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Pegasystems PEGACPDS88V1認定試験は、認定Pega Data Scientistになりたい個人の知識とスキルをテストすることを目的としています。Pega Data Scientistは、Pegaの予測および適応型分析ツールを使用してデータを分析し、ビジネスの意思決定に役立つ洞察を得る能力を持つ専門家です。この試験は、統計モデリング、データ可視化、機械学習、およびデータ管理など、幅広いトピックをカバーしています。この試験は、難易度が高く、包括的に設計されており、最も適格な個人のみが認定を取得することができます。
Pegasystems PEGACPDS88V1認定試験を受験するには、個人はデータサイエンスの概念と技術に強い理解を持っている必要があります。また、Pegaの分析ツールを使用した経験があり、それらを実際のビジネス問題に適用できる能力を持っている必要があります。試験は60問の多肢選択問題で構成され、時間制限は90分です。試験に合格した個人は、認定を取得し、Pegaデータサイエンスの分野の専門家として認められます。この認定は業界で非常に高く評価され、個人のキャリアを進め、収益性を高めることができます。
質問 # 34
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. Customer Decision Hub
- C. Text analysis
- D. Case management
正解：B
解説：
Explanation
Customer Decision Hub Reference:
To optimize the click-through rate of a web banner, you need to create a Customer Decision Hub prediction.
質問 # 35
Two results of an adaptive model are
- A. Priority and Propensity
- B. Propensity and Rank
- C. Propensity and Performance
- D. Priority and Evidence
正解：C
解説：
Explanation
Two results of an adaptive model are propensity and performance. Propensity is the probability that the customer will accept or respond to an offer. Performance is a measure of how well the adaptive model predicts customer behavior over time. References:
https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data-archived/topic/adaptive-m
質問 # 36
You are a company with a new and unique product, and you want to offer it to the right customer.
Give the scenario, which rule type should you use?
- A. Decision table
- B. Adaptive model
- C. Predictive model
- D. Scorecard
正解：B
解説：
Explanation
You are a company with a new and unique product, and you want to offer it to the right customer. Given the scenario, you should use an adaptive model rule type. An adaptive model rule type allows you to define the predictors and the outcome of the model and associate it with an action. An adaptive model learns from customer responses in real time and predicts the propensity of each customer to accept the action. An adaptive model is suitable for new products or markets where there is no historical data available. References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-decision
質問 # 37
The Pega Customer Decision Hub delivers Next-Best-Actions consistently through multiple channels. To which of the following channels does this apply?
- A. Billboard
- B. Mobile
- C. Cable television
- D. Traditional newspaper
正解：B
解説：
Explanation
The Pega Customer Decision Hub delivers Next-Best-Actions consistently through multiple channels. This applies to Mobile channels.
質問 # 38
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. Limit the number of responses
- B. Suit the use case
- C. Optimize the success rate
- D. Increase lift
正解：B
解説：
Explanation
As a data scientist, a valid reason to adjust the default response timeout in a prediction is to suit the use case.
質問 # 39
To measure the boost in success rate AI generates, you need
- A. a control group of customers that receive a random action
- B. a control group of customers that receive a standard action
- C. a control action that is offered to a fixed group of customers
- D. a control action that is offered to random customers
正解：D
解説：
Explanation
To measure the boost in success rate AI generates, you need a control action that is offered to random customers.
質問 # 40
When building a predictive model, at what stage do you compare the performance of predictive models?
- A. Model Comparison stage
- B. Model Export stage
- C. Model Analysis stage
- D. Model Development stage
正解：A
解説：
Explanation
When building a predictive model, you compare the performance of predictive models at the Model Comparison stage. This stage allows you to select the best model based on various metrics, such as accuracy, lift, or area under curve (AUC). References:
https://academy.pega.com/module/predictive-analytics/topic/comparing-predictive-models
質問 # 41
Pega Customer Decision Hub uses the P*C*V*L arbitration formula to select the next best action for each customer. Which description best describes the purpose of the formula?
- A. To ensure that every customer receives the same action
- B. To ensure that the customer is always given the best offer, regardless of the business objective
- C. To provide insight into business processes
- D. To balance customer needs with business objectives
正解：D
解説：
Explanation
Pega Customer Decision Hub uses the PCV*L arbitration formula to select the next best action for each customer. The purpose of the formula is to balance customer needs with business objectives.
質問 # 42
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 for which the model is not predictive
- D. Predictors with a low performance_________
- E. Actions that are offered so often that they dominate other actions
正解：D、E
解説：
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.
質問 # 43
The decision components used on the strategy canvas are interconnected by arrows. What does a solid arrow from a "Set Property" component to a "Filter" component mean?
- A. There is a one-to-one relationship between a "Set Property" and a "Filter" component.
- B. Information from the "Set Property" component is copied over to the "Filter" component.
- C. A property from the "Set Property" component is referenced by the "Filter" component.
- D. To evaluate the "Set Property" component, the "Filter" component is evaluated first.
