Salesforce Public Sector Solutions Accredited Professional Exam Prep
Public Sector Solutions Accredited Professional (Page 7 )

• Microsoft Teams: Connects to Teams-related data, but it isn’t the primary connector for the Power Apps data tables.
• Personal Analytics: Provides personal productivity insights, not application data.
• SQL Server database: Only applies if the app explicitly uses SQL Server as its data source.
• Dataflows: Used for preparing and centralizing data, not as the normal direct connection to a Power Apps app.

• Conserve public IPv4 addresses: IPv4 addresses are limited, so many internal devices share a smaller number of public addresses through NAT.
• Reduce direct exposure: Private addresses are not directly routable from the public Internet, which helps reduce unsolicited access to internal devices.

• Elicited and documented customer requirements
• Converted them into clear, measurable specifications
• Validated the requirements with the customer
• Used them as the basis for design, quality checks, and acceptance

• A: Requirements should reflect the customer’s needs—not the supplier’s standards.
• B: Iteration review planning does not replace proper requirements collection.
• D: A retrospective occurs after work is completed and is mainly for process improvement, not initial requirements definition.

• Accept: Acknowledge the risk and choose not to take additional action.
• Transfer: Shift the risk or its financial impact to another party, such as through insurance or outsourcing.
• Mitigate: Reduce the likelihood or impact of the risk, such as by implementing security controls.
• Avoid: Eliminate the activity or condition that creates the risk.

• Dynamics 365 Remote Assist — used for remote collaboration and mixed-reality scenarios.
• Dynamics 365 Finance — supports financial and operational management.
• Dynamics 365 Business Central — designed primarily for small and medium-sized businesses’ finance and operations.
• Dynamics 365 for Phones — provides mobile access to Dynamics 365 apps, including Sales, through the mobile Unified Interface.

• Mesh: WAPs communicate wirelessly with one another, often to extend coverage without wired connections. It does not specifically describe centralized WLC management.
• Point-to-point: Connects two specific devices or locations.
• Ad hoc: Wireless devices communicate directly with one another without an access point.

• GPU: A failure may cause no video output, but the PC usually still powers on.
• RAM: Can prevent booting or produce error beeps, but fans and power indicators generally work.
• CPU: Can prevent startup or booting, but it usually does not cause a completely lifeless system.

• prompt: the input or instruction given to the model
• completion: the desired response

json 
{"prompt":"Summarize this customer complaint.","completion":"The customer reports a delayed shipment."}

• B: A .txt file containing CSV-style lines is not automatically a valid fine-tuning dataset. The required structure and format must match the selected Bedrock model.
• C: Provisioned Throughput provides dedicated inference capacity; it does not fine-tune a model.
• D: Journals and textbooks might support domain adaptation or pretraining, but they do not provide the prompt-to-answer examples typically required for supervised fine-tuning.

• The connecting host keeps the private key securely.
• The destination host stores the corresponding public key in its authorized keys.
• Authentication can occur without a person entering credentials each time.
• SSH also provides encrypted communication and host authentication.

• Biometric: Requires a human user and is difficult to automate.
• Smart card: Often requires user interaction or card access.
• Hard-coded password: Unsafe because passwords stored in scripts or applications can be exposed, reused, or difficult to manage securely.

• A. Implement retries with exponential backoff

• C. Reduce the frequency and/or size of requests

• B. Use PutRecord instead of PutRecords — PutRecord sends one record per call and does not remove the underlying throughput limitation. It may increase request overhead.
• D. Use Amazon SNS instead — SNS is not a direct fix for Kinesis shard throttling and changes the required streaming architecture.
• E. Reduce KCL consumers — KCL consumers read from Kinesis; they do not solve producer-side PutRecords throttling.

• Correct answer: A. System characterization

• Why the other options are not correct:

1. Ensure BOMs can include subcomponents ? Configure an entity relationship

1. Report changes made by engineers ? Enable auditing

• Configure entity relationship
• Configure auditing

• Assign a Teams license to a user — Licenses are assigned through the Microsoft 365 admin center, Microsoft Entra ID, or PowerShell.
• Deploy the Teams client — The Teams admin center manages Teams policies and apps, but it is not the primary tool for deploying the desktop client.
• Prevent users from creating teams — Team creation depends on controlling the creation of Microsoft 365 groups, generally configured through Microsoft Entra ID and PowerShell rather than directly in the Teams admin center.

