Healthcare CPHQ Exam Prep
Certified Professional in Healthcare Quality (Page 12 )

• The S3 bucket as an origin for static content
• The Application Load Balancer (ALB) as an origin for dynamic content
• An Amazon Route 53 alias record pointing the application domain to CloudFront

Why this works

• Static data: CloudFront caches objects from S3 at edge locations, reducing latency for users worldwide.
• Dynamic data: CloudFront forwards requests that require application processing to the ALB. It can also maintain persistent connections and use the AWS global edge network to improve delivery performance.
• One domain: CloudFront behaviors can route different path patterns to different origins—for example, /static/* to S3 and other paths to the ALB.

Why the other options are incorrect

• Global Accelerator is designed primarily for accelerating traffic to applications with endpoints such as ALBs, not for caching S3 content.
• Using separate domains or splitting static and dynamic traffic adds unnecessary complexity.
• CloudFront already provides the required global edge distribution and caching, so combining it with Global Accelerator is unnecessary here.

• Remote and global work: Access is based on the approved device, not a specific office or geographic location.
• Seamless login: Users may not need to repeatedly enter credentials on a recognized device.
• Limited equipment: It uses devices employees already have rather than requiring separate hardware.

• Geotagging: Restricts access based on location and may prevent legitimate remote work.
• Smart cards: Require issuing and managing additional physical equipment.
• Time-based logins: Limit access by time and do not provide a seamless authentication experience.

• A. Periodically rotate responsibilities: May reduce some risks, but it does not directly detect unauthorized changes.
• B. Review segregation-of-duties conflicts: Identifies incompatible access combinations, not whether a specific data change was unauthorized.
• C. Log changes in an outside application: Logs provide evidence, but someone must review and analyze them. Logging alone does not detect misuse.
• D. Independent review: Directly detects unauthorized changes and reduces the risk that the person making the change can conceal it.

• AB’s own PPE: $100m
• CD’s PPE in its individual accounts: $50m
• Fair value uplift at acquisition: $40m
• Remaining useful life: 10 years
• Extra depreciation each year: $40m ÷ 10 = $4m
• Four years’ extra depreciation to 31 December 20X4: 4 × $4m = $16m
• Remaining fair value uplift: $40m - $16m = $24m

• A — Use getRecordTypeInfosByDeveloperName()

apex 
  Id rtId = Schema.SObjectType.Account 
      .getRecordTypeInfosByDeveloperName() 
      .get('Business_Account') 
      .getRecordTypeId();

• C — Query the RecordType object

apex 
  RecordType rt = [ 
      SELECT Id 
      FROM RecordType 
      WHERE SObjectType = 'Account' 
      AND Name = 'Business Account' 
      LIMIT 1 
  ];

• B: An outbound SOAP call is unnecessary and inefficient.
• D: Hardcoding an ID is not dynamic, and IDs can differ between orgs.

Recommended process

1. Access each switch’s terminal.
2. Use help to identify available commands.
3. Use the MAC table command, such as:

text 
   show mac-address-table

1. Use VLAN information, such as:

text 
   show vlan

1. Use interface information, such as:

text 
   show ip interface brief

1. Record each device’s:

• Constrained VMs: VMs whose workloads are experiencing resource pressure, such as insufficient CPU or memory. They may need additional resources or optimization.
• Overprovisioned VMs: VMs allocated more CPU, memory, or storage than their workloads require. Their resources may be reclaimed or reduced.

• Underprovisioned VMs: This is not the predefined view identified for this report question.
• Zombie VMs: These are typically inactive or unused VMs and are useful for cleanup, but they are not the two views specifically intended here to identify inefficient resource allocation.

• Controlar o fluxo de dados entre S3 e SageMaker;
• Aplicar regras de segurança por meio da VPC;
• Reduzir a exposição dos dados;
• Permitir acesso privado ao bucket do S3.

• Amazon Inspector: avalia vulnerabilidades, mas não gerencia o fluxo de dados.
• Amazon Macie: ajuda a descobrir e proteger dados sensíveis no S3, mas não cria a conexão com o SageMaker.
• S3 Glacier Deep Archive: é uma classe de armazenamento para arquivamento, não uma solução de conectividade.

