Question # 1
| 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 |
C. Lead scoring, opportunity forecasting, and case classification
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.”
Question # 2
To avoid introducing unintended bias to an AI model, which type of data should be omitted?
| | A. Transactional | | B. Engagement | | C. Demographic |
C. Demographic
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.”
Question # 3
| How does data quality impact the trustworthiness of Al-driven decisions? | | A. The use of both low-quality and high-quality data can improve the accuracy and reliability of AI-driven decisions. | | B. High-quality data improves the reliability and credibility of Al-driven decisions, fostering trust among users. | | C. Low-quality data reduces the risk of overfitting the model, improving the trustworthiness of the predictions. |
B. High-quality data improves the reliability and credibility of Al-driven decisions, fostering trust among users.
Explanation: “High-quality data improves 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 AI systems.”
Question # 4
| 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. |
C. Identify business objectives.
Explanation: The first step Cloud Kicks should take for data quality assessment is to identify business objectives. This is crucial because understanding how the company uses customer data to support its business objectives will guide the assessment process1. By identifying the business objectives, Cloud Kicks can determine what customer data is required to support those objectives and how that data is being used. This foundational step is essential before moving on to other aspects of data quality assessment, such as running reports or planning territories. It aligns the data quality initiatives with the company’s goals and ensures that the assessment is focused on areas that will drive business value.
Question # 5
Cloud Kicks wants to ensure that multiple records for the same customer are removed in Salesforce. Which feature should be used to accomplish this?
| | A. Duplicate management | | B. Trigger deletion of old records | | C. Standardized field names |
A. Duplicate management
Explanation: “Duplicate management should be used to remove multiple records for the same customer in Salesforce. Duplicate management is a feature that helps prevent and manage duplicate records in Salesforce. Duplicate management can help define matching rules, duplicate rules, and alert messages to detect and merge duplicate records.”
Question # 6
| Cloud Kicks discovered multiple variations of state and country values in contact records.
Which data quality dimension is affected by this issue? | | A. Usage | | B. Accuracy | | C. Consistency |
C. Consistency
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.”
Question # 7
| 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. Build reports to expire the data quality. | | C. Leverage data quality apps from AppExchange |
C. Leverage data quality apps from AppExchange
Explanation: Data quality apps from the AppExchange can help Cloud Kicks assess and improve their data quality, which is essential for accurate predictions using Einstein Prediction Builder.
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