Salesforce NONPROFIT-CLOUD-CONSULTANT Exam Prep
Salesforce Certified Nonprofit Cloud Consultant (Page 18 )

• Use a field on Account to show the aggregated yearly shipments (a Roll-Up Summary).
• A Master-Detail relationship between Shipment and Account is required for Roll-Up Summary to work (and to ensure access is governed by the parent Account).
• OWD and the relationship type determine what users can see. If you want to restrict shipment-level access while still showing a summary on Account, Private OWD on Shipment plus Master-Detail helps, because access to shipments is controlled by the Account record.

• A (Public OWD on Shipment with Process Builder and a Lookup to Account): Not ideal. Public access would expose shipments broadly, and a lookup cannot support a built-in roll-up summary.
• B (Private OWD on Shipment, Roll-Up Summary, Master-Detail to Account): Best answer. Private shipments, but because of Master-Detail, access and the roll-up are tied to the Account. The Account can show the yearly total via a Roll-Up Summary field.
• C (Controlled by Parent on Shipment, Trigger, Master-Detail): Master-Detail is correct, but using a trigger is unnecessary for a straightforward roll-up; roll-ups are the standard, maintainable solution.
• D (Private OWD on Shipment, Trigger, Lookup to Account): More complex and not as efficient; no automatic roll-up, and lookup breaks the ease of summarizing by Account.

• 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.

• A Storage Gateway File Gateway provides an on-premises NFS/SMB file share that's backed by objects in S3. This is exactly what you need to migrate an NFS workload: applications continue using NFS, while the actual data moves to and is stored in S3.
• It can cache frequently accessed data locally for performance, while uploads go to an S3 bucket.
• Why the other options aren’t suitable:

• The user starts in the corporate portal.
• The portal launches the Salesforce resource.
• The IdP sends the SAML response to Salesforce.

• Connected App + OAuth is for OAuth authorization and API/app access, not this SAML-based seamless login scenario.
• SP-initiated SSO would begin when the user first requests the Salesforce resource and Salesforce redirects them to the IdP. That is not the described starting point.

• Correct answer: Power BI dataset

• The scenario says the data model already contains several measures and you want to create a report from the existing data with minimal development. Reusing a published Power BI dataset lets you inherit the existing measures and data model, so you don’t have to recreate them.
• How to do it: In Power BI Desktop, use the connector Power BI datasets (Get Data > Power BI datasets) and connect to the existing dataset, then build visuals using the pre-defined measures.
• Why the other options are less suitable:

Why B works

• AWS KMS keys are Regional resources. A normal customer managed key in Region A cannot be used directly in Region B.
• A customer managed multi-Region KMS key (MRK) has related key replicas in both Regions. The replicas share key material and key ID, although each has a Regional ARN.
• With client-side encryption, the application encrypts the data before storing it in S3. Cross-Region replication then copies already-encrypted objects, so S3 does not need to decrypt and re-encrypt them with a different Regional key.

Why the other choices are weaker

• A and C: SSE-S3 uses Amazon-managed S3 keys, not the required customer managed KMS key.
• D: SSE-KMS can work only if the solution creates and configures the appropriate KMS key or multi-Region key replica in each Region. As written, it says to create a customer managed KMS key in each Region, which implies separate keys—not the same KMS key. Replication also requires additional KMS permissions and destination encryption configuration.

• Incidents & alerts — see how the phishing activity was detected, correlated, and investigated.
• Threat Explorer — search for the malicious messages, recipients, URLs, attachments, and campaign activity.
• Email and collaboration reports — assess how many users or messages were affected.
• Remediation details — verify whether messages were quarantined, removed, or otherwise contained.

• Microsoft 365 admin center — general tenant administration.
• Microsoft Entra admin center — identity and access management.
• Exchange admin center — mail-flow and Exchange configuration, rather than full phishing-incident investigation.

• Equipment and hardware
• Facilities
• Inventory
• Backup media
• Supplies stored at an alternate or remote location

• Personal belongings of staff: Usually not organizational assets.
• DR line-item revenues: Revenue is a financial impact, not a physical asset.
• Cloud-based applications: These are primarily logical or information-processing assets, even though they depend on physical infrastructure.

• Review iteration length: Changing duration does not resolve unclear requirements.
• Limit work in progress: Useful when excessive multitasking is the problem, but it does not directly clarify requirements.
• Review individual performance: The issue is a process and backlog-quality problem, not necessarily an individual performance problem.

