring and opportunity forecasting
B. Sales dashboards and reporting
C. Data modeling and management |
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Definition
| A. Lead scoring and opportunity forecasting |
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Question No. 47
Cloud Kicks wants to use an AI mode to predict the demand for shoes using historical data on sales and regional characteristics.
What is an essential data quality dimension to achieve this goal?
A. Reliability
B. Volume
C. Age |
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Question No. 48
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. Accuracy
B. Consistency
C. Completeness |
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Question No. 49
A data quality expert at Cloud Kicks wants to ensure that each new contact contains at least an email address ...
Which feature should they use to accomplish this?
A. Autofill
B. matching rule
C. Validation rule |
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Question No. 50
Cloud Kicks uses Einstein to generate predictions out is not seeing accurate results?
What to a potential mason for this?
A. Poor data quality
B. The wrong product
C. Too much data |
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Question No. 51
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 |
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| C. Lead scoring, opportunity forecasting, and case classification |
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