Pegasystems PEGACPDS88V1 Certified Pega Data Scientist 8.8 Online Training
Pegasystems PEGACPDS88V1 Online Training
The questions for PEGACPDS88V1 were last updated at Nov 20,2024.
- Exam Code: PEGACPDS88V1
- Exam Name: Certified Pega Data Scientist 8.8
- Certification Provider: Pegasystems
- Latest update: Nov 20,2024
When implementing Next-Best-Action, the Customer Lifetime Value Threshold is typically used to_________.
- A . prioritize high value propositions
- B . prioritize customers
- C . determine if the customer is eligible
- D . calculate the customer’s lifetime value
B
Explanation:
The Customer Lifetime Value Threshold is typically used to prioritize customers based on their expected long-term value to the business. Customers who have a higher lifetime value than the threshold are considered high-value customers and receive more personalized and relevant offers.
References: https://academy.pega.com/module/one-one-customer-engagement/topic/next-best-action-designer
A legal firm wants to use text analytics for easier and faster access to information to helo with compliance related issues. The legal firm needs a taxonomy of legal concepts.
What is a taxonomy?
- A . A list of business rules
- B . The output of an expert survey
- C . A sentiment analysis model
- D . A list of valid categories
D
Explanation:
A taxonomy is a list of valid categories that can be used to classify text documents or entities. A taxonomy can be hierarchical or flat, depending on the level of detail required.
References: https://academy.pega.com/module/text-analytics/topic/creating-taxonomy
To optimize their customer interactions, U+ Bank routes all emails that are complaints to a specialized department. To identify emails that voice a complaint, the text prediction uses___________
- A . An entity extraction model
- B . a topic model
- C . a language model
- D . a sentiment model
B
Explanation:
Topic models are typically used to identify the main themes or topics in a body of text. In this case, a topic model could be used to identify emails that pertain to the topic of "complaints".
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 . Adaptive prediction
- B . Case management
- C . Customer Decision Hub
- D . Text analysis
A
Explanation:
Predictive analytics tools like Prediction Studio are used to build predictive models. To optimize the click-through rate of a web banner, you would likely use an adaptive prediction, which uses machine learning to improve predictions based on past data.
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 . Suit the use case
- B . Optimize the success rate
- C . Increase lift
- D . Limit the number of responses
A
Explanation:
As a data scientist, a valid reason to adjust the default response timeout in a prediction is to suit the use case.
Prediction Studio supports keyword-based topic detection, model-based topic detection and the combination of these.
When using machine learning,
- A . keywords have a higher impact on the model than the training data
- B . the Must keywords are required to detect the topic
- C . the Must keywords function as positive features
- D . the keywords are ignored
C
Explanation:
When using machine learning, the Must keywords function as positive features.
What happens when you increase the performance threshold setting of an adaptive model rule?
- A . The number of active predictors increases
- B . The performance of the model is increased
- C . The correlation threshold decreases
- D . The number of active predictors may decrease
D
Explanation:
When you increase the performance threshold setting of an adaptive model rule, the number of active predictors may decrease. The performance threshold is the minimum performance that a predictor must have to be included in the model. If you increase this value, some predictors may not meet the criteria and be excluded from the model.
References: https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-decision-adaptivemodel/main.htm
To enable an assessment of its reliability, the Adaptive Model produces three outputs: Propensity, Performance and Evidence. The performance of an Adaptive Model that has not collected any evidence is_________.
- A . 1-0
- B . null
- C . 0.5
- D . 0.0
B
Explanation:
The performance of an Adaptive Model that has not collected any evidence (i.e., hasn’t been trained on any data yet) is typically indicated as null, as it doesn’t have any basis for making accurate predictions yet.
As a data scientist, you are tasked with creating a new prediction that estimates a customers’ likelihood to leave the business in the near future. The NBA analyst wants to move forward and use the prediction in Pega Customer Decision Hub™ to test the application.
To unblock the NBA specialist, which task do you prioritize?
- A . Create the prediction
- B . Create the customer data model
- C . Create a placeholder scorecard to drive the prediction
- D . Create the predictive model that drives the prediction
D
Explanation:
To unblock the NBA specialist, as a data scientist, you should prioritize creating the predictive model that drives the prediction.
Which property is automatically recomputed for each decision component?
- A . Property
- B . Rank
- C . Order
- D . Priority
B
Explanation:
The rank property is automatically recomputed for each decision component. It indicates the order in which the actions are presented to the customer, based on their priority and propensity.
References: https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/ranking-actions
Latest PEGACPDS88V1 Dumps Valid Version with 140 Q&As
Latest And Valid Q&A | Instant Download | Once Fail, Full Refund
