Test Prep ACT Test Exam Prep
American College Testing: English, Math, Reading, Science, Writing (Page 27 )

• Minimum
• Maximum
• Average
• Count
• Null/empty values
• Distinct values

• Enable column profile
• Enable details pane
• Show column profile in details pane

• A. IDS attack signatures: Detects suspicious network activity, but is not primarily designed to scan uploaded files for malware.
• C. Load balancer: Distributes traffic among servers and improves availability; it does not inspect files for threats.
• D. WAF: Protects web applications from attacks such as SQL injection and command injection, but its primary role is not malware scanning of uploaded documents.

1. insert con; ? 1
2. Database.setSavepoint(); ? 2
3. update con; ? 3
4. Database.rollback(sp_admin); ? 4

• A: It allows for branching and merging...

• C: It allows multiple engineers to work against the same code and configuration files and manage differences and conflicts.

• B: Build automation and infrastructure provisioning are handled by CI/CD and automation tools, not by version control alone.
• D: User Stories and backlogs are managed by project-management tools.
• E: Version control stores and tracks code, but it does not itself ensure that developers write effective unit tests.

• B — The most significant risks are held by SQ.

• C — SQ should recognise the cars as inventory.

• F — SQ recognises revenue when LM sells a car to a third party.

• A: LM does not hold the most significant risks.
• D: LM does not recognise the cars as inventory.
• E: SQ should not recognise revenue when cars are merely delivered to LM.

• API tool matcher: runs a deterministic normalization command after the API tool returns.
• Write/Edit matcher: checks whether the target path begins with src/api/ and runs the linter.

json 
{ 
  "hooks": { 
    "PostToolUse": [ 
      { 
        "matcher": "api_tool", 
        "hooks": [ 
          { "type": "command", "command": "normalize-to-snake-case" } 
        ] 
      }, 
      { 
        "matcher": "Write|Edit", 
        "hooks": [ 
          { "type": "command", "command": "lint-if-under-src-api" } 
        ] 
      } 
    ] 
  } 
}

1. Append Table1 and Table2 as a new query

1. Select the product column in the appended query.

1. Choose Remove Rows > Remove Duplicates

• Authentication: Verifies who the user is.
• Authorization: Determines what the authenticated user is allowed to access.
• Accounting: Records activity such as login times and resource usage.

• CIA: Confidentiality, integrity, and availability—the three core security goals.
• ACL: Access Control List, which defines permitted or denied traffic or access.
• PEM: A certificate and key encoding format, not the primary function of RADIUS.

• Reporting relationships
• Organizational structures
• Leadership styles
• Team maturity
• Individual and group behavior
• Communication and motivation

• Acquire Project Team: Focuses on obtaining the people needed for the project.
• Develop Project Team: Focuses on improving team skills, relationships, and performance.
• Manage Project Team: Focuses on tracking performance, resolving issues, and managing changes within the team.

• Asynchronous inference is designed for applications that submit individual inference requests, place them in a queue, and retrieve results later. It is useful when requests may take a long time or when traffic is intermittent.
• Batch transform is designed specifically to run inference over an entire large dataset stored in Amazon S3 and produce an output dataset.

• Large dataset/offline processing ? Batch transform
• Large or slow individual requests processed later ? Asynchronous inference

• 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 designed to attract attackers. Legitimate users should not access them, so activity there is a strong indication of unauthorized access.
• DNS sinkholes: Redirect requests for known malicious domains to a controlled internal destination instead of the real attacker infrastructure. Security teams can then identify infected systems making those requests.

• Tokenization: Replaces sensitive data with non-sensitive tokens; it protects data but does not detect intruders.
• CI/CD: Software development and deployment processes.
• Threat modeling: Identifies potential threats before or during system design, rather than detecting successful infiltration.
• Data obfuscation: Makes information harder to understand, but is not an attacker-detection mechanism.

• AB’s own PPE: $100m
• CD’s PPE in its individual accounts: $50m
• Fair value uplift at acquisition: $40m
• Remaining useful life: 10 years
• Extra depreciation each year: $40m ÷ 10 = $4m
• Four years’ extra depreciation to 31 December 20X4: 4 × $4m = $16m
• Remaining fair value uplift: $40m - $16m = $24m

• Suspended an operator who refused to use unsafe equipment.
• Paid another operator a bonus for using it.
• Prioritised short-term productivity over employee safety.

• A — Management is not particularly concerned with managing risks.

• B — Employees will perceive that management does not care about health and safety risks.

