Avaya 7230X Exam Prep
Avaya Aura Communication Applications (Page 4 )

• Driver node: Coordinates Spark jobs and runs in the compute environment.
• Worker node: Executes tasks and processes data.
• Databricks Filesystem (DBFS): Provides storage access for data used by compute resources.

• A. IDS attack signatures: An IDS primarily detects suspicious network activity; it is not the best tool for scanning uploaded files.
• C. Load balancer: Improves availability and distributes traffic but does not inspect files for malware.
• D. WAF: Protects web applications against attacks such as SQL injection and command injection. It may inspect HTTP requests, but malware scanning of uploaded PDFs is the key requirement here.

• True positive: The scan reports a vulnerability that really exists.
• False positive: The scan reports a vulnerability that does not exist.
• True negative: The scan correctly reports no vulnerability.
• False negative: The scan fails to detect a vulnerability that is actually present.

• Injection
• Broken access control
• Authentication failures
• Security misconfiguration
• Cross-site scripting

• STIX: A standardized language and format for exchanging threat intelligence.
• OVAL: Used to describe and assess system vulnerabilities and configuration issues.
• Threat intelligence feed: Provides current indicators and intelligence about threats, but not necessarily a structured overview of common application exploitation methods.
• CVE: A catalog of individually identified, publicly disclosed vulnerabilities.

• Honeypots: Deliberately vulnerable or attractive systems designed to lure attackers. Legitimate users should not access them, so activity on a honeypot is a strong indicator of compromise.
• DNS sinkholes: Redirect requests for known malicious domains to a controlled internal system instead of allowing the connection. This can identify infected hosts attempting to contact command-and-control infrastructure.

• Tokenization: Replaces sensitive data with non-sensitive tokens; it protects data but does not primarily detect attackers.
• CI/CD: Automates software development and deployment processes.
• Threat modeling: Identifies potential threats and weaknesses before or during system design.
• Data obfuscation: Makes data harder to understand, but it is not an attacker-detection method.

• Confirming the data has the required columns and data types
• Handling missing or duplicate records
• Converting data into a suitable format
• Selecting or engineering useful features
• Splitting it into training, validation, and test sets

1. Prepare the training data
2. Select an algorithm or configure AutoML
3. Train the model
4. Evaluate its performance
5. Tune hyperparameters if needed
6. Deploy the model

• B — The glass core component is encased in a cladding.

• D — Light is transmitted through the core of the fiber.

• BNC connectors are associated mainly with coaxial copper cabling, not standard fiber connections.
• Data does not pass through the cladding; the cladding helps reflect and contain the light.
• RJ-45 connectors are used with copper Ethernet cabling, not fiber-optic interfaces.

• A. PsFile — Correct: Displays files opened remotely on a system. This reveals shared resources and user activity.
• B. UserInfo — Correct: Gathers information about user accounts, supporting account and privilege enumeration.
• C. PsPasswd — Answer key lists it: This is questionable. PsPasswd is primarily used to change passwords remotely, not enumerate information. The key may classify it broadly as a Windows account-management tool, but it is not a strong enumeration example.
• D. WinSSLMiM — Incorrect: Used for SSL man-in-the-middle activity, not enumeration.

• C — Before update
• D — Before insert

apex 
trigger AccountTrigger on Account (before insert, before update) { 
    for (Account acct : Trigger.new) { 
        acct.Description = 'Updated automatically'; 
    } 
}

• In after insert and after update, Trigger.new records are read-only.
• Use after triggers when you need the record’s final database Id or want to create/update related records.
• Attempting to change a field directly in an after trigger causes a read-only error.

• Build, measure, learn: Create something, assess real feedback or results, and adapt.
• Minimum viable product (MVP): Produce the smallest useful version to test assumptions and reduce uncertainty.
• Fail fast: Test ideas early so that unsuccessful approaches can be identified before significant time or cost is invested.

