PEGACPDS88V1 Exam Questions and Answers

QUESTION: 16

Proactive retention is applicable when a customer is

Initiating contact to churn
A high value customer
In a collections process
Likely to churn

Answer(s): D

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.

Reference:

https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#decisioning- /decisioning-strategies-/decisioning-strategies-proactive-retention/main.htm

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QUESTION: 17

Pega machine learning supports the creation of which two distinct types of predictive models? (Choose Two)

Categorical
Continuous
Binary
Numerical

Answer(s): A,C

Explanation:

Pega machine learning supports the creation of two distinct types of predictive models: categorical and binary. Categorical models predict the outcome of a variable that can have multiple values, such as product category or customer segment. Binary models predict the outcome of a variable that can have only two values, such as yes or no, accept or reject, etc.

Reference:

https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule- decision-/rule-decision-predictivemodel/main.htm

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QUESTION: 18

Which decision component enables you to use a PMML model?

Predictive Model
PMML Model
Third-party Model
Adaptive Model

Answer(s): A

Explanation:

The decision component that enables you to use a PMML model is Predictive Model. Predictive Model is a component that references a predictive model rule that defines the input parameters and the output score of the model. You can use a predictive model component to reference a PMML model that is imported from a third-party tool and use it in your decision strategy.

Reference:

https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule- decision-/rule-decision-predictivemodel/main.htm

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QUESTION: 19

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?

Change request
Shadow mode
Historical data capture
Connection to machine learning services

Answer(s): B

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

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QUESTION: 20

A large online store uses Pega Customer Decision Hub to smoothly adapt to changing customer behavior. Adaptive models help accomplish this business objective as the models learn from customer responses.
Which statement about adaptive models is correct? s

Adaptive models perform a binary model calculation
Adaptive models require underlying predictive models
Adaptive models require a historical data set to start learning
Adaptive models perform a continuous model calculation

Answer(s): A

Explanation:

Adaptive models perform a binary model calculation. This means that adaptive models predict the likelihood of a positive or negative response for each action and customer profile. Adaptive models do not require underlying predictive models or historical data sets to start learning. They learn from customer responses in real time and continuously update their predictions.

Reference:

https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule- decision-/rule-decision-adaptivemodel/main.htm

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Pegasystems PEGACPDS88V1 Exam (page: 4) Pegasystems Certified Pega Data Scientist 8.8 Updated on: 12-Feb-2026

QUESTION: 16

Explanation:

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QUESTION: 17

Explanation:

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QUESTION: 18

Explanation:

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QUESTION: 19

Explanation:

QUESTION: 20

Explanation:

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Pegasystems PEGACPDS88V1 Exam (page: 4)
Pegasystems Certified Pega Data Scientist 8.8
Updated on: 12-Feb-2026