• IPsec: Protects traffic at the network layer, commonly for VPNs; it is not WPA2’s authentication protocol.
• SSL: Protects specific application sessions and has largely been replaced by TLS.
• SSH: Secures remote command-line administration.

• B. Users accessing Salesforce from public Wi-Fi

• C. Users choosing the same password as their Facebook password

• A: 2FA does not protect an already-authenticated, unlocked session if someone accesses an unattended laptop.
• D: Weak password-reset questions are an account-recovery weakness. 2FA primarily strengthens login authentication, not necessarily the security-question reset process.

• A larger question bank with verified answers
• Explanations tied to ISACA exam domains
• Current content aligned with the exam blueprint
• Useful review or progress features

• Amazon S3 — Object storage, not a database.
• Amazon DynamoDB — Fully managed NoSQL key-value and document database.
• Amazon Redshift — Managed data warehouse designed for analytics, not primarily transactional MySQL workloads.

1. Identify every Region containing a replica.
2. Schedule deletion of the KMS key in each Region.
3. Use the minimum KMS waiting period: 7 days.

• A — Use the root user: Root access does not eliminate the need to schedule deletion for every regional replica. The problem is the multi-Region structure, not insufficient administrative permissions.

• C — Update the key policy: The policy already grants kms:* to IAM principals. Changing permissions does not delete the key or its replicas.

• D — Disable the key and schedule deletion in 30 days: Disabling can stop cryptographic use, but 30 days is slower than the permitted 7-day waiting period. It also does not address replicas in other Regions.

• Guiding principles
• Governance
• Service value chain
• Practices
• Continual improvement

• Guiding principles: Recommendations that guide decisions and actions; they do not describe the entire system.
• Four dimensions: Perspectives used to ensure a balanced approach to service management.
• Service relationship: Describes cooperation between a service provider and service consumer, rather than the whole value-creation system.

• Whether a user has a console password
• Password age and last password change
• Whether MFA is enabled
• Access key status
• Access key creation date and last-use information
• Access key age, which helps audit rotation

• IAM Access Analyzer identifies unintended access to resources; it does not report credential age or rotation.
• AWS Artifact provides AWS compliance documents and agreements, not details about your IAM users.
• AWS Audit Manager helps collect evidence for audits, but it is not the direct tool for viewing IAM credential rotation details.

python 
def add_integers(a, b): 
    return a + b

• Uses def to define a function.
• Accepts two parameters, a and b.
• Uses return to send their sum back to the caller.
• Uses indentation to define the function body.

python 
result = add_integers(3, 4) 
result is 7

• Regional leads — Customer Community Plus

• Capacity planners — External Identity

• Customer Community does not provide the enhanced reporting/dashboard access required by regional leads.
• An Identity license is generally for internal Salesforce identity use and does not fit the external capacity-planning users as well as External Identity.

• Workspace: Stores notebooks, libraries, jobs, and other project resources.
• Notebooks: Interactive documents containing code, queries, visualizations, and explanations. Common languages include Python, SQL, Scala, and R.
• Clusters: Groups of virtual machines that run Spark workloads. Clusters can be started, stopped, and automatically scaled.
• Data access: Databricks can read from services such as Azure Data Lake Storage, Azure Blob Storage, and Azure SQL.
• Jobs: Automate notebooks or data-processing workflows on a schedule or in response to events.

• Numerical flexibility: Adjusting the number of employees, such as using temporary, part-time or contract staff.
• Temporal flexibility: Varying when employees work, such as through flexitime, overtime or different working hours.
• Shift system flexibility: Changing work patterns or shift arrangements; it is not specifically about moving between tasks.

• Aggregation happens once, during the scheduled job.
• Dashboard users query a relatively small, precomputed table.
• Repeated users do not trigger expensive aggregations against the detailed sales table.
• Overwriting is appropriate because the summary is rebuilt for the reporting period.

• B: Structured Streaming is unnecessary for data that only needs daily refreshes and adds operational/compute overhead.
• C: A view recomputes the aggregation at query time, increasing latency and query cost.
• D: Delta caching may improve reads but does not replace the need to materialize the expensive aggregation, and cache availability is not the main design guarantee.

