PEGAPCSSA86V1 Pegasystems Pega Certified Senior System Architect (PCSSA) 86V1 Exam

Exam Name Pega Certified System Architect
Exam Code PCSA
Exam Duration 90 Minutes
Number of Questions 60
Passing Score 65%
Format Multiple Choice Questions

About Pegasystems
Pega is the leader in cloud software for customer engagement and operational excellence. The world’s most recognized and successful brands rely on Pega’s AI-powered software to optimize every customer interaction on any channel while ensuring their brand promises are kept. Pega’s low-code application development platform allows enterprises to quickly build and evolve apps to meet their customer and employee needs and drive digital transformation on a global scale. For more than 35 years, Pega has enabled higher customer satisfaction, lower costs, and increased customer lifetime value.

Certified Pega System Architect
The Certified Pega System Architect version 8.6 certification is for developers and technical staff members who want to learn how to develop Pega applications. This certification is the first level in the System Architect certification path and provides a baseline measurement on your knowledge of Pega applications. The PCSA Version 8.6 exam includes scenario questions, multiple choice questions and drag/drop items.

Exam Code: PEGAPCSA86V1
Languages: English | French | German | Japanese | Portuguese-Brazilian | Spanish

Retirement date: September 30, 2022
Prerequisites : System Architect

Case Management (28%)
Design a case lifecycle, stages, set case statuses, add instructions to tasks
Add a service level agreement; configure urgency, goals, deadlines, passed deadlines
Route assignments to users, work groups, work queues
Configure approval processes; cascading approvals, authority matrix
Configure and send email correspondence
Identify duplicate cases
Identify and add optional actions
Automate workflow decisions using conditions
Pause and resume case processing; wait steps
Skip a stage or process
Configure child cases
Understand when to use automation shapes
Automate decisions using decision tables and decision trees
Create and manage teams of users

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Data and Integration (18%)
Configure data types, create data objects, data relationships, and field types
Identify and create calculated values
Validate data; create and configure data validation rules by using business logic
Manipulate application data, set default property values, configure data transforms
Access sourced data in a case; refresh strategies; populate user interface controls
Save data to a system of record
Simulate and add external data sources
Capture and present data; fields and views
View data in memory; clipboard tool, pyWorkPage

Security (7%)
Manage user and role assignments
Configure security policies
Track and audit changes to data

DevOps (7%)
Use unit test rules
Create and execute scenario-based test cases
Identify best practices for configuring unit tests

User Experience (16%)
Customize user interface elements, dashboards, portal content, configure action sets
Customize form appearance, visibility settings, controls
Add and remove fields
Group fields in views
Display list data in views; configure repeating dynamic layouts
Localize application content
Enable accessibility features in an application

Application Development (12%)
Manage application development; user stories, feedback, bugs
Use the Estimator to scope a Pega Platform project
Create and maintain rules, rulesets, classes, inheritance
Debug application errors

Reporting (7%)
Create business reports
Identify types of reports
Use columns and filters
Describe the benefits of using Insights

Mobility (5%)
Configure mobile app channels
Use of Pega Mobile Preview

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QUESTION 1
Which two factors do you inspect to assess the general health of the adaptive models in Certkingdom Prediction Studio? (Choose Two.)

A. Model transparency
B. Insights
C. Performance of the models
D. Number of decisions

Answer: A,C

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QUESTION 2
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

Answer: D

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QUESTION 3
When defining outcomes for an Adaptive Model you must define.

A. only negative behavior values
B. positive, negative and neutral behavior values
C. one or more positive behavior values
D. behavior values to be ignored

Answer: A

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QUESTION 4
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?

A. The likelihood of a statistically similar behavior
B. The number of customers who exhibited statistically similar behavior
C. The number of statistical bins used to evaluate the response
D. The number of customers who have responded to the modeled offer

Answer: D

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QUESTION 5
A company wants to simulate decisions that requires large amounts of data. However, the Certkingdom organisation’s live data is inaccessible. Your advice is to use a Monte Carlo data set. The Monte Carlo method

A. enables the company to generate random data for most of its application needs
B. generates data that the company can use as input for adaptive decisioning
C. combines external data sets into a larger data set
D. makes the organisation’s live data accessible

Answer: A