Pegasystems PEGAPCSSA85V1 Exam Prep
Pega Certified Senior System Architect (PCSSA) 85V1 (Page 14 )

• 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.

• A. Remove rows where Sales[Status] is Canceled

• E. Remove Sales[Canceled Date]

• B: Removing Sales_Date would remove information users need—the date portion.
• C: Changing Delivery_Time to Integer could alter its meaning or precision and is not necessarily safe.
• D: Splitting the date/time column creates additional columns rather than simply removing unnecessary data.

• 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.

• Disable default accounts: Default or unused accounts may have known usernames or predictable settings, making them targets. They should be disabled, removed, or securely configured.
• Remove unnecessary services: Every running service creates potential vulnerabilities. Removing services the server does not need reduces exploitable entry points.

• Add the server to the asset inventory: Important for asset management, but not a hardening step.
• Document default passwords: Default passwords should be changed or eliminated—not documented for continued use.
• Send server logs to the SIEM: Valuable for monitoring and detection, but generally performed as part of logging/monitoring configuration.
• Join the server to the corporate domain: May be necessary operationally, but does not itself harden the server.

• Shared capacity

• Fabric capacity — F SKUs

• Fabric trial capacity

• Existing Power BI Premium — P SKUs

• A. IDS attack signatures: An IDS mainly detects suspicious network traffic. It is not the best control for scanning uploaded documents.
• C. Load balancer: Distributes traffic among servers and can improve availability, but does not specifically detect malware.
• D. WAF: Protects web applications from attacks such as SQL injection and command injection. It may inspect web requests, but malware scanning of PDF files is not its primary function.

Correct sequence

1. Merge Sales_Region with Sales_Manager using an inner join

1. Merge Region_Manager with Manager using an inner join

1. Merge Sales_Region and Region_Manager using a right join as a new query

• Disabling a compromised account
• Blocking a malicious IP address
• Isolating an endpoint
• Creating or escalating an incident ticket

• Virus signatures: Primarily associated with antivirus or endpoint protection.
• Security agent deployment: Usually handled by endpoint-management or security-agent platforms.
• Vulnerability scanning: Typically performed by vulnerability-management tools.

• Active-active routers: Provide redundant Internet connections/devices. Both can operate, so traffic can fail over or be load-balanced.
• Active-active firewalls: Avoid a single firewall becoming a failure point while maintaining security inspection.
• Load balancers: Distribute requests across multiple web servers. If one server fails, traffic can go to the other.
• Redundant power supplies: A server with separate power supplies should connect to independent power sources or circuits.
• UPS A and UPS B: Provide backup power and redundancy. Ideally, each power supply is connected to a different UPS.
• SONET ring: A ring topology provides alternate paths if a fiber link or segment fails.

• B: Não é preciso implantar o modelo em um endpoint do Amazon SageMaker, pois o Bedrock já oferece a infraestrutura de inferência.
• C: O SageMaker Model Registry é usado para gerenciar modelos no SageMaker, não é requisito para modelos customizados no Bedrock.
• D: Não existe uma etapa geral de “conceder acesso” ao modelo customizado como requisito principal de uso. O ponto essencial é adquirir o Provisioned Throughput.

• Custom domain: miami.weyland.com requires a paid App Service tier; Free and Shared are unsuitable.
• Two instances: Standard supports scaling to multiple instances.
• SSL: Standard includes SSL support.
• 12 GB storage: Basic provides only about 10 GB, so it does not meet the requirement. Standard provides substantially more storage.
• Cost minimization: Standard is the lowest tier among the choices that satisfies all requirements.

• User2 is in Group1, so CA2 applies.
• CA2 targets Office 365.
• CA2 requires MFA OR an app protection policy.
• User2 has no app protection policy, but if User2 successfully completes MFA, the OR condition is satisfied.
• The device being noncompliant does not matter because CA2 does not require device compliance.
• CA1 applies only to Global Administrators. Unless User2 is also a Global Administrator, CA1 does not apply.

• 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.

1. Create Workspace2 with Lakehouse2 — F
2. Migrate the Employee table to Lakehouse2 — E
3. Assign the data engineer the Contributor role for Workspace1 — D

Why

• Sharing Lakehouse1 would not provide the required isolation.
• Viewer access would not allow writing to Customer.
• Giving Contributor access to Workspace2 would expose the sensitive table.

• Unfamiliar locations or IP addresses
• Anonymous or malicious IP addresses
• Leaked credentials
• Unusual sign-in behavior

• 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.

