PEGACPDS88V1 Certified Pega Data Scientist 8.8 Dumps

1. Download the latest PCDS Certification PEGACPDS88V1 dumps for your best preparation Exam : PEGACPDS88V1 Title : Certified Pega Data Scientist 8.8 https://www.passcert.com/PEGACPDS88V1.html 1 / 6

2. Download the latest PCDS Certification PEGACPDS88V1 dumps for your best preparation 1.A Scoring Model allows you to differentiate between A. Accept, Reject, Maybe Later B. Good, Bad C. Good, Better, Best D. Good, Bad, Unknown Answer: C Explanation: A scoring model allows you to differentiate between Good, Better, and Best outcomes for a given proposition or action. A scoring model assigns a numerical value to each outcome based on its desirability or profitability for the business. References: https://academy.pega.com/module/predictive-analytics/topic/using-scoring-models 2.As a data scientist, you have enabled capturing of historical data in an adaptive model. Which two data elements are captured for every customer interaction? (Choose Two) A. The value of only the active predictors B. The outcome of the interaction C. The model metadata D. The propensity generated by the model E. The value of all predictors Answer: B,E Explanation: When capturing historical data in an adaptive model, the outcome of the interaction and the value of all predictors are captured for every customer interaction. 3.What is the difference between predictive and adaptive analytics? A. Predictive models can predict a continuous value. B. Predictive models predict customer behavior. C. Adaptive models use the customer data as predict* D. Predictive models have evidence. Answer: C 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/ada ptive-models-overview 4.The outcome of a scoring model indicates the likely A. write-off value of an arrears case B. claim value of a health insurance C. period in which a spare part has to be replaced D. response to an offer 2 / 6

3. Download the latest PCDS Certification PEGACPDS88V1 dumps for your best preparation Answer: D Explanation: The outcome of a scoring model indicates the likely response to an offer that is presented to a customer. For example, a scoring model can predict if a customer will accept, reject, or defer an offer for a credit card upgrade. References: https://academy.pega.com/module/predictive-analytics/topic/using-scoring-models 5.The standardized machine learning process (MLOps) lets you replace a low-performing predictive model that drives a prediction with an updated model. When you approve the model, a change request is automatically generated in__________ A. the business operations environment B. an external environment C. the production environment Answer: C Explanation: When you approve the updated model in the standardized machine learning process (MLOps), a change request is automatically generated in the production environment. 6.What is the key difference between a predictive model and a human expert? A. Predictive models always outperform human experts. B. Humans are better at dealing with structured data and identifying patterns. C. Predictive models are more capable of detecting patterns in historical data. D. Humans make successful predictions on a large amount of data. Answer: B 7.As a data scientist, you are tasked with configuring two predictions that are driven by an adaptive model: one for an inbound channel and one for an outbound channel. To which setting do you need to pay extra attention? A. Response timeout B. Adaptive model C. Predictor fields D. Control group Answer: B Explanation: As a data scientist, if you are tasked with configuring two predictions that are driven by an adaptive model, you need to pay extra attention to adaptive model settings. 8.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. Case management_____ B. Customer Decision Hub C. Text analytics Answer: B 3 / 6

4. Download the latest PCDS Certification PEGACPDS88V1 dumps for your best preparation 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. 9.Which component(s) do you use to calculate the average margin of four actions? A. one Set Property component B. one Group By component C. four Group By components D. four Set Property components Answer: A Explanation: You can use one Set Property component to calculate the average margin of four actions by using an expression that sums up the margin values of each action and divides by four. You can then use this property in other components, such as Filter or Prioritize. References: https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/setting -properties 10.An adaptive adaptive model component in a decision: propensity, performance, evidence, and positives. What is evidence in the context of an adaptive model? A. The likelihood of a statistically similar behavior B. The number of customers who exhibited statistically similar behavior C. The number of statistical bins that arc generated by the system D. The number of outcomes that system registered Answer: B Explanation: Evidence is the number of customers who exhibited statistically similar behavior. It indicates how much data the model has collected for a given predictor profile. The higher the evidence, the more reliable the model is. References: https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-de cision-adaptivemodel/main.htm 11.You are the Decisioning Consultant on an Al-powered one-to-one Customer Engagement implementation project. You are asked to design the Next-Best-Action prioritization expression that balances the customer needs with the business objectives. What factors do you consider in the prioritization expression? A. product eligibility rules B. customer contact rules C. product compatibility rules D. business levers Answer: D Explanation: 4 / 6

5. Download the latest PCDS Certification PEGACPDS88V1 dumps for your best preparation Business levers are factors that you consider in the prioritization expression to balance the customer needs with the business objectives. They can include revenue, cost, risk, retention, satisfaction, or any other custom metric that reflects the value of an action. References: https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/using- business-levers 12.What type of a predictor can you use in an adaptive model? A. Symbolic B. Integer C. Page Type D. Logical Answer: A Explanation: In an adaptive model, you can use Symbolic predictors. 13.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. Similar offers were rejected by the customer B. The offer was rejected by similar customers C. Similar offers were accepted by the customer D. The offer was accepted by similar customers Answer: C 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-StudentGuid e.pdf 14.When implementing a Next-Best-Action project, which step is recommended to be taken first? A. Define Issue and Group hierarchy B. Define propositions C. Define business rules D. Define prioritization formula Answer: A Explanation: When implementing a Next-Best-Action project, the recommended first step is to define Issue and Group hierarchy, which are used to organize and categorize propositions based on business objectives and customer needs. This step helps to align the project with the business vision and goals. References: https://academy.pega.com/module/one-one-customer-engagement/topic/next-best-action-designer 5 / 6

6. Download the latest PCDS Certification PEGACPDS88V1 dumps for your best preparation 15.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. Configure an adaptive model to drive the prediction. D. Create a prediction. Answer: D 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 16.In a strategy defined in the "Retension" issue and the "X-Sell" group, you can import________ A. Actions from all groups under the "Retention" issue B. Actions from "X-Sell" group C. Actions from the "Sales" issue D. All active actions Answer: A Explanation: According to the Pega Academy1, a strategy is a unit of reasoning that defines how to select an action for a customer. A strategy can be defined in different issues and groups, which are categories that help organize actions. An issue represents a business goal (such as retention or sales), and a group represents a subcategory of an issue (such as cross-sell or up-sell). In a strategy defined in the “Retention” issue and the “X-Sell” group, you can import actions from all groups under the “Retention” issue1. This allows you to use actions that are relevant to your business goal and compare them with other actions in the same issue. 17.U+ Bank promotes credit card offers on its website and uses Pega Customer Decision Hub to personalize the offer for every customer. Now, the bank wants to lower the number of customers that leave the bank by showing a proactive retention offer to high churn risk customers instead. As an NBA analyst, you are tasked with creating a new applicability setting to comply with the new business rule. Which business issue or issues do you modify? A. The Retention issue B. The Sales issue C. The Sales issue and the Retention issue D. No modification is required Answer: A Explanation: To comply with the new business rule of showing a proactive retention offer to high churn risk customers, you should modify the Retention issue. 6 / 6