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Pegasystems PEGACPDS88V1 (Certified Pega Data Scientist 88V1) Certification Exam is a globally recognized certification exam that validates the skills and knowledge of data scientists in Pega technology. Certified Pega Data Scientist 88V1 certification exam is designed to test the ability of the candidates to use Pega tools and techniques to analyze and model business data. PEGACPDS88V1 exam is intended for professionals who want to demonstrate their expertise in Pega data science and analytics.
Pegasystems PEGACPDS88V1 (Certified Pega Data Scientist 88V1) Exam is a certification exam designed to test the knowledge and skills of professionals in the field of data science using the Pega platform. PEGACPDS88V1 exam is ideal for data scientists, machine learning engineers, and other professionals who work with data on a regular basis and want to demonstrate their expertise in using the Pega platform to solve complex data problems.
NEW QUESTION # 12
In a strategy defined in the "Retension" issue and the "X-Sell" group, you can import________
- A. All active actions
- B. Actions from the "Sales" issue
- C. Actions from all groups under the "Retention" issue
- D. Actions from "X-Sell" group
Answer: C
Explanation:
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.
NEW QUESTION # 13
U+ Bank wants to offer a 10% discount for customers whose CLV value is higher than 400. Which strategy component should you use to meet the new requirement?
- A. Filter
- B. Group By
- C. Set Property
- D. Prioritize
Answer: A
Explanation:
Explanation
To offer a 10% discount for customers whose CLV value is higher than 400, you should use the Filter strategy component.
NEW QUESTION # 14
The purpose of regular inspection is to detect factors that negatively influence the performance of the adaptive models and the success rate of the actions. Which two issues should be discussed with the business? (Choose Two)
- A. Predictors that are never used
- B. Actions that have a low number of responses
- C. Actions that are offered so often that they dominate other actions
- D. Actions for which the model is not predictive
- E. Predictors with a low performance_________
Answer: C,E
Explanation:
Explanation
When performing regular inspection of adaptive models, two issues that should be discussed with the business are predictors with a low performance and actions that are offered so often that they dominate other actions.
NEW QUESTION # 15
What is the difference between predictive and adaptive analytics?
- A. Predictive models predict customer behavior.
- B. Predictive models can predict a continuous value.
- C. Predictive models have evidence.
- D. Adaptive models use the customer data as predict*
Answer: D
Explanation:
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/adaptive-m
NEW QUESTION # 16
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. Up to 100 fields to limit the impact on model speed
- D. All available uncorrected fields
Answer: C
Explanation:
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.
NEW QUESTION # 17
A text prediction perform natural language processing on a piece of text. It then produces a structured output, which can be analyzed using reports.
What is one of the types of text analysis that a text prediction performs?
- A. Word count
- B. Entity extraction
- C. Cross reference analysis
- D. Word analysis
Answer: B
Explanation:
Explanation
Text prediction is a type of natural language processing that uses AI and statistics to predict the next word in a sentence based on the preceding words . Text analysis is a process of extracting information from text data using various methods and tools. One of the types of text analysis that a text prediction performs is entity extraction23, which is the identification and classification of named entities such as people, places, organizations, dates, etc. in a text.
NEW QUESTION # 18
MyCo, a telecommunications company, wants to implement one-to-one customer engagement using Pega Customer Decision Hub. Which three of the following real-time channels can the company use to present Next-Best-Actions? (Choose Three)
- A. Billboard on the company building
- B. Traditional television advertisements
- C. SMS
- D. Call center
- E. Retail store
Answer: C,D,E
Explanation:
Explanation
Call center, SMS, and Retail store Reference:
MyCo can use Call center, SMS, and Retail store as real-time channels to present Next-Best-Actions.
NEW QUESTION # 19
As a data scientist, you want to use a predictive model to detect potential churn for a telecom company.
Which three options do you have? (Choose Three)
- A. Create a Text extraction model
- B. Use a Google ML model
- C. Use Pega machine learning to build a model
- D. Import a third party PMML model
- E. Use a machine learning service
- F. Create an adaptive self-learning model
Answer: C,D,F
Explanation:
* Import a third party PMML model : PMML stands for Predictive Model Markup Language, which is an XML-based standard for representing predictive models. You can import a PMML model that was created by another tool or platform into Pega and use it in your strategies.
* Create an adaptive self-learning model : An adaptive model is a type of predictive model that learns from customer responses and adapts its predictions over time. You can create an adaptive model in Pega and configure its parameters, such as learning rate, decay rate, and performance goal.
* Use Pega machine learning to build a model1: Pega machine learning is a feature that allows you to build predictive models using various algorithms, such as decision trees, logistic regression, neural networks, and random forests. You can use Pega machine learning to build a model from your data and evaluate its performance.