• Approval publish: Request approval from a manager of the knowledge base before moving the article into the publish state.
• Instant Publish: Immediately publishes a draft article without requiring an approval.
• Instant Retire: Immediately retires a published article without requiring an approval.
• Retire Knowledge: Moves a knowledge article to the retired state.

• These are the base knowledge workflows that control how articles move between states (Draft, Published, Retired) and whether approvals are required.
• The other options describe different lifecycle actions, but these four cover the standard publish/retire workflows in ServiceNow.

• AWS IoT Greengrass supports local ML inference using models trained in Amazon SageMaker.
• The model and inference code run on the factory’s local server, so processing continues even when internet connectivity is unavailable.
• A Greengrass component can:

• This provides low latency and avoids sending images to AWS for every inference.

• A: Uses AWS-hosted services and therefore depends on internet connectivity. It would fail during an outage.
• C: Snowball Edge is unnecessary for this use case and adds deployment complexity. A local Greengrass server is the intended edge-inference solution.
• D: Amazon Monitron is designed for monitoring industrial equipment health, not analyzing camera images with a custom SageMaker model.

bash 
docker run -it microsoft/azure-cli:0.10.17

• docker run starts an Azure CLI container; it does not automatically connect to the AKS cluster.
• The command does not run kubectl apply.
• The container would need the appropriate Kubernetes tools and AKS credentials.
• The device or container must obtain cluster credentials, typically using an AKS credential command, before running Kubernetes commands.

bash 
az aks get-credentials --resource-group <resource-group> --name <aks-cluster> 
kubectl apply -f myapp.yaml

• Leadership and stakeholder commitment
• Business capability and skills
• Organizational culture
• Availability of resources
• Ability to manage and sustain change
• Impact of the proposed transformation

• How ready the organization is
• Which areas require urgent attention
• How difficult each issue may be to resolve
• Risks that could affect implementation

• A: Places the assessment in Phase B and refers vaguely to creating views; this is not the prescribed technique.
• B: An Implementation Factor Assessment and Deduction Matrix is not the primary TOGAF technique described for business transformation readiness.
• D: A Business Scenario helps identify requirements and stakeholder concerns, but it is not the main technique for assessing organizational readiness.

• Amazon GuardDuty: Detects suspicious activity and threats using security-related data sources; it is not primarily a software vulnerability scanner.
• Amazon Detective: Helps investigate and analyze the root cause of security findings after an event.
• Amazon Cognito: Provides user authentication and authorization for applications.

• 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.

• AWS Audit Manager continuously collects evidence from AWS services and helps assess whether workloads comply with regulatory frameworks and internal policies. It can produce audit-ready reports.
• AWS Config records resource configurations and evaluates them against compliance rules. For example, it can check whether encryption, logging, or access settings meet company requirements.

• Amazon Inspector identifies software vulnerabilities and unintended network exposure, not general policy or regulatory compliance.
• Amazon CloudWatch monitors metrics, logs, and operational events, but is not primarily a compliance assessment service.
• AWS CloudTrail records API activity for auditing and investigation. It supports compliance, but does not itself provide the structured compliance assessment capabilities of Audit Manager and Config.

• 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.

• The correct AAA mapping (per Cisco objectives) is:

• Why the given options aren’t fully correct:

• Quick takeaway: when you configure AAA, you should conceptually map them as:

• Example commands (to reinforce concepts):

• Version control provides a single source of truth for metadata changes and tracks every modification.
• It supports branching and merging, so each feature can be developed in isolation and later merged without overwriting others.
• It allows diffs and conflict resolution, making it easier to manage dependencies across features and ensure a stable release.

• Setup Audit Trail: only logs who/change when something happened; it doesn’t prevent overwriting or manage cross-feature dependencies.
• Change Sets: used to deploy changes between orgs, not to coordinate parallel development or prevent conflicts across ongoing sprints.

• What the dataflow options mean:

• Why C fits best:

• Actual filename: Document.xml.txt
• Explorer displays: Document.xml
• File type: Text Document (.txt)

text 
Document.txt ? Document.xml

• Detect risky sign-ins from unfamiliar or unidentified IP addresses
• Evaluate user or sign-in risk
• Automatically require a password change because of a risky sign-in

• User risk policy: Can require a user to securely change their password when the account may be compromised.
• Sign-in risk policy: Can require MFA or block access based on the risk of a particular sign-in.

• Generates a syslog message
• Shuts down the PoE port
• Places the port into error-disabled (err-disabled) state
• Frees the power allocation

• A device starting to draw power does not necessarily generate a syslog message.
• Monitoring does not pause data traffic while checking power.
• Drawing less than the configured minimum does not automatically mean the device has failed and should be disconnected.

