[Jan 15, 2024] Download Free Pegasystems PEGACPDS88V1 Real Exam Questions
Pass Your Exam With 100% Verified PEGACPDS88V1 Exam Questions
Pegasystems PEGACPDS88V1 is a certification exam that is designed for individuals who want to become a certified Pega data scientist. It is an advanced-level exam that tests the candidate's knowledge and skills in Pega's data science and machine learning capabilities. PEGACPDS88V1 exam is designed to validate the candidate's ability to use Pega's tools and technologies to solve complex business problems.
Pegasystems PEGACPDS88V1 certification exam is designed for professionals who want to prove their expertise in Pega technology and data science. Certified Pega Data Scientist 88V1 certification exam measures the capability of candidates to design and develop predictive models, data preparation, and data analysis. It is an ideal certification for data scientists, data analysts, and business analysts who want to improve their skills in Pega technology and data science.
Pegasystems is a leading provider of customer engagement and business process automation software solutions. The company has developed a range of products designed to help businesses optimize their operations and improve customer satisfaction. One of these products is the Pega Platform, which offers a range of tools for building and deploying applications. To ensure that users of the platform are able to make the most of its features, Pegasystems offers a range of certification exams, including the PEGACPDS88V1 (Certified Pega Data Scientist 88V1) Certification Exam.
NEW QUESTION # 59
In a predictive model rule, the predictors must be mapped to
- A. Action properties
- B. Model properties
- C. Strategy properties
- D. Customer properties
Answer: D
Explanation:
Explanation
Customer properties are used to map predictors to customer data that is available in the system. They can be either scalar or aggregate properties. References:
https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/mapping-predic
NEW QUESTION # 60
Which statement about predictive models is true?
- A. You need past experience to create a predictive model.
- B. They are always associated with a proposition.
- C. They need to be specified in a data attribute.
- D. They need unstructured big data.
Answer: A
NEW QUESTION # 61
U+ Telecom wants to engage in proactive retention to reduce churn. As a data scientist, you create a prediction that calculates the probability that a client is likely to cancel a subscription. What type of prediction do you create?
- A. Text analytics
- B. Customer Decision Hub
- C. Case management_____
Answer: B
Explanation:
Explanation
As a data scientist, you create a prediction that calculates the probability that a client is likely to cancel a subscription. The type of prediction you create is Customer Decision Hub.
NEW QUESTION # 62
Which property is automatically recomputed for each decision component?
- A. Property
- B. Order
- C. Rank
- D. Priority
Answer: C
Explanation:
Explanation
The rank property is automatically recomputed for each decision component. It indicates the order in which the actions are presented to the customer, based on their priority and propensity. References:
https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/ranking-actions
NEW QUESTION # 63
When developing a predictive model, the outcome value of a continuous model type can represent__________________
- A. customer churn
- B. the purchase value of an offer
- C. acceptance of an offer
- D. customer loan default
Answer: B
Explanation:
Explanation
When developing a predictive model, the outcome value of a continuous model type can represent the purchase value of an offer.
NEW QUESTION # 64
What is the difference between predictive and adaptive analytics?
- A. Predictive models predict customer behavior.
- B. Adaptive models use the customer data as predict*
- C. Predictive models have evidence.
- D. Predictive models can predict a continuous value.
Answer: B
Explanation:
Explanation
The difference between predictive and adaptive analytics is that adaptive models use the customer data as predictors, while predictive models use the customer data as outcomes. Adaptive models learn from real-time customer interactions and update their predictions accordingly. Predictive models use historical customer data to train and validate their predictions. References:
https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data-archived/topic/adaptive-m
NEW QUESTION # 65
The decision components used on the strategy canvas are interconnected by arrows. What does a solid arrow from a "Set Property" component to a "Filter" component mean?
- A. A property from the "Set Property" component is referenced by the "Filter" component.
- B. Information from the "Set Property" component is copied over to the "Filter" component.
- C. There is a one-to-one relationship between a "Set Property" and a "Filter" component.
- D. To evaluate the "Set Property" component, the "Filter" component is evaluated first.
Answer: A
Explanation:
Explanation
A solid arrow from a "Set Property" component to a "Filter" component means that a property from the "Set Property" component is referenced by the "Filter" component. For example, you can use a "Set Property" component to calculate a customer's age and then use a "Filter" component to remove actions that are not suitable for that age group. References:
https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/setting-properti
NEW QUESTION # 66
MyCo, a telecommunications company, wants to implement one-to-one customer engagement using Pega Customer Decision Hub. Which three of the following real-time channels can the company use to present Next-Best-Actions? (Choose Three)
- A. Retail store
- B. Call center
- C. SMS
- D. Billboard on the company building
- E. Traditional television advertisements
Answer: A,B,C
Explanation:
Explanation
Call center, SMS, and Retail store Reference:
MyCo can use Call center, SMS, and Retail store as real-time channels to present Next-Best-Actions.