NEW QUESTION # 20
A very important aspect of each model is how good a model or a given predictor is in predicting the required behavior. When building a predictive model, the use of testing and validation samples___________________
- A. enables model validation in strategies
- B. is mandatory for segmentation
- C. validates the quality of input data
- D. increases the accuracy of models
Answer: D
Explanation:
Explanation
A predictive model is a mathematical function that estimates the probability of an outcome based on input data. When building a predictive model, the use of testing and validation samples increases the accuracy of models123. Testing and validation samples are subsets of data that are used to evaluate how well a model performs on new data that was not used to train the model. Testing and validation samples help prevent overfitting, which is when a model learns too much from the training data and fails to generalize to new data.
NEW QUESTION # 21
Which statement about the PMML standard is correct?
- A. The PMML standard is designed to facilitate the exchange of models between applications
- B. The PMML standard is designed to facilitate the exchange of scores between applications
- C. The PMML standard is a proprietary standard
- D. The PMML standard can only be used to describe tree, scorecard and regression models.
Answer: A
Explanation:
Explanation
The PMML standard is designed to facilitate the exchange of models between applications.
NEW QUESTION # 22
U+ Insurance uses Pega Process AI and wants straight-through processing of claims with a low fraud risk.
As a data scientist, you create a prediction that calculates the probability that a claim is fraudulent.
What type of prediction do you create to meet this requirement?
- A. A Customer Decision Hub prediction.
- B. A text analytics prediction.
- C. A case management prediction.
- D. A fraud detection prediction
Answer: C
Explanation:
Explanation
to create a prediction that calculates the probability that a claim is fraudulent, you need to create a case management prediction. This type of prediction allows you to use predictive models built on external platforms such as H2O.ai and apply them to case types in Pega Process AI. You can then use the prediction outcome in a decision step to route claims based on their fraud risk.
https://academy.pega.com/challenge/creating-fraud-prediction/v3
NEW QUESTION # 23
Which property is automatically recomputed for each decision component?
- A. Rank
- B. Property
- C. Priority
- D. Order
Answer: A
Explanation:
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
NEW QUESTION # 24
U+ Telecom uses predictive analytics in its retention strategy. You have created a predictive model based on recent historical company data and have placed the new model in shadow mode. Which statement is true about the new predictive model?
- A. The active model and the new model affect business outcomes
- B. The new model affects business outcomes
- C. The active model does not affect business outcomes
- D. The new model does not affect business outcomes
Answer: B
Explanation:
Explanation
The new model does not affect business outcomes Reference:
When you place a new predictive model in shadow mode, it does not affect business outcomes.
NEW QUESTION # 25
Which value is output by an Adaptive Model?
- A. Score
- B. Performance
- C. Lift
- D. Behavior
Answer: D
Explanation:
Explanation
The value that is output by an adaptive model is behavior, which indicates the likelihood that the customer will accept or respond to an offer. Behavior is also known as propensity or probability in decision strategies.
References:
https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data-archived/topic/using-adap
NEW QUESTION # 26
Which decision component allows you to use a third-party Credit Risk Model 80% of the time and a Pega Credit Risk Model 20%?
- A. Switch
- B. Champion Challenger
- C. Adaptive Model
- D. Filter
Answer: A
Explanation:
Explanation
The Switch component allows you to use a third-party Credit Risk Model 80% of the time and a Pega Credit Risk Model 20%.
NEW QUESTION # 27
A Scoring Model allows you to differentiate between
- A. Good, Bad, Unknown
- B. Good, Better, Best
- C. Good, Bad
- D. Accept, Reject, Maybe Later
Answer: B
Explanation:
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
NEW QUESTION # 28
Using Prediction Studio to build Pega machine learning models on historical data, you can build two types of models:____________and____________.
(Choose Two)
- A. binary models
- B. adaptive models
- C. continuous models
- D. voice to text model
Answer: A,B
Explanation:
Explanation
Using Prediction Studio to build Pega machine learning models on historical data, you can build two types of models: binary models and adaptive models.
NEW QUESTION # 29
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. pxSegment
- B. nxOutcome
- C. pxResult
- D. pxEvidence
Answer: C
Explanation:
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
NEW QUESTION # 30
Adaptive model predictors are selected from the____________.
- A. customer profile
- B. proposition profile
- C. similar propositions
- D. communication channel
Answer: A
Explanation:
Explanation
Adaptive model predictors are selected from the customer profile, which contains information about the customer's attributes and behavior. Predictors can be either scalar or aggregate properties that capture customer context, such as channel, location, time, etc. References:
https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data-archived/topic/configuring
NEW QUESTION # 31
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