• Training or coaching
• Mentoring
• Additional support or resources
• Targeted performance improvement plans

• A: Recognition may be appropriate, but awards do not address identified gaps.
• C: Rotating schedules does not necessarily improve the specific competencies that are missing.
• D: Assessment results should be handled sensitively, but keeping them entirely private prevents useful feedback and development discussions.

• 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.

• Packet capture: Collects and analyzes network traffic; it does not describe the scan type.
• Privilege escalation: Attempts to gain higher permissions after obtaining access.
• System enumeration: Identifies systems, services, or resources, but is not specifically defined by the lack of credentials.
• Passive scan: Observes traffic without actively probing systems. A vulnerability scan is generally an active assessment.

• A — Capacity: The system must handle all current records and anticipated future records. A system that cannot cope with volume will quickly become ineffective.
• C — Accuracy: Academic records are critical, so the new system must be at least as accurate as the existing system and comparable systems. Poor accuracy could cause serious administrative and reputational problems.
• D — Integration: Linking with the university’s financial systems supports consistency and avoids duplicate data entry, especially for registration, deregistration and fee-related transactions.

• B — Parallel running: This is a useful implementation and risk-control technique, but it is not an essential feature of the system itself. It may also be expensive and time-consuming.
• E — Internet access for all information: This creates significant confidentiality and security risks. External access might be needed for selected services, but unrestricted access to all information is not essential and would be inappropriate for student records.

• A — VARIANT "null" values are not the same as SQL NULL values: True

• B — Frequent, single-row DMLs: False

• C — Validate data before loading into the target table: True

• D — Use staging tables to manage MERGE statements: True

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

• 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.

• 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.

• 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.

• Assign endpoints to a group based on the result of one policy.
• Use that group as the scope of another policy.
• This effectively passes the endpoints from one policy’s processing flow to another.

• Maintain head office control: Transfer pricing generally supports decentralisation rather than direct head-office control.
• Establish centralised decision making: This conflicts with divisional autonomy.
• Develop a top-down culture: Transfer pricing is intended to support empowered divisions and goal congruence, not impose purely top-down management.

• Sustainability
• Performance efficiency
• Reliability

• Amazon EC2 instances — ???????? ?? ?? ??????? CPU, memory ??? instance size ???????? ???????
• AWS Lambda functions — memory configuration ?????????? ???????
• Amazon EBS volumes — volume type ?? size optimize ???? ???????
• ??????? ECS workloads — resource configuration ? cost optimization-?? ???????

• Memory ? compute usage ?????????? ???? custom code ????? ???? development ? maintenance ??????
• Cost allocation tags ???? ????? ??? ?????? ???? ??????? ???; inefficient resource ??????? ?? recommendation ???? ???
• CloudTrail resource ???? ?? API activity ??????, resource utilization ????

• A — Increased call deflection: o KCS disponibiliza conhecimento reutilizável para clientes e agentes, ajudando a resolver dúvidas sem abrir ou continuar chamadas.
• C — Reduced issue resolution time: os representantes reutilizam artigos e soluções já documentadas, acelerando o atendimento.
• E — Optimized use of resources: o conhecimento compartilhado reduz retrabalho e melhora o uso dos recursos da equipe.

• Existing expected ROI: 15%
• New project ROI: 14%
• Cost of capital: 12%

• Project return = 14%
• Cost of capital = 12%
• It earns 2% more than the cost of capital, so it should increase shareholder value.

• Restrict a port to a defined number of MAC addresses
• Use statically assigned or “sticky” MAC addresses
• Shut down or restrict the port when violations occur

• Load balancer: Distributes application traffic; it does not protect switch MAC tables.
• IPS: May detect suspicious network activity, but is not the primary control for limiting switch MAC entries.
• NGFW: Filters traffic at the network boundary; it does not directly prevent MAC table flooding on access switches.

Box 1: No

• configure_azure_monitor() configures Azure Monitor and the OpenTelemetry pipeline.
• LangChain requires its own instrumentation or callback tracer, such as AzureAIOpenTelemetryTracer.
• You must pass the tracer to the LangChain execution configuration so chains, tools, prompts, and model calls become spans in Application Insights.

Box 2: Yes

text 
OTEL_SERVICE_NAME=customer-agent 
OTEL_SERVICE_NAME=invoice-agent

• Identifies which user or department owns the device
• Supports inventory and compliance requirements
• Enables tracking of lost, stolen, retired, or unauthorized devices
• Helps enforce security controls such as mobile-device management and secure configuration

• Customer information must not be revealed ? PII Detection
• Malicious instructions embedded in images/documents must be blocked ? Prompt Shields

• If the question allows multiple selections, choose PII Detection and Prompt Shields.
• If it requires one selection specifically for the image-based threat, choose Prompt Shields.