• Basic: No technical or architectural guidance.
• Standard: Technical support, but not the required design-assessment service.
• Professional Direct: Provides advisory and architecture guidance.
• Premier: Provides it too, but is unnecessarily expensive for this requirement.

• Import mode loads the data into the Power BI model. Visuals query the in-memory model, which generally provides faster calculation and rendering than DirectQuery.
• Import mode also minimizes online processing because report interactions do not send queries back to the dataflow or SQL Server.
• A daily refresh can load data through the previous day, satisfying the freshness requirement without unnecessary hourly processing.

• DirectQuery keeps querying the data source or dataflow during report use, increasing online processing and potentially slowing visuals.
• Adding a gateway enables connectivity for on-premises sources, but it does not remove the performance disadvantages of DirectQuery.
• An hourly Power Automate refresh is unnecessary when the requirement is only data through the previous day and creates additional processing overhead.

• Looking up accounts, contacts, and opportunities
• Logging calls and updating Salesforce records
• Accessing previously available customer information when temporarily offline

• Salesforce Touch App: Primarily an older tablet-focused experience, not the best general solution for the sales team.
• Custom hybrid app: Unnecessary development when Salesforce provides the required capabilities natively.
• SalesforceA: Intended mainly for Salesforce administrators, not sales representatives.

• Works across SaaS and internal applications: TOTP is widely supported by authentication systems and can be integrated into many applications.
• Device manufacturer agnostic: A hardware token or authenticator application can generate the code without depending on a specific computer or phone manufacturer.
• Offline capability: The code is generated locally using a shared secret and the current time; an internet connection or cellular service is not required.

• Username and password: May work offline but provides weaker authentication and does not meet the intended improvement in security.
• Biometrics: Can depend on device hardware, operating-system support, and enrollment mechanisms.
• SMS verification: Requires cellular connectivity and is vulnerable to threats such as SIM swapping.

Correct choices

• DB1: Azure Data Box Heavy
• Virtual machines: Azure Migrate

Why

• Replication with minimal downtime
• A test migration
• Final cutover after validation

• Issuer: Identifies the party issuing a SAML message—usually the identity provider in the assertion. It is not the Salesforce-specific identifier the architect should provide for differentiating Salesforce.
• Identity Provider Login URL: The endpoint where users are sent to authenticate.
• SAML identity location: Determines where the user identity is found in the SAML assertion, such as the subject or an attribute.

• Amazon DynamoDB — Managed NoSQL database, not PostgreSQL.
• Amazon Athena — Serverless service for querying data in S3; intended for analytics, not OLTP.
• Amazon EMR — Managed cluster platform for big-data frameworks such as Hadoop and Spark.

• Application management: Controls which apps can be installed or used; it does not remove existing data after theft.
• Full-disk encryption: Protects data when the device is powered off or locked, but it may not help if the attacker has already unlocked the device.
• Containerization: Separates corporate data from personal data, but the attacker may still access the corporate container using the stolen credentials.

• MAC flooding: Overwhelms a switch’s MAC address table, potentially causing traffic to be broadcast.
• DNS spoofing: Provides false DNS responses to redirect users.
• ARP poisoning: Sends false ARP information to associate an attacker’s MAC address with another device’s IP address.

• A. IDS attack signatures: An IDS primarily detects suspicious network activity and usually does not provide dedicated file-upload malware scanning. It is generally detective rather than preventive.
• C. Load balancer: Distributes traffic among servers and improves availability; it does not inspect documents for malware.
• D. WAF: Helps block web-application attacks such as SQL injection, command injection, and XSS. Although a WAF may inspect upload requests, malware detection in PDF files is more directly addressed by antivirus or content-scanning functionality.

• Who performed the action
• What action occurred
• When it occurred
• Where it originated
• Whether it succeeded or failed

• Investigating suspicious activity: Important, but investigation depends on having adequate audit data first.
• Storage allocation: Necessary for retention, but storage does not help if the records lack meaningful details.
• Actions after audit failure: Part of operational planning, not the primary assessment of the application’s audit capability.

• A separate scope using a /32 subnet: A /32 identifies one host, but it is not a practical DHCP scope for this purpose.
• A static IP within the DHCP range: This can cause an IP address conflict if DHCP assigns that address to another device.
• SLAAC: Used for automatic IPv6 address configuration, not for assigning a predictable IPv4 address through DHCP.

