How to Prepare for CyberArk CDE Recertification CAU305 Exam
Preparation Guide for CyberArk CDE Recertification CAU305 Exam
Introduction
CyberArk CDE Recertification CAU305 Exam is related to CyberArk CDE recertification.
This program is specially designed for aspirants who are really interested in earning CyberArk stars and can start working as PAM technology experts. This shows knowledge of end to end implementation of CyberArk Privilege Access Security Solution.
Vault Administrators, IT Personnel, CyberArk PAS Consultants usually hold or pursue this certification and you can expect the same job role after completion of this certification.
The CyberArk Certification Program offers a variety of options to those who want recognition for their technical expertise. The CyberArk Certification Program, hosted and proctored by Pearson VUE*, offers multi-level industry certifications covering privileged account security. CyberArk offers certifications designed for various roles and experience, each introducing progressively more advanced and challenging material and exams. You can work up to the level that best aligns with your responsibilities and career ambitions.
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How to book the CAU305 Exam
These are following steps for registering the CyberArk CAU305 exam.
- Step 1: Visit to Pearson VUE Exam Registration
- Step 2: Signup/Login to Pearson VUE account
- Step 3: Search for CyberArk CAU305 Exam Certifications Exam
- Step 4: Select Date, time and confirm with payment method
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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.
Choosing between ACID, idempotent, eventually consistent requirements
Performing data preparation and quality control (e.g., Cloud Dataprep)
When is it best to use components, and when is it best to use a custom field instead?
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 business requirements necessitate the use of separate issue types in a project (e.g. different screens, workflows, etc.)?
Target Hosts Using Privileged Session Manager
Which export options are available from the Issue Navigation? The following will be discussed here:
What are the uses of Project Category in Jira?
What is the relationship between screens, screen schemes and issue type screen schemes?
Hardware accelerators (e.g., GPU, TPU)
What features are available for Jira Software projects, and to users who have Jira Software application access (as compared to just Jira Core)?
Data staging, cataloging, and discovery
What things may need to be updated as a result of workflow changes of any kind?
Ingesting appropriate data
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?
ML APIs (e.g., Vision API, Speech API)
What is the importance of the Browse Projects permission?
Ensuring reliability and fidelity
Retraining of machine learning models (Cloud Machine Learning Engine, BigQuery ML, Kubeflow, Spark ML)
What are the features, uses, limitations/restrictions of workflow changes, especially the Simplified Workflow?
What are the use cases where it is best to use Project Roles rather than Groups?
Identity and access management (e.g.,Cloud IAM)
Building and running test suites
Resizing and autoscaling resources
What types of workflow changes can Project Administrators make if Extended Project Administration is activated?
What changes can be performed on statuses and transitions?
Defining the CyberArk Privileged Account Security Solution Architecture
Leveraging pre-built ML models as a service
Designing for data and application portability (e.g., multi-cloud, data residency requirements)
Customizing ML APIs (e.g., AutoML Vision, Auto ML text)
Use of edge compute
Impact of dependencies of machine learning models
Pipeline monitoring (e.g., Stackdriver)
Designing for security and compliance
How do combinations of permissions work together to enable specific actions?
Verification and monitoring
Ensuring flexibility and portability
Distributed vs. single machine
Deploying an ML pipeline
Where are all the places you need to look to fully identify what permissions a particular user has?
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.)
Machine learning terminology (e.g., features, labels, models, regression, classification, recommendation, supervised and unsupervised learning, evaluation metrics)
Mapping to current and future business requirements
What are all the various factors that influence whether a field is visible on a screen?
Assessing, troubleshooting, and improving data representations and data processing infrastructure
Choosing the appropriate training and serving infrastructure
Conversational experiences (e.g., Dialogflow)
Operationalizing machine learning models
Which project details can be added and changed by Project Administrators?
Who can change a Project Key, and what are the effects on issues in the project?
Ensuring privacy (e.g., Data Loss Prevention API)
What is an Issue Collector and what permissions are needed to configure it?
Securely Managing the System Architecture
Data security (encryption, key management)
Common sources of error (e.g., assumptions about data)
Who can change the Simplified Workflow? What are the limitations on changes to the Simplified Workflow?
What workflow changes can be done through the board by board administrators?
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 scalability and efficiency
Planning, executing, and stress testing data recovery (fault tolerance, rerunning failed jobs, performing retrospective re-analysis)
Monitoring Privileged Account Access
Measuring, monitoring, and troubleshooting machine learning models