• Azure Machine Learning Studio is designed to build, test, train, and deploy machine-learning models, including predictive analytics.
• Azure Cosmos DB is a globally distributed NoSQL database. It can store data used by an AI solution, but it is not the primary service for developing and deploying predictive models.
• Therefore, the appropriate recommendation is Azure Machine Learning Studio, as shown in Question 15.

text 
user<TAB>action<TAB>status

text 
user|action|status

• Colons: Although colons commonly appear in log data, they are not a supported delimiter choice in the FX workflow described by this exam question.
• Spaces: Spaces are not treated as a supported delimiter for this extraction method; ordinary text often contains variable spacing.

• Suspended an operator who correctly refused to use unsafe equipment.
• Rewarded another operator for using the equipment despite the broken safety guard.

• A — Management is not particularly concerned with managing risks.

• B — Employees will perceive that management does not care about health and safety risks.

• C — This factory’s safety record is likely to be poor.

1. It examines the source MAC address and learns it on the incoming port.
2. It examines the destination MAC address.
3. If the destination MAC is already in the MAC/CAM table, it forwards the frame only through the associated port.
4. If the destination MAC is unknown, it performs unknown-unicast flooding:

• Deterrent control: The signs warning that people may be filmed can discourage unauthorized or malicious activity. They do not directly stop the action; they influence behavior.
• Detective control: CCTV records or monitors activity so security personnel can identify events or investigate them afterward.

• Preventive: Stops an incident from occurring, such as access control.
• Corrective: Restores systems after an incident.
• Directive: Instructs people to behave in a certain way, such as a security policy.
• Compensating: An alternative control used when the preferred control is not feasible.

• File is shared externally ? Access level

• File is labeled “Internal only” ? Sensitivity label

• An active relationship is used automatically when filters are evaluated. An inactive relationship does not propagate filters unless explicitly activated in DAX, so it would not reliably enforce the required security behavior.
• Apply security filter in both directions allows RLS filters to propagate across the relationship in both directions. This ensures that bidirectional filtering respects the RLS rules applied to both tables.
• Assume referential integrity is unrelated to RLS. It is mainly a DirectQuery optimization that allows Power BI to use an inner join when matching keys are guaranteed to exist.
• The relationship must therefore be active, with security filtering enabled in both directions.

• Streams — track change data for tables or views.
• External tables — reference data stored in an external cloud storage location.

• Role — account-level security object.
• Warehouse — account-level compute resource.
• User — account-level security object.
• Share — account-level object used to share data.

• 10 TB with maximum I/O performance: Use EC2 instance store. It provides very high-throughput, low-latency local storage suitable for temporary video-processing data. The application must tolerate data loss because instance store is ephemeral.
• 300 TB of highly durable media: Use Amazon S3, which is designed for highly durable object storage and can scale to this size.
• 900 TB of inactive archival media: Use S3 Glacier, which provides lower-cost storage for data that is rarely accessed.

• A: Amazon EBS offers high performance but is not the best fit for the question’s “maximum possible I/O” requirement compared with local instance store.
• B: Amazon EFS is durable and shared, but is generally more expensive and less suitable for very large archival storage.
• C: Uses EC2 instance store for performance, but incorrectly uses EFS for the 300-TB durable tier and S3 rather than Glacier for archival data.

• 10 minutes have elapsed, or
• 20 MB of accounting data has accumulated

• Required response and resolution times
• Availability or uptime targets
• Performance standards
• Support obligations
• Remedies or penalties for failing to meet the terms

• SOW (Statement of Work): Defines the project’s scope, tasks, deliverables, and schedule.
• MOA (Memorandum of Agreement): Describes agreed responsibilities between parties, often for a specific activity.
• MOU (Memorandum of Understanding): Records a mutual understanding or intention, usually less formal than a contract.

• Data Category Groups e categorias;
• Visibilidade dessas categorias para perfis ou permission sets.

• B e C: regras de compartilhamento não são o mecanismo apropriado para restringir resultados de busca do Knowledge por divisão.
• D: a role hierarchy não é o mecanismo principal para controlar a visibilidade de categorias do Knowledge. Além disso, a configuração correta é atribuir visibilidade a perfis ou permission sets.