• Pull: Downloads changes from the central repository and updates the local repository.
• Push: Sends local commits to the central repository.
• Commit: Records local changes in the repository’s history.
• Merge: Combines changes from different branches.
• Clone: Creates a new local copy of a repository.

• vSmart controls the overlay control plane. It uses OMP to exchange routing information, distribute policies, and determine how WAN Edge devices reach one another.
• vManage is the centralized management and configuration platform.
• vBond is the orchestrator. It helps devices authenticate, discover controllers, and traverse NAT during onboarding.
• APIC-EM is not the SD-WAN control-plane component described here.

• Writing with Apache Spark, typically as Delta tables.
• Reading with Apache Spark for processing and analysis.
• Reading with T-SQL through the lakehouse’s automatically generated SQL analytics endpoint.
• Reading with KQL through Fabric’s query capabilities that can access lakehouse data.

• Eventhouse: Optimized for real-time and KQL workloads, but it is not the natural destination for Spark-based writes or general lakehouse storage.
• Datamart: Intended mainly for relational analytics and Power BI; it is not designed for Spark-based data ingestion.
• Warehouse: Primarily T-SQL-based and structured. It does not provide the same native Spark write experience or flexibility for semi-structured data.

• Creating and managing users and roles
• Granting and revoking roles and privileges
• Managing access-control responsibilities

• SYSADMIN: Manages warehouses, databases, schemas, and other objects—not primarily users and roles.
• PUBLIC: Automatically granted to every user; it is not an administrative role.
• ACCOUNTADMIN: Has the highest level of access, but should be reserved for account-level administration and emergencies rather than routine security tasks.

• Digitally signing the software: Verifies authenticity and integrity. It does not hide how the software works.
• Limiting third-party libraries: May reduce dependencies and attack surface, but does not directly prevent reverse engineering.
• Using compile flags: Some compiler options can remove debugging information or optimize code, which may provide limited protection, but this is not the primary technique identified for preventing reverse engineering.

• nomes de pessoas;
• organizações;
• locais;
• datas;
• números de processos;
• leis ou contratos.

• NER = identifica informações específicas e classificáveis.
• Sumarização = reduz um documento e apresenta seus pontos principais.

• Progress iteratively with feedback focuses on making improvements in manageable steps and learning from feedback.
• Optimize and automate focuses on maximizing value from resources and automating suitable activities.
• Start where you are focuses on assessing the current situation and reusing what already exists.

• SQL injection (SQLi): Attacks databases by inserting malicious SQL commands.
• Cross-site scripting (XSS): Injects scripts into web pages viewed by other users.
• Sideloading: Installing an application from outside the official app store. It may install unauthorized apps, but it does not generally unlock the operating system or enable restricted system features.

• Recovery procedures actually work
• Recovery time and recovery point objectives can be met
• Staff understand their responsibilities
• Contact details, dependencies, and technical configurations are accurate
• Gaps or conflicts exist in the plan

• Not version-controlled: Creates a risk of using an outdated copy, but the plan might still be effective.
• Contact information needs updating: This is a specific weakness that can be corrected, often identified during testing.
• Not approved by senior management: Approval is important for authority and resource commitment, but an untested plan presents the most direct risk that recovery will fail when needed.

1. Define Power Platform DLP policies

1. Add custom prompt modifications

1. Conduct adversarial testing

• Prevent connections to malware command-and-control servers
• Identify infected systems making those DNS requests
• Collect information for incident response

• A: Attackers do not normally use sinkholes to map a company’s domain structure.
• B: Redirecting employees from legitimate sites to attacker-owned sites describes malicious DNS manipulation, not a defensive sinkhole.
• D: Attracting attackers away from real resources is more closely associated with a honeypot or deception system.

• R-squared (R²): mede quanto da variação dos valores reais é explicada pelo modelo. É mais usado em regressão, não em classificação.

• Accuracy (acurácia): mede a proporção de previsões corretas em relação ao total. É adequada para a classificação de imagens da questão.

• RMSE (Root Mean Squared Error): mede o tamanho médio dos erros entre valores previstos e reais, penalizando erros maiores. É usado principalmente em regressão.

• Learning rate (taxa de aprendizado): controla o tamanho dos ajustes feitos pelo modelo durante o treinamento. Não é uma métrica de avaliação; é um hiperparâmetro.