Final Exam: Systems Architect
Final Exam: Systems Architect will test your knowledge and application of the topics presented throughout the Systems Architect track.
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Final Exam: Systems Architect
define safety and reliability of systems and their relationship to risk in the system life cycle
identify tools for assessing and managing system risk
identify techniques for analyzing system reliability
recognize the importance of communicating risk to stakeholders
outline the role of verification and validation in ensuring quality, reliability, and safety
recognize the purposes of validation and verification and how they complement each other in the systems development process
provide an overview of continuous verification throughout a system life cycle, emphasizing the importance of adapting to changing requirements and conditions
outline how to analyze validation and verification results, interpret findings, and generate comprehensive reports
recognize the ethical implications of system failures due to inadequate validation and verification
provide an overview of common validation errors, methods for mitigating system failure, and why validation fails
outline key performance indicators (KPIs), KPI categories, KPI metrics, and examples of process-specific, system-based, and project-based KPIs
recognize how performance measurements are used to assess systems engineering performance
identify key aspects of project outputs used in systems
outline how KPIs influence decision-making and how to hone KPIs for better decision-making
identify goals and best practices of reporting performance measurements and various report types
provide an overview of principles and methodologies in system architecture and design
outline the role of systems architecture
describe various types of architecture
describe trade-offs during system architecture design
describe key system architecture design capabilities
outline methods for integrating and interfacing different subsystems within a complex system
outline the principles of system optimization in the context of systems engineering
use mathematical modeling techniques to optimize system performance
describe trade-offs between different system parameters and design choices
provide an overview of decision analysis models and how they can be used to evaluate and select the most optimal system configurations
outline the impact of resource constraints and limitations on system optimization
outline the importance of system operation and maintenance in ensuring system reliability and performance
recognize key considerations for effective systems operations and maintenance planning
recognize key considerations for the change management process in engineering
outline system changes as it relates to scope, communication, and stakeholders
provide an overview of risk management when dealing with system changes and disruptions
identify the challenges and considerations associated with system upgrades, patches, and maintenance activities
provide an overview of the fundamental principles and benefits of Model-Based Systems Engineering (MBSE)
outline considerations for system model creation using standardized modeling languages and tools
demonstrate how to create a basic system model using a standardized modeling language
describe how MBSE facilitates the capture of system requirements, behavior, and structure in models
discuss how MBSE relates to the system development life cycle (SDLC)
outline the role of traceability in MBSE
describe popular tools used in MBSE
discuss challenges and best practices in implementing MBSE in real-world projects
provide an overview of Sparx Enterprise Architect software, its purpose, and uses
outline key features of Sparx EA software
provided an overview of SysML and the transition to SparX
describe how to install and navigate Sparx EA
demonstrate how to build a model using Sparx EA
provide an overview of relationships and dependencies in Sparx EA, including tracing relationships and dynamic relationships
demonstrate how to create relationships and dependencies using Sparx EA
outline simulation and behavior, dynamic model simulation, and business process modeling and behavior capabilities in Sparx EA
provide an overview of concurrent engineering and its principles
outline key benefits of concurrent engineering
describe common challenges associated with concurrent engineering
provide an overview of stakeholder engagement in Concurrent Engineering
outline key considerations for conflict management in collaborative environments
identify how collaborative engineering environments can be improved upon using tools and techniques to improve the overall team effort
provide an overview of communication methods in concurrent engineering environments
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