• Azure Cosmos DB is a globally distributed NoSQL database service. It stores and retrieves application data, but it does not provide the complete environment for building, testing, and deploying predictive analytics models.
• Azure Machine Learning is the appropriate service for this requirement. It supports creating experiments, training and testing models, and deploying them for predictions.
• Azure Machine Learning Studio provides the browser-based interface for these tasks.

• Custom domains are supported.
• It provides dedicated compute instances.
• It offers enough storage for the applications.
• It supports multiple instances with load balancing between them.
• It is less expensive than higher tiers such as Premium.

• Free and Shared use shared compute and have limited storage, so they cannot meet the dedicated-instance requirement.
• Basic provides dedicated compute and custom domains, but the question’s requirement for the broader multi-instance/load-balancing capability is intended to point to Standard.

• Microservices: An application design approach that divides software into small services; it does not specifically reduce the number of operating systems.
• Containerization: Uses isolated containers that share the host OS kernel—best match.
• Virtualization: Creates separate virtual machines, and each typically requires its own guest OS, so it does not minimize OS instances as effectively.
• Infrastructure as code: Automates deployment and management of infrastructure; it does not describe the architecture being used.

• The product is already in production.
• The organization is examining the product’s functions and cost drivers.
• The objective is to reduce cost without reducing perceived value or required quality.

• Kaizen costing focuses on continuous, usually incremental, cost reductions during the manufacturing stage. It is not specifically the systematic examination of a product’s functions.
• Standard costing compares actual costs with predetermined standards; it is a control technique, not a product redesign method.
• Process innovation concerns developing significantly improved production processes, rather than analysing the product’s functions and value.

• The job keeps 31 days of regular restore points. A backup from the week of January 1 is older than 31 days by March 20, so it is no longer expected to remain on the performance tier.
• It is also a weekly GFS full backup, retained for 14 weeks. Therefore, it is still protected and has not been deleted.
• In a Scale-out Backup Repository, older backups can be moved from the performance tier to the capacity tier—typically object storage—according to the configured offload policy.
• The archive tier is not selected because the question’s configuration does not indicate that the backup has been archived there.

• Additional running costs: $800
• Less depreciation: $300

• The $100 reduction in fixed production overhead absorbed is only an accounting reallocation. It does not represent an actual saving in total fixed overhead.

• desktopwidth:i:1280
• desktopheight:i:1024

• Connection information: Controls connection-related settings, not the desktop resolution.
• Scaling plan: Controls when session hosts start, stop, or scale based on demand.
• Session behaviour: Controls behavior such as disconnect or logoff handling.
• Display settings: Specifically controls RDP display properties, making it the appropriate choice.

• 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.

• On VirtualNetworkA: enable Allow gateway transit.
• On VirtualNetworkB: enable Use remote gateways.

• 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.

• Static IP address: Not needed if the workstation already has network connectivity.
• Subnet mask: Incorrect subnetting would usually prevent local communication, including pinging the server.
• Default gateway: Primarily affects communication outside the local network; it does not normally prevent finding an internal domain controller.

• Reconnaissance: Gathering information about the target.
• Weaponization: Creating or combining a malicious payload with a delivery method.
• Delivery: Sending the payload, such as through phishing.
• Exploitation: Triggering a vulnerability or weakness to gain execution or access.

• Tokens: Individual units of text processed by a model, such as words, subwords, or characters.
• Models: Systems that learn patterns and generate predictions or outputs.
• Binaries: Data represented using the binary number system, not semantic representations.

• What information each stakeholder needs
• When and how often it should be communicated
• Which format or channel should be used
• Who is responsible for communicating it

• A: The team should not decide stakeholder communications without first checking the established plan and CEO’s needs.
• B: An executive summary may be appropriate, but choosing a solution before reviewing the plan is premature.
• D: The stakeholder engagement plan addresses how to engage stakeholders, but this is primarily a communication planning issue.

