[Oct-2023] PEGACPDS88V1 Dumps PDF - PEGACPDS88V1 Real Exam Questions Answers
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The Pegasystems PEGACPDS88V1 exam consists of 60 multiple-choice questions, and candidates have 90 minutes to complete the exam. To pass the exam, candidates must score at least 65%. PEGACPDS88V1 exam is available in English, Japanese, and Spanish. PEGACPDS88V1 exam fee is $150, and candidates can take the exam at a Pearson VUE testing center or online.
NEW QUESTION # 22
Pega Customer Decision Hub uses the P*C*V*L arbitration formula to select the next best action for each customer. Which description best describes the purpose of the formula?
- A. To balance customer needs with business objectives
- B. To ensure that every customer receives the same action
- C. To provide insight into business processes
- D. To ensure that the customer is always given the best offer, regardless of the business objective
Answer: A
Explanation:
Explanation
Pega Customer Decision Hub uses the PCV*L arbitration formula to select the next best action for each customer. The purpose of the formula is to balance customer needs with business objectives.
NEW QUESTION # 23
As a data scientist, you are asked to create a prediction to optimize the click-through rate of a web banner.
What type of prediction do you need to create in Prediction studio?
- A. Case management
- B. Text analysis
- C. Adaptive prediction
- D. Customer Decision Hub
Answer: D
Explanation:
Explanation
Customer Decision Hub Reference:
To optimize the click-through rate of a web banner, you need to create a Customer Decision Hub prediction.
NEW QUESTION # 24
U+ Insurance uses Pega Process AI to assess the complexity of the claims and route a claim to the best-suited user. In the case type that handles claims, the application developer wants to use AI to route claims that are likely to miss their deadline to an expert. As a data scientist, what task do you first perform to allow the application developer to reference the AI output in the case type?
- A. Create a predictive model.
- B. Add a decision step to the case type.
- C. Create a prediction.
- D. Configure an adaptive model to drive the prediction.
Answer: C
Explanation:
Explanation
to use AI to route claims that are likely to miss their deadline to an expert, you need to create a prediction. A prediction is a decision management component that you can reference in a case type. A prediction uses a predictive model or an adaptive model to calculate a probability or a score for a specific outcome.
https://academy.pega.com/topic/process-ai-predictions/v1
NEW QUESTION # 25
When building a predictive model, at what stage do you compare the performance of predictive models?
- A. Model Development stage
- B. Model Export stage
- C. Model Comparison stage
- D. Model Analysis stage
Answer: C
Explanation:
Explanation
When building a predictive model, you compare the performance of predictive models at the Model Comparison stage. This stage allows you to select the best model based on various metrics, such as accuracy, lift, or area under curve (AUC). References:
https://academy.pega.com/module/predictive-analytics/topic/comparing-predictive-models
NEW QUESTION # 26
Model transparency is becoming an important requirement for many businesses. In Prediction Studio, model transparency thresholds can be set for
- A. a department
- B. a model
- C. a business issue
- D. a model type
Answer: B
Explanation:
Explanation
In Prediction Studio, model transparency thresholds can be set for a model.
NEW QUESTION # 27
The likelihood that an action will be accepted by the customer is stored in the Strategy property called_______
- A. pyLikelihood
- B. pyPropensity
- C. pyProbability
- D. pyBehavior
Answer: B
Explanation:
Explanation
The pyPropensity property stores the likelihood that an action will be accepted by the customer. It is calculated by a predictive model or an adaptive model and used in decision strategies to prioritize actions. References:
https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/using-predictio
NEW QUESTION # 28
To build a predictive model, use____________.
- A. Pega Decision Management
- B. Pega Platform
- C. Pega Marketing
- D. Pega Customer Service
Answer: A
Explanation:
Explanation
Pega Decision Management Reference:
To build a predictive model, use Pega Decision Management. Pega Decision Management is a tool that enables businesses to make informed decisions based on data and analytics.
