Google Google Cloud Data Engineer Professional Exam Prep
Google Cloud Data Engineer Professional (Page 20 )

• Accept: Acknowledging the risk without taking additional action.
• Transfer: Moving the risk’s financial impact to a third party, such as an insurer.
• Mitigate: Reducing the likelihood or impact through controls, such as patching or employee training.
• Avoid: Eliminating the activity that creates the risk.

• 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.

• 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.

• Customers may boycott V’s products.
• Supermarket customers may stop buying from V.
• Investors may view V as having higher legal, ethical and reputational risk.
• V could face fines, lawsuits, contract losses and higher costs.
• Expected future profits may fall.

• Route table: Controls how traffic is routed within a VPC; it does not use the AWS worldwide network to accelerate internet traffic.
• AWS Transit Gateway: Connects multiple VPCs and on-premises networks through a central gateway, but it is not primarily an internet traffic acceleration service.
• Amazon VPC: Provides isolated virtual networking in AWS, but it does not itself accelerate traffic globally.

• B. Versioned configuration files — Infrastructure is defined in machine-readable files and tracked in version control, allowing repeatable provisioning and change history.
• D. Docker files — Assuming “Doctor files” is a typo for Dockerfiles, a Dockerfile declaratively defines how to build a container image and is commonly considered infrastructure/configuration as code.

• A. Cloned virtual machine images — These are prebuilt infrastructure artifacts, but cloning an image is not itself a code-based infrastructure definition.
• C. Change management database records — A CMDB records information about infrastructure; it does not define or provision that infrastructure.

• Low: Applies system, tenant, and user-based suppressions. Activity from locations commonly used by that user is more likely to be suppressed.
• Medium: Applies system and user suppressions.
• High: Applies only system suppressions, so more unusual-location activity generates alerts.

• MFA adds an additional authentication factor, such as a phone notification or verification code.
• It helps prevent unauthorized sign-ins, even if a password is compromised.
• It does not encrypt, store, or protect credentials used by deployment processes.

• miami.weyland.com requires a custom domain, which is not available in the Free tier.
• Two instances require a tier that supports scaling out. Standard supports multiple instances.
• SSL support is available in Standard.
• 12 GB of storage exceeds the storage limit of the Basic tier in the older Azure pricing model used by this question.
• Standard provides sufficient storage and features while being cheaper than higher tiers—though higher tiers are not listed here.

• Free/Shared: insufficient features for custom domains, SSL, and multiple instances.
• Basic: supports some production features, but its storage capacity is insufficient for the required 12 GB.

• 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.

• 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.

sql 
ALTER TABLE dbo.DimCustomer 
ADD CONSTRAINT PK_DimCustomer 
PRIMARY KEY NONCLUSTERED (CustomerKey) 
NOT ENFORCED;

1. ALTER TABLE dbo.DimCustomer
2. ADD CONSTRAINT PK_DimCustomer PRIMARY KEY NONCLUSTERED (CustomerKey)
3. NOT ENFORCED

• 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.

Step 1: Calculate the rights issue price

Step 2: Calculate the number of new shares

Step 3: Calculate the value after the issue and project

• Rights issue proceeds: $21.6m
• Project NPV: $5m

Step 4: Calculate the theoretical ex-rights price

• 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

• 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.

• Deterrent control: The signs warn people they may be filmed. This can discourage unauthorized activity because individuals know surveillance is present.
• Detective control: CCTV monitors and records activity, helping identify or investigate incidents after—or while—they occur.

• Preventive: Stops an incident from occurring; CCTV generally does not physically prevent access.
• Corrective: Restores systems after an incident.
• Directive: Tells people what they must do, such as a security policy.
• Compensating: An alternative control used when the preferred control cannot be implemented.

• A — Improved management of storage space: Correct.

• B — Improved supplier relationships: Correct.

• C — Improved pricing decisions: Correct.

• D — Non-product-specific costs must be apportioned: Incorrect.

• E — Profitability of each customer group: Incorrect.

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

• Sustainability
• Performance efficiency
• Reliability

• Help the team identify the root causes of delays.
• Empower the team to improve its workflow and practices.
• Facilitate removal of impediments.
• Avoid directing the team toward a solution without its involvement.
• Protect quality and sustainable delivery rather than simply accelerating everything.

• A: An impediment log may help, but merely recording problems does not empower the team to solve them.
• B: Directing the team to solutions conflicts with self-management.
• C: Adding impediments to the product backlog may incorrectly treat internal obstacles as product features and delays their resolution.

• C. Case after-insert trigger that publishes a Platform Event

• D. Custom Apex controller that publishes a Platform Event

• A. Trigger with a callout: Salesforce triggers should not make direct synchronous callouts, and this tightly couples transaction processing to the external system.
• B. Workflow Rule with Outbound Message: This can react to record changes, but it cannot reliably capture a user clicking a menu item. It also does not provide the same flexible event-driven model as Platform Events.

• A is correct: It establishes the revised dates and identifies the effect on the critical path.
• B is premature: Stakeholders should be informed after the impact has been assessed and the updated schedule is understood.
• C is not automatically appropriate: Fast-tracking may introduce additional risk and should be considered only after analyzing schedule options.
• D is premature: Adding resources may not resolve a dependency and could increase costs without addressing the actual constraint.