• Asynchronous inference is designed for applications that submit individual inference requests, place them in a queue, and retrieve results later. It is useful when requests may take a long time or when traffic is intermittent.
• Batch transform is designed specifically to run inference over an entire large dataset stored in Amazon S3 and produce an output dataset.

• Large dataset/offline processing ? Batch transform
• Large or slow individual requests processed later ? Asynchronous inference

• Amazon SageMaker — charges apply for compute, storage, and other resources used.
• AWS Config — generally charges for configuration recording and rule evaluations.
• Amazon CloudWatch — has a limited free tier, but many metrics, logs, alarms, and API usage can incur charges.

• SQL injection
• Cross-site scripting (XSS)
• Malicious or malformed web requests
• Some application-layer abuse

• Layer 4 firewall: Filters based mainly on IP addresses, ports, and connections; it lacks detailed web-request inspection.
• NGFW: Provides broader network security, but a WAF is more specialized for protecting web applications.
• UTM: Combines multiple security functions, but it is not necessarily optimized for web-application protection.

• NAT traversal: Helps WAN Edge, vSmart, and vManage devices discover how to reach one another through NAT.
• Initial orchestration: Authenticates and introduces devices when they first join the SD-WAN fabric.
• Connection brokering: Provides information that allows devices to form their required control connections, after which the vBond is generally not in the data path.

• WAN Edge: Forwards user traffic and forms secure tunnels.
• vSmart: Controls the overlay control plane and distributes routes and policies.
• vManage: Provides centralized management, configuration, and monitoring.

• C — Custom buttons display at the top and bottom of a page: Correct. In Salesforce Classic, buttons can appear in the page’s button areas, including the top and bottom of record pages.
• D — Custom buttons are available for Person Accounts: Correct. Person Accounts use the Account object, so Account custom buttons can be available on Person Account layouts.
• E — Custom buttons can reference an external app: Correct. A URL custom button can launch or navigate to an external application or website.

• A: JavaScript custom buttons are a Salesforce Classic feature and are not supported in Lightning Experience. They do not enhance Lightning Experience.
• B: The User object does not generally support custom buttons in the same way standard business objects do.

• Access controls — ensuring only authorized users can access it.
• Encryption — protecting the data if it is intercepted or exposed.

• The CSV contains the external users’ email addresses.
• The bulk invitation feature supports inviting many guest users in one operation.
• Each invited user becomes a guest account in contoso.com.

• Endpoint Manager: manages hosts and sensor-related settings.
• Falcon Investigator: supports investigation and analysis, but does not necessarily grant RTR access.
• Remediation Manager: handles remediation-related actions rather than interactive host access.

• Allow only approved MAC addresses
• Limit the number of learned addresses
• Shut down or restrict a port when a violation occurs

• Load balancer: Distributes application traffic; it does not protect switch MAC tables.
• IPS: May detect some attack traffic, but it is not the direct control for limiting MAC addresses on switch ports.
• NGFW: Filters routed network traffic, while this attack targets Layer 2 switch behavior.

• Packet loss
• Latency
• Jitter
• Call quality by user, device, network, location, or building

• Teams Usage Report: Shows adoption and usage statistics, not detailed call-quality metrics.
• Teams Device Usage Report: Reports which devices are being used and how, but does not provide detailed packet-loss analysis.
• Microsoft Network Testing Companion: Helps assess network readiness before deployment, but it is not the primary tool for analyzing packet loss from actual Teams calls.

1. CALCULATE
2. AND
3. FILTER

DAX 
Transaction Category = 
CALCULATE( 
    MAX('Transaction Size'[Size]), 
    FILTER( 
        'Transaction Size', 
        AND( 
            Sales[Sales Amount] >= 'Transaction Size'[Minimum], 
            Sales[Sales Amount] <= 'Transaction Size'[Maximum] 
        ) 
    ) 
)

• FILTER examines the rows in the Transaction Size table.
• AND ensures the sales amount falls between the category’s minimum and maximum values.
• CALCULATE evaluates the result in the modified filter context and returns the matching category.