NEW QUESTION # 29
To predict if a customer is likely to churn you use a model of type
- A. decision tree
- B. champion challenger
- C. decision table
- D. switch
Answer: A
Explanation:
Explanation
To predict if a customer is likely to churn, you use a model of type decision tree. A decision tree is a type of predictive model that uses a set of rules to classify customers into different categories based on their attributes and behavior. A decision tree can predict a binary outcome (such as churn or not churn) or a multi-class outcome (such as low risk, medium risk, or high risk). References:
https://academy.pega.com/module/predictive-analytics/topic/using-decision-tree-models
NEW QUESTION # 30
U+ Insurance uses Pega Process AI and wants straight-through processing of claims with a low fraud risk.
As a data scientist, you create a prediction that calculates the probability that a claim is fraudulent.
What type of prediction do you create to meet this requirement?
- A. A fraud detection prediction
- B. A case management prediction.
- C. A text analytics prediction.
- D. A Customer Decision Hub prediction.
Answer: B
Explanation:
Explanation
to create a prediction that calculates the probability that a claim is fraudulent, you need to create a case management prediction. This type of prediction allows you to use predictive models built on external platforms such as H2O.ai and apply them to case types in Pega Process AI. You can then use the prediction outcome in a decision step to route claims based on their fraud risk.
https://academy.pega.com/challenge/creating-fraud-prediction/v3
NEW QUESTION # 31
The decision components use on the strategy canvas can be individually configured.
Which function is available when configuring the Group By component?
- A. True if Some
- B. Multiply
- C. Divide
- D. Count
Answer: D
Explanation:
Explanation
According to the Pega Academy1, decision strategies drive the next best action and comprise a unit of reasoning represented by decision components. You use the Proposition Data component to import actions into a strategy canvas. The sequence of the components in the canvas determines which action is selected for a customer.
The Group By component2 is used to group a list of ranked items based on a field and retain only one element in each group. The function available when configuring the Group By component is Count2, which returns the number of elements in each group.
NEW QUESTION # 32
Predictions combine predictive analytics and best practices in data science. As a data scientist, what is a valid reason to adjust the default response timeout in a prediction?
- A. Optimize the success rate
- B. Suit the use case
- C. Increase lift
- D. Limit the number of responses
Answer: B
Explanation:
Explanation
As a data scientist, a valid reason to adjust the default response timeout in a prediction is to suit the use case.
NEW QUESTION # 33
When building a predictive model, what is a valid predictor data type?
- A. Character
- B. Symbolic
- C. Boolean
- D. String
Answer: C
Explanation:
Explanation
When building a predictive model, a valid predictor data type is Boolean, which can have only two values:
true or false. Other valid predictor data types are numeric, date, and symbolic (categorical). References:
https://academy.pega.com/module/predictive-analytics/topic/predictor-data-types
NEW QUESTION # 34
In a decision strategy, the Adaptive Model decision component belongs the
- A. Arbitration category
- B. Business Rules category
- C. Decision Analytics category
- D. Predictive Model category
Answer: C
Explanation:
Explanation
In a decision strategy, the Adaptive Model decision component belongs to the Decision Analytics category.
This category contains components that use advanced analytics techniques, such as adaptive models, predictive models, text analytics models, etc., to make predictions or recommendations. References:
https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/decision-analyt
NEW QUESTION # 35
Acquiring new customers can be more costly than retaining active customers. U+ Bank uses Pega Customer Decision Hub for its customer engagement and wants to reduce the churn rate by identifying high churn risk customers and making them a retention offer.
To meet this requirement, which two artifacts created by a data scientist allow the NBA specialist to implement the decision strategy? (Choose Two)
- A. A prediction
- B. A predictive model
- C. An adaptive model
- D. A control group
Answer: B,D
Explanation:
Explanation
According to the Data Scientist Student Guide1, page 18, the correct answer is B. A predictive model and C. A control group. A predictive model is a mathematical representation of a real-world process that can be used to predict an outcome based on input data. A control group is a subset of customers who are not exposed to a treatment (such as an offer) and are used to measure the effectiveness of the treatment by comparing their behavior with the treated group.
NEW QUESTION # 36
U+ Bank introduces a new credit card that has no historical customer behavior data. U+ Bank wants to offer this credit card on the personalized web portal. Given the scenario, which rule type must you use?