NEW QUESTION # 67
The filter component is used to filter_______
- A. Customers
- B. Actions
- C. attributes
- D. Adaptive models
Answer: B
Explanation:
Explanation
The filter component is used to filter actions based on various criteria, such as eligibility, suitability, priority, or custom conditions. References:
https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/filtering-action
NEW QUESTION # 68
Proactive retention is applicable when a customer is
- A. A high value customer
- B. In a collections process
- C. Initiating contact to churn
- D. Likely to churn
Answer: D
Explanation:
Explanation
Proactive retention is applicable when a customer is likely to churn. Proactive retention is a strategy that aims to prevent customer attrition by identifying customers who are at risk of leaving and offering them incentives or solutions to retain them. Proactive retention requires predicting the customer's churn risk and selecting the next best action accordingly. References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#decisioning-/decisioning-strategi
NEW QUESTION # 69
An online store is interested in increasing its revenues from cross-selling and wants to predict the acceptance rate of the offers presented on their website. A customer's propensity to accept an offer increases when_________.
- A. The offer was rejected by similar customers
- B. Similar offers were rejected by the customer
- C. The offer was accepted by similar customers
- D. Similar offers were accepted by the customer
Answer: D
Explanation:
Explanation
This is because a customer's propensity to accept an offer depends on their past behavior and preferences. If a customer has accepted similar offers in the past, they are more likely to accept a new offer that matches their interests
https://academy.pega.com/sites/default/files/media/documents/2020-12/Mission20301-2-EN-StudentGuide.pdf
NEW QUESTION # 70
Which value is output by an Adaptive Model?
- A. Score
- B. Behavior
- C. Lift
- D. Performance
Answer: B
Explanation:
Explanation
The value that is output by an adaptive model is behavior, which indicates the likelihood that the customer will accept or respond to an offer. Behavior is also known as propensity or probability in decision strategies.
References:
https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data-archived/topic/using-adap
NEW QUESTION # 71
What is the key component of a Next-Best-Action strategy?
- A. Predictive model
- B. Work flow
- C. Decision table
- D. Strategy
Answer: D
Explanation:
Explanation
The key component of a Next-Best-Action strategy is a strategy, which is a graphical representation of the business logic that determines which actions to offer to each customer and in what order. A strategy can use various components, such as business rules, predictive models, filters, prioritizers, etc., to achieve this goal.
References: https://academy.pega.com/module/one-one-customer-engagement/topic/next-best-action-designer
NEW QUESTION # 72
Customer Decision Hub uses the P*C*V*L arbitration formula to select the next best action for each customer. Which factor in the arbitration formula is calculated by using AI?
- A. Propensity
- B. Context weighing
- C. Business levers
- D. Action value
Answer: A
Explanation:
Explanation
In Customer Decision Hub, the factor in the arbitration formula that is calculated by using AI is Propensity.
NEW QUESTION # 73
The mapping of the input fields of a third-party predictive model is done in the
- A. Predictive Analytics Director portal
- B. Predictive Model decision component
- C. Customer class definition
- D. Predictive Model rule
Answer: D
Explanation:
Explanation
The mapping of the input fields of a third-party predictive model is done in the Predictive Model rule. The Predictive Model rule defines how to invoke and interpret the results of a third-party predictive model that is imported in PMML format. References:
https://academy.pega.com/module/predictive-analytics/topic/using-pmml-models
NEW QUESTION # 74
Which decision component allows you to monitor the real-time performance of a third- party Churn Model?
- A. PMML Model
- B. Predictive Model
- C. Scorecard Model
- D. Adaptive Model
Answer: C
Explanation:
Explanation
A scorecard model is a type of predictive model that allows you to monitor the real-time performance of a third-party churn model. A scorecard model compares the predicted churn probability with the actual churn outcome and calculates a performance score for each customer segment. References:
https://academy.pega.com/module/predictive-analytics/topic/using-scorecard-models
NEW QUESTION # 75
The management team at U+ Insurance wants to improve the experience of dissatisfied customers. The customers send the feedback through email.
To detect the sentiment of the incoming emails, which type of prediction do you need to configure in Prediction Studio?
- A. Case management prediction.
- B. Pega Customer Decision Hub prediction.
- C. Sentiment detection does not require any predictions.
- D. Text analytics prediction.
Answer: D
Explanation:
Explanation
To detect the sentiment of the incoming emails, you need to configure a text analytics prediction1234 in Prediction Studio. A text analytics prediction is a type of prediction that uses natural language processing (NLP) to analyze text data and extract insights, such as topics, entities, and sentiments. You can use a text analytics prediction to detect the sentiment of an email based on its content and assign a score ranging from -1 (negative) to 1 (positive). This can help you improve the customer experience by identifying dissatisfied customers and taking appropriate actions.
NEW QUESTION # 76
To enable an assessment of its reliability, the Adaptive Model produces three outputs: Propensity, Performance and Evidence. The performance of an Adaptive Model that has not collected any evidence is_________.
- A. 0.0
- B. null
- C. 0.5
- D. 1-0
Answer: C
Explanation:
Explanation
When an adaptive model has not collected any evidence, its performance is 0.5, which means that it has no predictive power and is equivalent to a random guess. As more evidence is collected, the performance can increase or decrease depending on how well the model predicts customer behavior. References:
https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data-archived/topic/adaptive-m
NEW QUESTION # 77
......
PEGACPDS88V1 Dumps 100 Pass Guarantee With Latest Demo: https://www.itexamsimulator.com/PEGACPDS88V1-brain-dumps.html
PEGACPDS88V1 Dumps PDF - PEGACPDS88V1 Real Exam Questions Answers: https://drive.google.com/open?id=1gP_UQalkl7PzGbsGsl6dMgmMQ5lW8T4n