• A is incorrect: Flow Debugger is for debugging Salesforce Flows, not Trust Layer masking.
• B is incomplete/misleading: Requesting audit data may be part of reviewing the results, but collection and storage must first be enabled.
• C is correct: It describes the initial validation step.

• Accept terms of use
• Enter a temporary code or credentials
• Provide basic registration information

• Enterprise authentication — Authenticates organizational users, often with centralized identity services; it is not specifically designed for temporary guest access.
• Ad hoc network — A temporary device-to-device network, not an authentication process.
• WPA3 — A wireless security standard. It protects Wi-Fi access but does not provide the web-based temporary access workflow described here.

• New investment: $536,500
• Resulting NPV: $0

• MTTC: Time required to contain or limit the incident’s impact — best match.
• MTTR: Time required to remediate or recover from the incident; this may include eradication, restoration, and cleanup, which goes beyond merely stopping spread.
• MTTD: How long it takes to discover the incident.
• MTBF: Average time between failures, generally a reliability metric.

• Future costs — Only costs occurring in the future can be affected by the investment decision. Past costs are sunk and irrelevant.
• Incremental costs — These are additional costs caused by choosing the investment. They are relevant because they differ between alternatives.
• Cash flows — Capital investment decisions are based on future cash inflows and outflows, usually discounted to present value.

• Committed costs have already been agreed or incurred and generally cannot be changed by the decision.
• Unavoidable costs will arise regardless of which option is selected, so they do not affect the choice.

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:

• Third-party attestation: Provides independent validation, but is typically periodic and performed by an external party.
• Penetration testing: Simulates attacks to identify exploitable vulnerabilities; it does not primarily track compliance.
• Vulnerability scans: Identify technical weaknesses, but do not provide a detailed review of procedures or compliance activities.

• B — Notify affected business units: Notification should follow an initial determination of scope and impact; otherwise, the organization may communicate incomplete or inaccurate requirements.
• C — Assess noncompliance risk: Risk assessment requires understanding the regulation’s requirements first.
• D — Inform senior management: Management should be informed, but with a clear summary of the regulation’s impact, risks, and recommended actions.

• Employees can work from any location, including remote sites and offices worldwide.
• Login can be relatively seamless after the device is registered.
• It does not require distributing additional physical authentication equipment.

• Geotagging: Identifies location, but location alone is not a strong authentication method and may prevent legitimate remote access.
• Smart cards: Provide strong authentication but require card readers and physical cards, increasing equipment and management requirements.
• Time-based logins: Typically involve one-time codes that users must enter, making the experience less seamless and potentially requiring a token or authenticator app.

• GPS coordinates
• Date and time the image was taken
• Camera or device model
• Exposure settings

• Log data: Records events or activities, such as system or application activity.
• Encrypted data: Information intentionally encoded to prevent unauthorized access.
• Sensitive data: A broad classification for information requiring protection; geolocation may be sensitive, but the technical type stored in the image is metadata.

• Access List: controls whether a client is allowed or denied.
• Connect List: controls which wireless networks/APs a station may connect to.

• Dataset file: Use Import mode. Excel files are imported into Power BI, and the two Sales tables can be combined with Power Query.
• Report file: Use a live connection to the published dataset. This keeps the report separate from the dataset and avoids importing the data again.

• Report file: DirectQuery/live connection
• Dataset file: Import

• Box 1: No — The rule requires user.department to equal Engineering. Engineer does not match, so User1 is not in AU1. Admin1 cannot reset User1’s password.
• Box 2: No — Admin1’s role is scoped to AU1 and cannot manage users outside that AU.
• Box 3: Yes — Admin2 is a Global Administrator and can reset User3’s password.

• WPA3: Secures wireless traffic but does not normally verify whether someone has paid.
• PSK: A shared Wi-Fi password gives access to anyone who knows it; it cannot easily validate individual receipts.
• IEEE 802.1X: Provides user/device authentication, commonly through an authentication server, but is excessive and not designed specifically for a simple receipt-based guest-access workflow.

