Pegasystems PEGACPDS88V1 Certified Pega Data Scientist 8.8 Online Training
Pegasystems PEGACPDS88V1 Online Training
The questions for PEGACPDS88V1 were last updated at Nov 19,2024.
- Exam Code: PEGACPDS88V1
- Exam Name: Certified Pega Data Scientist 8.8
- Certification Provider: Pegasystems
- Latest update: Nov 19,2024
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
D
Explanation:
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
What type of a predictor can you use in an adaptive model?
- A . Symbolic
- B . Integer
- C . Page Type
- D . Logical
B
Explanation:
Integer type predictors can be used in an adaptive model, as they represent quantifiable or measurable attributes.
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
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-StudentGuide.pdf
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
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
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.
A
Explanation:
Before a developer can reference the AI output in a case type, a data scientist would first need to create a predictive model. This model will be used to predict which claims are likely to miss their deadline.
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
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.
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
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.
Which statement about predictive models is true?
- A . Predictive models need historical data to be created
- B . Predictive models need to be specified in a data attribute
- C . Predictive models are always associated with an action
- D . Predictive models need unstructured bie data
A
Explanation:
Predictive models need historical data to be created. Predictive models are statistical models that use historical data to learn patterns and trends and make predictions for future outcomes. Predictive models can be built with Pega machine learning or imported from third-party tools such as PMML or H2O.
References: https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-decision-predictivemodel/main.htm
Configuring an adaptive model involves selecting the potential predictors.
How many potential predictors are recommended for an adaptive model?
- A . At least 100 fields to reach an acceptable level of model performance
- B . All fields that have been predictive in the past
- C . All available uncorrected fields
- D . Up to 100 fields to limit the impact on model speed
D
Explanation:
Up to 100 fields to limit the impact on model speed
Reference:
When configuring an adaptive model, it is recommended to select up to 100 potential predictors to limit the impact on model speed.
When you build a decision strategy, what property do you use to access the output of a prediction that is driven by a predictive model markup language (PMML) model?
- A . pxEvidence
- B . pxResult
- C . pxSegment
- D . nxOutcome
B
Explanation:
The pxResult property is used to access the output of a prediction that is driven by a PMML model. It contains the predicted value or class for each record in the input data set.
References: https://academy.pega.com/module/predictive-analytics/topic/using-pmml-models
Latest PEGACPDS88V1 Dumps Valid Version with 140 Q&As
Latest And Valid Q&A | Instant Download | Once Fail, Full Refund
