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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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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.
Ensuring privacy (e.g., Data Loss Prevention API)
Choosing between ACID, idempotent, eventually consistent requirements
Which export options are available from the Issue Navigation? The following will be discussed here:
Where are all the places you need to look to fully identify what permissions a particular user has?
Leveraging pre-built ML models as a service
Legal compliance (e.g., Health Insurance Portability and Accountability Act (HIPAA), Children's Online Privacy Protection Act (COPPA), FedRAMP, General Data Protection Regulation (GDPR))
Data security (encryption, key management)
What workflow changes can be done through the board by board administrators?
Measuring, monitoring, and troubleshooting machine learning models
Deploying an ML pipeline
What is the relationship between screens, screen schemes and issue type screen schemes?
What are the use cases where it is best to use Project Roles rather than Groups?
Pipeline monitoring (e.g., Stackdriver)
How do combinations of permissions work together to enable specific actions?
What changes can be performed on statuses and transitions?
Impact of dependencies of machine learning models
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?
When is it best to use components, and when is it best to use a custom field instead?
Target Hosts Using Privileged Session Manager
Continuous evaluation
Use of edge compute
Data staging, cataloging, and discovery
ML APIs (e.g., Vision API, Speech API)
Mapping to current and future business requirements
Which project details can be added and changed by Project Administrators?
Conversational experiences (e.g., Dialogflow)
Common sources of error (e.g., assumptions about data)
Which business requirements necessitate the use of separate issue types in a project (e.g. different screens, workflows, etc.)?
Performing data preparation and quality control (e.g., Cloud Dataprep)
Verification and monitoring
Planning, executing, and stress testing data recovery (fault tolerance, rerunning failed jobs, performing retrospective re-analysis)
Choosing the appropriate training and serving infrastructure
Machine learning terminology (e.g., features, labels, models, regression, classification, recommendation, supervised and unsupervised learning, evaluation metrics)
Designing for security and compliance
Distributed vs. single machine
What are the features, uses, limitations/restrictions of workflow changes, especially the Simplified Workflow?
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?
Ensuring flexibility and portability
What are all the various factors that influence whether a field is visible on a screen?
Building and running test suites
Operationalizing machine learning models
How are valid JQL queries written? What operators and arguments are valid for various JQL functions (e.g. membersOf(), StartOfDay(), WAS, CHANGED, etc.)
Defining the CyberArk Privileged Account Security Solution Architecture
What is an Issue Collector and what permissions are needed to configure it?
Assessing, troubleshooting, and improving data representations and data processing infrastructure
Resizing and autoscaling resources
Identity and access management (e.g.,Cloud IAM)
Hardware accelerators (e.g., GPU, TPU)
What types of workflow changes can Project Administrators make if Extended Project Administration is activated?
Who can change the Simplified Workflow? What are the limitations on changes to the Simplified Workflow?
Ensuring scalability and efficiency
Ensuring reliability and fidelity
Ingesting appropriate data
Monitoring Privileged Account Access
Designing for data and application portability (e.g., multi-cloud, data residency requirements)
What things may need to be updated as a result of workflow changes of any kind?
Customizing ML APIs (e.g., AutoML Vision, Auto ML text)
What features are available for Jira Software projects, and to users who have Jira Software application access (as compared to just Jira Core)?
Retraining of machine learning models (Cloud Machine Learning Engine, BigQuery ML, Kubeflow, Spark ML)
What are the uses of Project Category in Jira?
What is the importance of the Browse Projects permission?
Securely Managing the System Architecture
Protection of privacy for our customers
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