• 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 — SCIM synchronizes changes to user attributes from the identity provider to GitHub.
• B — SCIM deactivates GitHub accounts when users are removed or deactivated in the identity provider.
• D — SCIM automates user provisioning when new users are added to the identity provider.

• C: SCIM does not delete organization repositories.
• E: SCIM does not generate REST API authentication tokens.
• F: SCIM handles identity lifecycle management, not repository permission configuration based on roles.

• Azure Cosmos DB is a globally distributed NoSQL database service. It stores and retrieves application data, but it does not provide the tools needed to build, test, and deploy predictive analytics models.
• Azure Machine Learning—including the historical Azure Machine Learning Studio—is designed for the machine-learning lifecycle:

• Forecasting lets sales leaders predict revenue for upcoming fiscal periods, compare forecasts with targets, and review performance by salesperson or team.
• Opportunity Stages help determine the likelihood that opportunities will close. Each stage can have a probability, which contributes to forecast calculations.

• Sales Quotes: Used to present pricing or product proposals to customers; they do not provide revenue forecasting.
• Opportunity List View: Helps users filter and view opportunities, but it is not the forecasting tool.

• The diagnostic output shows that the protocol is TCP (proto=6) and the session state is 2.
• In FortiGate’s session output, state=2 maps to SYN_SENT. This means the TCP SYN has been sent but the handshake hasn’t completed yet.
• Therefore, the session is not ESTABLISHED, FIN/ACK-related states, or other states; it’s in SYN_SENT.

• Increase/decrease the number of epochs: Changes how long training runs, but does not reuse a pre-trained model.
• Unsupervised learning: Trains from unlabeled data and does not specifically address adapting an existing model.

• MFA verifies a user’s identity using additional authentication factors, such as a phone prompt or security token.
• It helps prevent unauthorized access even if a password is compromised.
• It does not provide secure storage or encryption of credentials used during automated deployment.

• Use one Azure AD directory for the organization.
• Separate divisions with subscriptions and/or resource groups.
• Assign each division’s administrator appropriate Azure role-based access control (RBAC) permissions, scoped to their subscription or resource group.

• Multi-factor authentication
• A secure password change for users whose credentials may be compromised

• administrators — Full access to switch configuration and REST API functions; excessive for this requirement.
• sysadmin — Intended for highly privileged system administration, not basic monitoring.
• helpdesk — More limited and focused on troubleshooting/support functions; it does not match the stated default role and level-1 requirement as directly.

• Correct options: C and D.

• The AWS Cloud Adoption Framework (CAF) security perspective focuses on capabilities to protect information and manage security risk.
• Observability (A) is primarily an operations/monitoring capability, not a core security capability under CAF.
• Incident and problem management (B) is IT service management/operations, not specifically a CAF security capability.
• Incident response (C) is a security-focused capability: detecting, containing, and recovering from security incidents.
• Infrastructure protection (D) involves applying security controls to protect the underlying infrastructure, which fits the security perspective.

• 6-phone boxes: 6x
• 8-phone boxes: 8x

• Data lakes: scalable, low-cost storage for structured, semi-structured, and unstructured data.
• Data warehouses: reliable SQL analytics, governance, and performance features.

• Data lake: Primarily provides flexible, scalable storage but may lack warehouse-style reliability and governance.
• Data warehouse: Strong for structured analytics but less flexible for raw and unstructured data.
• All of these: The individual lake and warehouse do not, by themselves, unify the siloed architecture.

• In Microsoft Entra (Azure AD), admin roles can be scoped to either the entire directory (tenant) or to an Administrative Unit (AU). To assign a role at an AU scope, the user must be a member of that AU.

• Roles in question: Security Administrator and User Administrator can be scoped either to the Directory or to a specific AU.

• User1 is a member of AU1. Therefore, User1 can be assigned either at the AU scope (AU1) or at the Directory scope (global).

• User2 is not a member of AU1. Therefore, User2 cannot be assigned at the AU scope; the valid scope for User2 is only the Directory scope.

• User1: can be assigned at AU1 and at Directory scopes.
• User2: can be assigned only at the Directory scope.

• Secure: uses encryption, such as HTTPS or SFTP.
• Cross-platform: supported by many languages and operating systems.
• Internet-friendly: designed to communicate across networks, usually using standard Internet protocols.

• JSON/REST over HTTPS — widely supported, secure, and Internet-friendly.
• SOAP over HTTPS — also secure and highly cross-platform, though more heavyweight.
• XML over SFTP — secure file-based exchange, but it is not an API-style interface.