• Attack simulator — Used to run phishing and other attack simulations for user awareness training.
• Hunting — Used to proactively query security data and investigate potential threats.
• Incidents — Used to investigate and manage related alerts and active security events.

• 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.

• Matching hashes: The software is likely unchanged.
• Different hashes: The software or its contents have been modified.

• Encryption: Protects confidentiality, not primarily integrity.
• Baselines: Document expected configurations and support comparison, but hashing is more directly suited to verifying file integrity.
• Tokenization: Replaces sensitive data with tokens and is unrelated to software tampering.

• Honeypots: Decoy systems or services designed to attract attackers. Legitimate users should not access them, so activity there is a strong indicator of compromise.
• DNS sinkholes: Redirect malicious or suspicious DNS requests to a controlled destination. This can identify infected systems attempting to contact command-and-control infrastructure.

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

• Process Builder: Automates actions based on record changes; it does not create interactive user forms.
• Approval Process: Routes records for approval and captures approval decisions.
• Outbound Message: Sends information to an external system; it does not provide a user interface.

• Sales processes: Define the available Opportunity stages for each team.
• Record types: Connect each team to its appropriate sales process and page layout.
• Page layouts: Control which fields and related sections each team sees.

• Solar market team 1
• Solar market team 2
• Installation Services team

• One sales process: Cannot provide different Opportunity stages for each team.
• One page layout: Cannot provide different field arrangements or fields by team.
• Three page layouts alone: Page layouts control fields, but not the available stages.

• 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.

• Data owners: Decide who should have access and approve the access rules.
• Business process owners: May help define business requirements, but normally do not enforce technical permissions.
• Security steering committee: Provides governance and direction; it does not manage individual access rights.
• Security administrators: Apply and enforce the approved access controls.

• Microsoft manages the physical datacenter, hardware, and virtualization.
• You manage the virtual machine’s operating system, installed software, configuration, and data.
• You choose the VM size, storage, networking, and scaling options.

• SaaS: You consume a complete application managed by the provider, such as Microsoft 365.
• PaaS: You deploy applications without managing the underlying operating system or VM infrastructure, such as Azure App Service.

• Record changes — a flow can start when a record is updated or otherwise changes.
• Schedules — a flow can run at a specified date/time or on a schedule.
• Record inserts — a flow can start when a new record is created.

• Subflows are reusable flow components called by another flow; they are not normally trigger types.
• Record views do not generally initiate a Flow Designer flow.

• Power BI dataset — Reuses the existing tables, relationships, and measures. You mainly create new visualizations.
• SharePoint folder — Connects to the source files, but you would need to rebuild the model and measures.
• Power BI dataflows — Primarily provide reusable data preparation; they do not automatically provide the existing report’s measures and model.
• Excel workbook — Requires reconnecting to and modeling the source data again.

• Scale out during the hours when customer traffic is high.
• Scale in during low-demand periods, reducing instance-hours and cost.
• Use scaling policies based on metrics such as CPU utilization or request count.

• Multiple Availability Zones: Improves availability and fault tolerance, but does not automatically reduce cost.
• Placement group: Helps with specialized performance or low-latency requirements, not cost optimization.
• Private subnets: Improve network security, but do not automatically adjust capacity or reduce EC2 usage costs.

• 2018-12-31 — the date
• 08:59 — the time

• Changing the original column to Date may fail because it still contains the text at and a time.
• Extracting the last 11 characters does not isolate the date.
• Extracting the first 11 characters gets the date plus a space, but the option does not specify changing the result to the Date type.

• QuickVisualize is used to create and render a Power BI report from a DataFrame.
• The typical pattern is:

python 
PBI_visualize = QuickVisualize( 
    get_dataset_config(df), 
    auth=device_auth 
) 


PBI_visualize

• get_dataset_config(df) prepares the dataset configuration.
• auth=device_auth supplies authentication for the Power BI connection.
• Evaluating PBI_visualize renders the report in the notebook.

• Box 1: No
• Box 2: Yes
• Box 3: Yes

• Orders contains order-level information, such as the order date.
• Order Line Items contains the products, quantities, and line amounts associated with each order.
• Merging them on the order key, such as OrderID, places the order date alongside each line item. This allows you to calculate total order value and analyze it over time.
• Product attributes can remain in the Products table and be related to the resulting line-item table through ProductID.

• Merging line items with products addresses product attributes but does not first provide the order-level date and value needed for time analysis.
• DAX calculated columns or lists add unnecessary model complexity.
• Calculating order counts is not the first requirement and does not combine the required order and line-item data.