- A. Adaptive model
- B. When rule
- C. Decision table
- D. Pega machine learning model
Answer: A
Explanation:
Explanation
Given the scenario where U+ Bank introduces a new credit card that has no historical customer behavior data and wants to offer this credit card on the personalized web portal, you must use an adaptive model.
NEW QUESTION # 37
The standardized model operations process (MLOps) lets you replace a low-performing predictive model that drives a prediction with a new one.
Which feature of MLOps lets you monitor the new model in the production environment without affecting the business outcomes?
- A. Change request
- B. Shadow mode
- C. Historical data capture
- D. Connection to machine learning services
Answer: B
Explanation:
Explanation
This is because shadow mode allows you to test a new model in parallel with an existing model without affecting the decision outcomes. You can compare the performance of both models and decide whether to replace or keep the existing model.
https://academy.pega.com/sites/default/files/media/documents/2020-12/Mission20301-2-EN-StudentGuide.pdf
NEW QUESTION # 38
A company wants to simulate decisions that requires large amounts of data. However, the organisation's live data is inaccessible. Your advice is to use a Monte Carlo data set. The Monte Carlo method
- A. enables the company to generate random data for most of its application needs
- B. makes the organization's live data accessible
- C. combines external data sets into a larger data set
- D. generates data that the company can use as input for adaptive decisioning
Answer: D
Explanation:
Explanation
The Monte Carlo method enables the company to generate data that simulates customer behavior and can be used as input for adaptive decisioning. The generated data is based on predefined probabilities and distributions that reflect realistic scenarios. References:
https://academy.pega.com/module/demonstrating-adaptive-learning-archived/topic/creating-monte-carlo-data-set
NEW QUESTION # 39
Which statement about Pega AI is correct?
- A. Pega AI is primarily based on self-learning models
- B. Pega AI is primarily based on models newly build in Prediction Studio
- C. Pega AI is restricted to self-learning models
- D. Pega AI is restricted to models newly build in Prediction Studio
Answer: A
Explanation:
Explanation
Pega AI is primarily based on self-learning models Reference:
Pega AI is primarily based on self-learning models
NEW QUESTION # 40
Through analysis of customer lifecycles, Next-Best-Action
- A. provides fulfillment services
- B. anticipates retention issues
- C. provides future sales reports
- D. identifies global sales targets
Answer: B
Explanation:
Explanation
Through analysis of customer lifecycles, Next-Best-Action anticipates retention issues and takes proactive actions to prevent customer churn. It uses predictive analytics to identify customers who are at risk of leaving and offers them incentives or solutions to retain them. References:
https://academy.pega.com/module/one-one-customer-engagement/topic/proactive-retention
NEW QUESTION # 41
How does a prediction help in proactive retention?
- A. The prediction identifies successful offers in past interactions
- B. The prediction suggests the best offer
- C. The prediction predicts the customer's churn risk
- D. The prediction selects the next best action
Answer: C
Explanation:
Explanation
A prediction helps in proactive retention by predicting the customer's churn risk. A prediction is an estimate of the likelihood of a future outcome based on historical data and statistical models. A prediction can help identify customers who are at risk of leaving and target them with appropriate actions to retain them.
References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#decisioning-/decisioning-strategi
NEW QUESTION # 42
When selecting the list of predictors for an adaptive model you should
- A. Always use numeric type for integer properties
- B. Select up to a maximum of 500 predictors
- C. Consider properties from a wide range of sources
- D. Select at least one date property
Answer: C
Explanation:
Explanation
When selecting the list of predictors for an adaptive model you should consider properties from a wide range of sources. Predictors are properties that influence the customer behavior and can be derived from various sources such as customer profile, interaction history, proposition details, etc. References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-decision
NEW QUESTION # 43
For an Adaptive Model to react quickly to changes in customer behavior, the
- A. strategy must include the calculation for smooth propensity
- B. model must always evaluate all customer responses
- C. value of the memory setting should be set to a low number
- D. performance threshold should be set to a low number
Answer: D
NEW QUESTION # 44
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The PEGACPDS88V1 exam consists of 65 multiple-choice questions and is timed for 90 minutes. PEGACPDS88V1 exam is computer-based and can be taken at one of the Pega testing centers. PEGACPDS88V1 exam is available in multiple languages, including English, Japanese, and Chinese.
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