• Extracted text and images
• Page numbers and bounding polygons for citation or grounding
• Structured tables, including tables that continue across multiple pages
• Document structure such as sections and figures

• Document Extraction: Extracts basic text and images, but does not provide the full layout and structural metadata required here.
• Azure Content Understanding in Foundry Tools: A broader content-analysis service, not the single built-in Azure AI Search skill expected by this question.
• GenAI Prompt: Can transform or interpret content but does not inherently produce reliable document geometry and page-level polygons.

• Regression predicts continuous numeric outcomes, such as house price, temperature, or sales amount.
• Linear regression assumes the target can be estimated from a linear relationship between the input features and the target.
• In Azure Machine Learning, you use a labeled dataset containing:

• Classification predicts a category or class, such as “spam” or “not spam.”
• Clustering groups similar records without a known label; it is an unsupervised learning technique.

• Self-signed certificate: Causes a browser security warning, not incorrect name resolution.
• Nameserver record: A DNS problem would typically affect multiple users, not just one workstation.
• IP helper: Relays services such as DHCP across network segments; it does not resolve website names.

• 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

DAX 
Blue Sales = 
CALCULATE( 
    [Total Sales], 
    KEEPFILTERS('Product'[Color] = "Blue") 
)

• CALCULATE evaluates [Total Sales] after applying an additional filter.
• 'Product'[Color] = "Blue" restricts the calculation to blue products.
• KEEPFILTERS ensures the existing filter context is preserved. For example, filters for year, region, or customer remain active. If Color is already filtered, the blue condition is applied as an intersection rather than replacing the existing filter.
• Avoid ALL, because it removes filters and would not maintain the existing context.

• Filtering harmful or inappropriate content
• Blocking specified topics
• Detecting and masking sensitive information
• Enforcing content policies suitable for children

• Amazon Rekognition analyzes images and videos; it does not control text generated by a language model.
• Amazon Bedrock playgrounds are for testing models and prompts, not enforcing production safety policies.
• Agents for Amazon Bedrock help models complete tasks and use tools; they do not primarily provide content-safety controls.

• Deterrent control: The signs warning people they may be filmed discourage unauthorized or malicious behavior. They may prevent incidents by influencing behavior, but their primary purpose is to deter.
• Detective control: The CCTV system monitors and records activity so security personnel can identify suspicious or unauthorized actions.

• Preventive: Blocks or prevents an incident, such as a lock or access-control system.
• Corrective: Fixes or restores systems after an incident.
• Directive: Tells people what they must do, typically through policies or procedures.
• Compensating: Provides an alternative control when the preferred control cannot be used.

• Virus signatures: Associated primarily with antivirus or antimalware tools.
• Security agent deployment: Usually handled by endpoint-management or endpoint-detection-and-response tools.
• Vulnerability scanning: Performed by vulnerability-management or vulnerability-scanning tools.

• Verifies the sender’s identity using their private key.
• Confirms the transaction was not altered after signing.
• Provides evidence that the signer approved or originated the transaction.

• Digital certificates: Bind an identity to a public key, but do not themselves prove that a specific transaction was signed.
• Encrypted passwords: Protect confidentiality or authentication, but generally do not provide transaction-level nonrepudiation.
• One-time passwords: Authenticate a user for a session or transaction, but usually do not provide durable proof of who authorized the electronic record.

• Maximum response and resolution times
• Expected uptime or availability
• Performance requirements
• Escalation procedures
• Consequences for failing to meet requirements

• SOW: Defines a project’s scope, tasks, deliverables, and schedule.
• MOA: Documents specific responsibilities agreed upon by two parties.
• MOU: Records a general understanding or intent to cooperate.

• A. IDS attack signatures: An IDS primarily detects suspicious network activity; it is not the best control for scanning uploaded documents for malware.
• C. Load balancer: Distributes traffic among servers and improves availability, but does not inspect files for malware.
• D. WAF: Protects web applications against attacks such as SQL injection and command injection. It may help secure the upload function, but malware scanning is the key requirement here.

• Complex inputs: Queueable jobs can accept objects such as Map<Id, Project__c> and List<Account> through the class constructor.
• Long-running callouts: Implement Database.AllowsCallouts in the Queueable class.
• Confirmation/status: System.enqueueJob() returns an AsyncApexJob ID, which can be used to query job status and determine whether execution completed successfully.

apex 
public class ProjectQueueable 
    implements Queueable, Database.AllowsCallouts { 


    private Map<Id, Project__c> projects; 
    private List<Account> accounts; 


    public ProjectQueueable( 
        Map<Id, Project__c> projects, 
        List<Account> accounts 
    ) { 
        this.projects = projects; 
        this.accounts = accounts; 
    } 


    public void execute(QueueableContext context) { 
        // Perform the callout 
    } 
}

• @future(callout=true) supports callouts, but future methods accept only primitive values or collections of primitives—not complex sObjects or maps of sObjects.
• Database.AllowsCallouts
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