正解：C
解説：
Explanation
A solid arrow from a "Set Property" component to a "Filter" component means that a property from the "Set Property" component is referenced by the "Filter" component. For example, you can use a "Set Property" component to calculate a customer's age and then use a "Filter" component to remove actions that are not suitable for that age group. References:
https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/setting-properti
質問 # 44
A best practice in data science is to use a control group. What business metric is supported by this practice?
- A. The lift that the prediction generates
- B. The success rate of the prediction
- C. The performance of the prediction
- D. The number of responses
正解：A
解説：
Explanation
The lift that the prediction generates Reference:
Using a control group is a best practice in data science that supports the business metric of the lift that the prediction generates.
質問 # 45
In a decision strategy, to remove propositions based on the current month, you use a
- A. Data Strategy property
- B. Calendar component
- C. Filter component
- D. Calendar strategy property
正解：B
解説：
Explanation
The calendar component is used to remove propositions based on the current month, day of week, or time of day. It can also be used to apply seasonal adjustments to propositions. References:
https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/using-calendar-
質問 # 46
The filter component is used to filter_______
- A. Actions
- B. attributes
- C. Customers
- D. Adaptive models
正解：A
解説：
Explanation
The filter component is used to filter actions based on various criteria, such as eligibility, suitability, priority, or custom conditions. References:
https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/filtering-action
質問 # 47
What is the most accurate description of proactive retention? Proactive Retention_______
- A. simplifies the process of retaining customers
- B. enables the business to reduce the number of credit risk customers
- C. anticipates potential customer churn
- D. enables business to respond to customers when they contact a call center
正解：C
解説：
Explanation
Proactive retention is a strategy that anticipates potential customer churn and takes actions to prevent it before it happens. It uses predictive analytics to identify customers who are at risk of leaving and offers them incentives or solutions to retain them. References:
https://academy.pega.com/module/one-one-customer-engagement/topic/proactive-retention
質問 # 48
As a highly experienced data scientist, which two advanced settings are available to you? (Choose Two)
- A. Predictor selection
- B. Predictor types
- C. The parameters used to bin the responses
- D. The update frequency of the models
- E. Outcomes
正解：A、D
解説：
Explanation
Predictor selection and The update frequency of the models Reference:
As a highly experienced data scientist, you have access to advanced settings such as predictor selection and the update frequency of the models
質問 # 49
To enable an assessment of its reliability the adaptive model produces four outputs: propensity,performance, evidence and positives.
The Performance of an adaptive model that has not collected any evidence yet is______.
- A. 0
- B. 1
- C. 2
- D. 3
正解：D
解説：
Explanation
The performance of an adaptive model that has not collected any evidence yet is 50. This means that the model is not confident about its predictions and assigns equal probability to all actions. References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-decision
質問 # 50
The adaptive model component in a decision strategy computes
- A. A single accept rate for all actions
- B. A unique accept rate for each action
- C. A propensity value for each action
- D. A single propensity value for all actions
正解：C
解説：
Explanation
The adaptive model component in a decision strategy computes a propensity value for each action. Propensity is the likelihood of a positive response for a given action and predictor profile. It ranges from 0 to 100.
References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-decision
質問 # 51
In a decision strategy, the Adaptive Model decision component belongs the
- A. Arbitration category
- B. Decision Analytics category
- C. Predictive Model category
- D. Business Rules category
正解：B
解説：
Explanation
In a decision strategy, the Adaptive Model decision component belongs to the Decision Analytics category.
This category contains components that use advanced analytics techniques, such as adaptive models, predictive models, text analytics models, etc., to make predictions or recommendations. References:
https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/decision-analyt
質問 # 52
Evidence an assessment of its viability, the Adaptive Model produces three outputs: Propensity, Performance and what is evidence in the context of an Adaptive Model? Performance and what is evidence in the context of an Adaptive Model?
- A. The number of customers who have responded to the modeled offer
- B. The likelihood of a statistically similar behavior
- C. The number of customers who exhibited statistically similar behavior
- D. The number of statistical bins used to evaluate the response
正解：C
解説：
Explanation
Evidence is the number of customers who exhibited statistically similar behavior to the current customer and responded to the modeled offer. It indicates how reliable the propensity score is based on the available data.
References:
https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data-archived/topic/adaptive-m
質問 # 53
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 an adaptive self-learning model
- B. Import a third party PMML model
- C. Create a Text extraction model
- D. Use Pega machine learning to build a model
- E. Use a machine learning service
- F. Use a Google ML model
正解：A、B、D
解説：
* 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.
質問 # 54
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. business levers
- B. product compatibility rules
- C. product eligibility rules
- D. customer contact rules
正解：A
解説：
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-
質問 # 55
The purpose of predictions is to______________
- A. add predictors to adaptive models
- B. monitor the success rate of individual actions
- C. add best data scientist practices to adaptive models
- D. build adaptive models
正解：C
解説：
Explanation
The purpose of predictions is to build adaptive models.
質問 # 56
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