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CAU305 Exam topics
Candidates must know the Defender + Sentry exam topics before they start of preparation because it will really help them in hitting the core. Our CAU-305 practice test and CAU-305 practice exams will include the following topics. These are covered in our CAU-305 exam dumps.
What are all the various factors that influence whether a field is visible on a screen?
Continuous evaluation
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
What are the uses of Project Category in Jira?
Designing for security and compliance
Who can change a Project Key, and what are the effects on issues in the project?
Pipeline monitoring (e.g., Stackdriver)
Operationalizing machine learning models
Machine learning terminology (e.g., features, labels, models, regression, classification, recommendation, supervised and unsupervised learning, evaluation metrics)
Data staging, cataloging, and discovery
Planning, executing, and stress testing data recovery (fault tolerance, rerunning failed jobs, performing retrospective re-analysis)
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?
Ensuring flexibility and portability
Securely Managing the System Architecture
Which project details can be added and changed by Project Administrators?
Common sources of error (e.g., assumptions about data)
Monitoring Privileged Account Access
Hardware accelerators (e.g., GPU, TPU)
When is it best to use components, and when is it best to use a custom field instead?
Resizing and autoscaling resources
Ensuring reliability and fidelity
Defining the CyberArk Privileged Account Security Solution Architecture
What are the use cases where it is best to use Project Roles rather than Groups?
Legal compliance (e.g., Health Insurance Portability and Accountability Act (HIPAA), Children's Online Privacy Protection Act (COPPA), FedRAMP, General Data Protection Regulation (GDPR))
Which configurations (schemes, versions, components, etc) are shared versus unique when new projects are (1) created from template or (2) with a shared configuration?
Choosing the appropriate training and serving infrastructure
Target Hosts Using Privileged Session Manager
Retraining of machine learning models (Cloud Machine Learning Engine, BigQuery ML, Kubeflow, Spark ML)
Deploying an ML pipeline
Conversational experiences (e.g., Dialogflow)
What are the features, uses, limitations/restrictions of workflow changes, especially the Simplified Workflow?
What is an Issue Collector and what permissions are needed to configure it?
How do combinations of permissions work together to enable specific actions?
Designing for data and application portability (e.g., multi-cloud, data residency requirements)
Data security (encryption, key management)
What workflow changes can be done through the board by board administrators?
Customizing ML APIs (e.g., AutoML Vision, Auto ML text)
What is the relationship between screens, screen schemes and issue type screen schemes?
Which export options are available from the Issue Navigation? The following will be discussed here:
Which business requirements necessitate the use of separate issue types in a project (e.g. different screens, workflows, etc.)?
Use of edge compute
Choosing between ACID, idempotent, eventually consistent requirements
Performing data preparation and quality control (e.g., Cloud Dataprep)
Leveraging pre-built ML models as a service
What types of workflow changes can Project Administrators make if Extended Project Administration is activated?
Ensuring privacy (e.g., Data Loss Prevention API)
Building and running test suites
Who can change the Simplified Workflow? What are the limitations on changes to the Simplified Workflow?
What features are available for Jira Software projects, and to users who have Jira Software application access (as compared to just Jira Core)?
ML APIs (e.g., Vision API, Speech API)
Identity and access management (e.g.,Cloud IAM)
Verification and monitoring
Ensuring scalability and efficiency
What changes can be performed on statuses and transitions?
What things may need to be updated as a result of workflow changes of any kind?
Ingesting appropriate data
Mapping to current and future business requirements
Measuring, monitoring, and troubleshooting machine learning models
What is the importance of the Browse Projects permission?
Where are all the places you need to look to fully identify what permissions a particular user has?
Impact of dependencies of machine learning models
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CyberArk CAU305 Exam Reference
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CyberArk CAU305日本語 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Implementation and Configuration | - Vault deployment and configuration - Safe management and permissions - Platform management and onboarding |
| Topic 2: Advanced Security and Use Cases | - Privilege threat analytics overview - Session management and PSM usage - Security best practices in PAS |
| Topic 3: Privileged Access Management Fundamentals | - Core components (Vault, PVWA, CPM, PSM) - CyberArk PAS architecture overview |
| Topic 4: Operations and Maintenance | - Backup and restore procedures - Upgrades and patch management - Monitoring and troubleshooting |