• Storage accounts: storage1, storage2, and storage3
• Log Analytics workspace: Analytics3

• Azure Backup reports can send the AzureBackupReports diagnostic log to eligible storage accounts. The storage account’s subscription and region do not have to match the Recovery Services vault, so all three listed storage accounts are valid.
• The Log Analytics workspace must be in the same region as the Recovery Services vault for this configuration. Vault1 and Analytics3 are both in West Europe, making Analytics3 the valid workspace.

• You normally do not create a new sensitive information type for credit card numbers. Microsoft Purview already provides a built-in Credit Card Number sensitive information type.
• The required sequence should generally be:

• On-Demand: You pay by the hour with no long-term commitment. This is ideal for workloads that are infrequent or have highly variable usage. Since this job runs only 24 hours once per year, you pay only for those 24 hours, with no wasted upfront or long-term payments.
• Reserved Instances: Require a 1- or 3-year commitment and pay for capacity whether you use it or not. For a workload that runs just 24 hours a year, you’d be paying for most of the term unused, making it far less cost-efficient.
• Spot Instances: Can be interrupted whenever AWS needs capacity, which is unacceptable for an uninterruptible workload.
• Dedicated Instances: Generally more expensive and aimed at licensing or compliance requirements; not needed for this use case.

• Disabling GPS: Affects location services, not email connectivity.
• Configuring 4G usage only: Does not enable international data access and could prevent connectivity if 4G is unavailable.
• Connecting using a hotspot: Could provide data, but it is not the most direct solution and depends on another network or device.

• State is stored remotely in Terraform Cloud/Enterprise, not as a local file.
• Terraform runs (plan/apply) can be executed on remote infrastructure, with results visible in the remote workspace UI.
• Supports workspace-based organization, state locking, and concurrency control.
• Useful for team collaboration, centralized governance, and auditable logs.

• In your configuration, you use a backend block like backend "remote" { ... }.
• You still run terraform init to configure/migrate to the remote backend.
• After setup, terraform plan/terraform apply may be executed remotely, and the outputs/logs appear in the Terraform Cloud/Enterprise UI rather than (only) in your local terminal.

• Other backends store state remotely but typically do not provide remote execution; with the remote backend you get remote runs and a collaborative UI, not just remote state storage.

• Basic: Self-help only; no technical support or design assessment.
• Developer/Standard: Technical support, but generally not the full proactive architecture guidance required here.
• Professional Direct: Includes proactive guidance and architecture recommendations.
• Premier: Also supports this, but is not the minimum-cost option.

• Wiping securely overwrites the drive so the original data cannot reasonably be recovered. It is generally less expensive than physically destroying the device.
• Recycling could expose the data if the drive is not securely erased first.
• Shredding physically destroys the drive and is effective, but usually more costly and prevents reuse.
• Deletion only removes file references; it is not a secure sanitization method.

• Correct answer: A. Inbound data transfer from the internet

• Why: AWS does not charge for data transferred into AWS from the internet. Inbound data transfer is free, regardless of the amount (in this case, 2 TB). The other options involve data leaving AWS or moving between AWS regions/AZs, which incur costs:

• Residual neural network (ResNet): Primarily used for computer vision tasks such as image classification.
• Support vector machine (SVM): Commonly used for classification and regression, not natural-language query generation.
• WaveNet: Designed mainly for generating or modeling audio and speech.

• Key difference: DirectQuery leaves data in the on-prem SQL Server and queries it live. That means every visual request can trigger online processing on the source, which can be slower and adds load on the on-prem system. In contrast, Import loads data into the Power BI data model, so visuals render from the in-memory engine (faster).

• Why that helps with the requirements:

• Why not A or B: Both rely on live data via DirectQuery, which contradicts the goal to minimize online processing and visuals performance.

• Why not D: It uses Import, but refreshing hourly adds unnecessary processing and complexity when daily refresh already satisfies currency needs.

• Post-Incident Review (A) is the after-action step used to capture lessons learned, identify process gaps, and drive improvements across the incident response lifecycle. This directly supports process maturity and a stronger security posture.
• Incident Analysis (D) focuses on investigating root causes during/after an incident, which is important but more of a diagnostic activity than a standalone baseline improvement to maturity.
• Fast Eradication (B) and Incident Containment (C) are tactical actions aimed at stopping the incident, not on maturing the process.

• Business
• People
• Governance
• Platform
• Security
• Operations

• Cloud financial management
• Portfolio and program management
• Risk management
• Data governance
• Compliance and oversight