CyberArk CDE Recertification (CAU305日本語版) : CAU305日本語 Exam

  • Exam Code: CAU305J
  • Exam Name: CyberArk CDE Recertification (CAU305日本語版)
  • Updated: Aug 02, 2026
  • Q & A: 66 Questions and Answers

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  • Where are all the places you need to look to fully identify what permissions a particular user has?

  • Ensuring privacy (e.g., Data Loss Prevention API)

  • Conversational experiences (e.g., Dialogflow)

  • Machine learning terminology (e.g., features, labels, models, regression, classification, recommendation, supervised and unsupervised learning, evaluation metrics)

  • How are valid JQL queries written? What operators and arguments are valid for various JQL functions (e.g. membersOf(), StartOfDay(), WAS, CHANGED, etc.)

  • Distributed vs. single machine

  • Choosing between ACID, idempotent, eventually consistent requirements

  • What are the features, uses, limitations/restrictions of workflow changes, especially the Simplified Workflow?

  • When is it best to use components, and when is it best to use a custom field instead?

  • What features are available for Jira Software projects, and to users who have Jira Software application access (as compared to just Jira Core)?

  • Continuous evaluation

  • Designing for security and compliance

  • What changes can be performed on statuses and transitions?

  • Performing data preparation and quality control (e.g., Cloud Dataprep)

  • Which project details can be added and changed by Project Administrators?

  • What are all the various factors that influence whether a field is visible on a screen?

  • Measuring, monitoring, and troubleshooting machine learning models

  • Deploying an ML pipeline

  • Who can change the Simplified Workflow? What are the limitations on changes to the Simplified Workflow?

  • ML APIs (e.g., Vision API, Speech API)

  • What is the importance of the Browse Projects permission?

  • Planning, executing, and stress testing data recovery (fault tolerance, rerunning failed jobs, performing retrospective re-analysis)

  • Data staging, cataloging, and discovery

  • Securely Managing the System Architecture

  • What workflow changes can be done through the board by board administrators?

  • Leveraging pre-built ML models as a service

  • What is an Issue Collector and what permissions are needed to configure it?

  • Which business requirements necessitate the use of separate issue types in a project (e.g. different screens, workflows, etc.)?

  • How do combinations of permissions work together to enable specific actions?

  • Operationalizing machine learning models

  • Mapping to current and future business requirements

  • Building and running test suites

  • Data security (encryption, key management)

  • Assessing, troubleshooting, and improving data representations and data processing infrastructure

  • What are the configuration options for all the out-of-box reports and gadgets (except Agile reports and gadgets)? What is their behavior and expected results?

  • Choosing the appropriate training and serving infrastructure

  • Ingesting appropriate data

  • Designing for data and application portability (e.g., multi-cloud, data residency requirements)

  • Ensuring scalability and efficiency

  • Defining the CyberArk Privileged Account Security Solution Architecture

  • Retraining of machine learning models (Cloud Machine Learning Engine, BigQuery ML, Kubeflow, Spark ML)

  • What is the relationship between screens, screen schemes and issue type screen schemes?

  • Hardware accelerators (e.g., GPU, TPU)

  • Legal compliance (e.g., Health Insurance Portability and Accountability Act (HIPAA), Children's Online Privacy Protection Act (COPPA), FedRAMP, General Data Protection Regulation (GDPR))

  • Common sources of error (e.g., assumptions about data)

  • Ensuring reliability and fidelity

  • Verification and monitoring

  • What types of workflow changes can Project Administrators make if Extended Project Administration is activated?

  • Impact of dependencies of machine learning models

  • Monitoring Privileged Account Access

  • What things may need to be updated as a result of workflow changes of any kind?

  • Use of edge compute

  • What are the uses of Project Category in Jira?

  • Resizing and autoscaling resources

  • What are the use cases where it is best to use Project Roles rather than Groups?

  • Customizing ML APIs (e.g., AutoML Vision, Auto ML text)

  • Target Hosts Using Privileged Session Manager

  • Pipeline monitoring (e.g., Stackdriver)

  • Identity and access management (e.g.,Cloud IAM)

  • Who can change a Project Key, and what are the effects on issues in the project?

  • Which configurations (schemes, versions, components, etc) are shared versus unique when new projects are (1) created from template or (2) with a shared configuration?

  • Which export options are available from the Issue Navigation? The following will be discussed here:

  • Ensuring flexibility and portability

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The benefit in Obtaining the CAU305 Exam Certification

The recertification exam provides the practical knowledge and technical skills to securely design, install, and configure the CyberArk Privileged Access Security Solution. The candidates will gain valuable hands-on experience installing CyberArk components, configuring Authentication Types, and System Integrations (SIEM, SMTP, SNMP), using our step-by-step exercise guide, official product documentation and a dedicated lab environment.

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CyberArk CAU305日本語 Exam Syllabus Topics:

SectionObjectives
Topic 1: Implementation and Configuration- Vault deployment and configuration
- Safe management and permissions
- Platform management and onboarding
Topic 2: Privileged Access Management Fundamentals- CyberArk PAS architecture overview
- Core components (Vault, PVWA, CPM, PSM)
Topic 3: Advanced Security and Use Cases- Privilege threat analytics overview
- Security best practices in PAS
- Session management and PSM usage
Topic 4: Operations and Maintenance- Upgrades and patch management
- Backup and restore procedures
- Monitoring and troubleshooting

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