• C — The factory’s safety record is likely to be poor.

• state preserves the client’s original context, such as the specific idea URL the user requested.
• The portal sends that value in the OAuth authorization request.
• Salesforce returns it after authorization, allowing the portal to redirect the user to the original idea rather than the Ideas home page.

• 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.

Why this is correct

• Each user authenticates with their own Google account.
• Google manages the user’s SSH key association.
• IAM controls who can access instances.
• Access can be audited by user identity, so security can determine who accessed a VM.
• Granting the role to a Google group avoids managing permissions individually.

Why the others don’t apply

• A: A shared private key is difficult to distribute securely and cannot reliably identify which employee used it.
• B: Manually collecting and deploying keys on every instance is operationally inefficient and complicates auditing.
• D: A project-wide shared key has the same identity and key-management problems as option A. It also does not provide per-user accountability.

• The application stores data on Amazon EBS volumes, so the encryption should be applied directly to those volumes.
• EBS encryption uses AWS-managed cryptographic operations and is designed to provide encryption at rest with minimal performance impact.
• The volumes are created during initial deployment, so they can be configured as encrypted when provisioned.

• B: Moving data to an encrypted S3 bucket changes the storage design and does not encrypt the EBS data the application uses.
• C: A custom encryption algorithm adds application overhead and is unnecessary.
• D: Ephemeral disks are temporary storage and can lose data when instances stop or terminate. Encrypting only the AMI’s root volume does not protect data stored elsewhere.

• Denial-of-service: Prevents users from accessing a service; it does not normally redirect them.
• Social engineering: Manipulates people into taking an action, such as clicking a malicious link, but does not directly alter DNS resolution.
• ARP spoofing: Associates the attacker’s MAC address with another device’s IP address on a local network. It can intercept traffic, but the described website redirection is most specifically DNS poisoning.

• B: Prompt caching reduces cost and latency for repeated content, but cached content still occupies the context window. It does not solve context accumulation.
• C: Switching to a smaller model changes model capacity but does not address the growing context or remove irrelevant data.
• D: Keeping everything indefinitely increases token usage, risks context-window limits, and can distract the model with outdated information.

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.

• Ramen is a Linux worm associated with Red Hat Linux 6.2 and 7.0 systems.
• It spreads by scanning randomly generated IP addresses using tools such as synscan.
• It exploits vulnerable network services, including web-related services, and may leave malicious files or altered web content.
• The tar.gz file is also a clue because it is a common Linux archive/package format.

• Code Red: Primarily targeted Microsoft IIS servers running Windows.
• LoveLetter: Spread mainly through email attachments.
• Nimda: A Windows-based worm that spread through email, web servers, and network shares.

• Set credit quotas for an account or individual virtual warehouses.
• Define monitoring intervals.
• Trigger actions when usage reaches thresholds, such as sending notifications or suspending a warehouse.
• Help control unexpected warehouse spending.

• Account Usage: Provides historical usage and billing data; it does not enforce credit limits.
• Warehouse Limit Parameter: Not the Snowflake object used for account-wide credit controls.
• Credit Consumption Tracker: Not a standard Snowflake object.

1. Which host originated the infection
2. Whether each other host is clean or infected
3. Which firewall or host logs provide evidence of the infection’s movement

• Find the earliest infection-related event. The host associated with that event is the likely origin.
• Follow the timeline: outbound connections from that host may indicate propagation or command-and-control activity.
• A host receiving suspicious traffic is not automatically infected; look for evidence that it executed or initiated malicious activity.
• A firewall log can show traffic paths, but endpoint logs are usually needed to confirm infection.
• Mark a host clean only when the logs show no indicators of compromise or malicious activity.

• A — .gitignore: Controls Git tracking; it does not configure Copilot exclusions.
• B — copilot.ignore: This is not the standard GitHub Copilot Business exclusion mechanism.
• D — Renaming files: Adding _no_copilot has no recognized effect.

• Streams — track change data for tables or views.
• External tables — reference data stored in an external cloud storage location.

• Role — account-level security object.
• Warehouse — account-level compute resource.
• User — account-level security object.
• Share — account-level object used to share data.

• 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.

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

• 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.

• Correct exam answer: A — HKEY_LOCAL_MACHINE
• The relevant location is associated with HKEY_LOCAL_MACHINE\SAM.
• The SAM does not store passwords in plain text; it stores password hashes.