1. Install a Cassandra-compatible ODBC driver.
2. Configure a data source name (DSN), if required.
3. In Power BI Desktop, select Get Data > ODBC.
4. Choose the configured DSN and connect.

• Microsoft SQL Server database: Connects to SQL Server, not Cassandra.
• OLE DB: Requires a compatible OLE DB provider; this is not the standard choice for Cassandra in Power BI.
• OData: Requires Cassandra data to be exposed through an OData service, which is not the normal direct connection method.

• Three DHCP scopes: Each VLAN has its own IPv4 subnet. DHCP scopes are subnet-specific, so create one scope for:

• Two DHCP relays: DHCP client discovery begins as a broadcast, and broadcasts do not cross routers or VLAN boundaries. Therefore, configure a DHCP relay on the router or Layer 3 switch interface for each client VLAN.

• Input validation: Prevents malicious or malformed input within an application; it does not authenticate a software package.
• Secure cookies: Protect web-session cookies; they do not protect downloadable software.
• Fuzzing: Tests software by supplying unexpected input to find vulnerabilities; it does not verify software integrity.

• Due diligence: Researching and evaluating a third party before entering or continuing a business relationship.
• Internal audit: Evaluates controls within the organization itself.
• Penetration testing: Actively tests systems for exploitable vulnerabilities.
• Attestation: A formal statement or report—such as a SOC 2 report—provided by an independent party about an organization’s controls.

• C — Some risks cannot be eliminated.

• D — Accepting residual risk does not imply recklessness.

• E — Most companies in this industry will say something similar.

Correct reasoning

• Create storage5 as a General-purpose v2 (StorageV2) account.
• Configure Blob object replication from storage5 to an existing compatible storage account.
• The destination must support object replication—typically another StorageV2 or premium block blob account.
• Blob versioning must be enabled on both accounts.
• Blob change feed must be enabled on the source account.
• The accounts must meet Azure’s object-replication requirements, including being in supported regions and having compatible configuration.

• 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.

• The JSON files contain one billion items, so this is a big-data workload.
• PySpark uses Apache Spark’s distributed, parallel processing, allowing the data to be processed across multiple compute nodes.
• It can read and transform data directly from OneLake, helping minimize unnecessary data movement or duplication.
• A Fabric notebook can also support exploration and visualization, as well as Spark-based analytics and anomaly-detection workflows.

• Pandas is primarily in-memory and generally suited to smaller datasets. One billion records would be impractical on a typical single machine.
• A Power BI report with core visuals is appropriate for visualization and sharing, but it is not the best tool for large-scale transformation, parallel processing, or anomaly detection. It would normally consume prepared data rather than perform the entire workload.

• Lead investigator: Coordinates the investigation and directs the response.
• Information security representative: Provides security expertise and helps assess the incident.
• Technical representative: Preserves system evidence, takes forensic backups, and supports technical analysis.
• Legal representative: Advises on legal, regulatory, privacy, and evidence-handling requirements.

• Load balancer: Distributes application traffic; it does not protect switch MAC tables.
• IPS: May detect some attack traffic, but it is not the primary control for switch-port MAC learning.
• NGFW: Protects at network boundaries but does not directly limit MAC addresses learned on access ports.

• User-generated content: precisa ser coletado, filtrado, anonimizado e rotulado.
• Moderation logs: podem conter dados inconsistentes, informações pessoais e decisões que precisam ser revisadas.
• Content moderation guidelines: são regras ou orientações, não dados diretamente utilizáveis para medir o comportamento do modelo.

• Data source: Folder
• Transformation: Remove the Content column (or keep only the file-metadata columns)

Why

• File name
• Extension
• Date modified
• Folder path
• Content — the binary contents of the file