What is a benefit of a diverse, balanced, and large dataset?
C
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.”
What are the three commonly used examples of AI in CRM?
B
Explanation:
“Predictive scoring, forecasting, and recommendations are three commonly used examples of AI in
CRM. Predictive scoring can help prioritize leads, opportunities, and customers based on their
likelihood to convert, churn, or buy. Forecasting can help predict future sales, revenue, or demand
based on historical data and trends. Recommendations can help suggest the best products, services,
or actions for each customer based on their preferences, behavior, and needs.”
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?
B
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.
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
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.”
What are some of the ethical challenges associated with AI development?
A
Explanation:
“Some of the ethical challenges associated with AI development are the potential for human bias in
machine learning algorithms and the lack of transparency in AI decision-making processes. Human
bias can arise from the data used to train the models, the design choices made by the developers, or
the interpretation of the results by the users. Lack of transparency can make it difficult to understand
how and why AI systems make certain decisions, which can affect trust, accountability, and fairness.”
Cloud Kicks discovered multiple variations of state and country values in contact records.
Which data quality dimension is affected by this issue?
C
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.”
How is natural language processing (NLP) used in the context of AI capabilities?
C
Explanation:
“Natural language processing (NLP) is used in the context of AI capabilities to understand and
generate human language. NLP can enable AI systems to interact with humans using natural
language, such as speech or text. NLP can also enable AI systems to analyze and extract information
from natural language data, such as documents, emails, or social media posts.”
What is an example of Salesforce's Trusted AI Principle of Inclusivity in practice?
A
Explanation:
“An example of Salesforce’s Trusted AI Principle of Inclusivity in practice is testing models with
diverse datasets. Inclusivity means that AI systems should be designed and developed with respect
for diversity and inclusion of different perspectives, backgrounds, and experiences. Testing models
with diverse datasets can help ensure that the models are fair, unbiased, and representative of the
target population or domain.”
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
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.”
What should organizations do to ensure data quality for their AI initiatives?
A
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.”
Which Einstein capability uses emails to create content for Knowledge articles?
A
Explanation:
“Einstein Generate uses emails to create content for Knowledge articles. Einstein Generate is a
natural language generation (NLG) feature that can automatically write summaries, descriptions, or
recommendations based on data or text inputs. For example, Einstein Generate can analyze email
conversations between agents and customers and generate draft articles for the Knowledge base.”
Which type of bias results from data being labeled according to stereotypes?
B
Explanation:
“Societal bias results from data being labeled according to stereotypes. Societal bias is a type of bias
that reflects the assumptions, norms, or values of a specific society or culture. For example, societal
bias can occur when data is labeled based on gender, race, ethnicity, or religion stereotypes.”
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
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.”
Cloud Kicks relies on data analysis to optimize its product recommendation; however, CK encounters
a recurring Issue of Incomplete customer records, with missing contact Information and incomplete
purchase histories.
How will this incomplete data quality impact the company's operations?
A
Explanation:
“The incomplete data quality will impact the company’s operations by hindering the accuracy of
product recommendations. Incomplete data means that the data is missing some values or attributes
that are relevant for the AI task. Incomplete data can affect the performance and reliability of AI
models, as they may not have enough information to learn from or make accurate predictions. For
example, incomplete customer records can affect the quality of product recommendations, as the AI
model may not be able to capture the customers’ preferences, behavior, or needs.”
What are some key benefits of AI in improving customer experiences in CRM?
C
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.”