• HKEY_CURRENT_USER contains settings for the currently logged-in user, not the account-password database.
• HKEY_USERS contains user profiles and settings loaded for users.
• HKEY_CURRENT_CONFIGURATION contains hardware/profile configuration information.

• The vulnerability scan identifies a vulnerability.
• The administrator verifies that the vulnerability is not present.
• Therefore, the scan produced a false positive.

• True positive: A vulnerability is reported and genuinely exists.
• False negative: A vulnerability exists, but the scan fails to detect it.
• True negative: No vulnerability exists, and the scan correctly reports no issue.

• C — Some risks cannot be eliminated.

• D — Accepting residual risk does not imply recklessness.

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

• Transport and handling
• Storage and warehousing
• Refrigeration
• Shelf-stacking or replenishment
• Other costs directly attributable to product P

• O File Gateway fornece uma interface de compartilhamento de arquivos usando protocolos como SMB ou NFS.
• Os usuários continuam acessando os arquivos localmente, aproveitando a baixa latência e o cache local.
• Os dados são armazenados de forma durável no Amazon S3, enquanto os arquivos acessados com frequência permanecem em cache no ambiente local.
• Isso amplia a capacidade de armazenamento sem exigir a substituição completa da infraestrutura existente.

• A: Montar buckets S3 diretamente não oferece uma experiência de compartilhamento de arquivos local tão adequada.
• C: Amazon WorkSpaces fornece desktops virtuais, não é uma solução principal de armazenamento compartilhado.
• D: Um volume EBS pertence a uma instância EC2 e não deve ser compartilhado diretamente entre vários usuários como um sistema de arquivos comum.

• 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 flooding.
• NGFW: Filters routed network traffic, while this attack targets Layer 2 switching behavior.

• Self-signed certificate — Causes a certificate trust warning, not incorrect name resolution.
• Nameserver record — A DNS record problem would usually affect multiple users, unless only this computer uses a different DNS server.
• IP helper — Relays certain network services, commonly DHCP, between subnets; it does not normally determine website name resolution.

• Containment policy: controls permitted communication during containment.
• Detection/response configuration: determines when containment is initiated.

• 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.

• la schermata completa della domanda 3;
• i log di ogni host;
• il log del firewall;
• la sezione Explanation, se disponibile.

1. Yes — One account can manage multiple subscriptions

1. No — You cannot merge two subscriptions into one

1. Yes — A resource belongs to only one subscription

• Create procurement-manager-role only in the shared services accounts, where procurement managers operate.
• Attach AWSPrivateMarketplaceAdminFullAccess to that role.
• Procurement managers assume the role when they need to administer Private Marketplace.
• Apply a root-level SCP that explicitly denies Private Marketplace administration to everyone except that role. The SCP acts as a maximum-permission boundary across member accounts.
• Add another SCP denying creation of a role with the same name. Otherwise, another administrator might create a similarly named role and bypass the intended exception.

• Creating the role in every account increases administration and creates more opportunities for misuse.
• A permissions boundary on developer roles does not prevent other administrators from managing Private Marketplace.
• Applying the SCP only to shared services accounts would not protect the rest of the organization.

• 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.

• Tracking who accessed or changed customer information
• Detecting unauthorized activity
• Supporting accountability and investigations
• Providing evidence for compliance and incident response

• Single sign-on not enabled: SSO improves convenience and centralized authentication, but it is not essential for access control.
• Complex passwords not required: This weakens authentication, but other controls may reduce the risk.
• Security baseline not consistently applied: A concern, but it is less specific and less immediately damaging than having no activity records at all.

• Active remediation actions role in Microsoft Defender for Endpoint

• Security Reader role in Azure AD/Entra ID

• Security Administrator is broader than necessary because it grants extensive security-management permissions, violating least privilege.
• Compliance Data Administrator is intended for compliance data management, not Defender for Endpoint remediation approvals.

• The Print Spooler is a Windows service.
• Services can have dependencies—other services that must be running first.
• If a dependency fails, the Print Spooler may repeatedly fail to start.
• In the Services tool, the technician can view the service’s Dependencies tab, start or restart services, and configure startup behavior.

• Processes: Shows currently running applications and processes.
• Startup: Controls which programs launch during Windows startup.
• Performance: Displays resource usage such as CPU, memory, disk, and network activity.

• 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.

• 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.

• Firewalls and routers
• Servers and applications
• Endpoint devices
• Authentication systems
• Cloud services

• Centralized log collection
• Event correlation
• Dashboards and reporting
• Alerting
• Compliance support

• 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.

• 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.