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Most Recent Pegasystems PEGACPDS88V1 Exam Dumps
Prepare for the Pegasystems Certified Pega Data Scientist 8.8 exam with our extensive collection of questions and answers. These practice Q&A are updated according to the latest syllabus, providing you with the tools needed to review and test your knowledge.
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The questions for PEGACPDS88V1 were last updated on Feb 21, 2025.
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The standardized model operations process (MLOps) lets you replace a low-performing predictive model that drives a prediction with a superior one.
When you place the new model in shadow mode in the production environment, the current model___________
When you place the new model in shadow mode in the production environment, the current model still drives the prediction, but the new model runs in parallel and collects performance data for comparison. Reference: https://academy.pega.com/module/predictive-analytics/topic/mlops
How does a prediction help in proactive retention?
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. Reference: https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#decisioning-/decisioning-strategies-/decisioning-strategies-proactive-retention/main.htm
Which two factors do you inspect to access the general health of the adaptive models in Prediction Studio? (Choose Two)
These factors indicate how accurate and explainable the models are, which are key measures of model health. The number of responses and decisions are related more to model usage rather than health.
The P*C*V*L arbitration formula is used by the Customer Decision Hub to select the Next-Best-Action for each customer. Which factor in the arbitration formula is calculated using AI?
Propensity Reference:
The PCV*L arbitration formula used by the Customer Decision Hub to select the Next-Best-Action for each customer calculatespropensityusing AI.
A telecom company is interested in improving customer engagement on social medi
a. However, there are hundreds of relevant messages posted every day, and it is not practical for customer service representatives (CSRs) to review and respond to all messages. Instead, CSRs should focus on negative messages. What do you need to analyze the incoming messages?
A text categorization model is a type of text analytics model that can analyze the incoming messages and assign them to predefined categories, such as positive, negative, or neutral sentiment. This way, CSRs can focus on negative messages that require immediate attention or escalation. Reference: https://academy.pega.com/module/text-analytics/topic/creating-text-categorization-model
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