Salesforce CRT-211 Exam Prep
Certification Preparation for Advanced Administrator (Page 30 )

• ?? ?? ?? ??
• ?? NFS ?? SMB ?? ??
• ?? ???? ???
• ?? IP ??? ???? ?? ???
• ??? ?? ???? ?????

• B: ????? NFS ? Snowball Edge? ?? ?? ? AWS? ?? ? S3
• D: ????? NFS ? ????/Direct Connect ? File Gateway ? S3

• A: CEO-sponsored formal policy — demonstrates executive support, but sponsorship at one point in time may not sustain commitment.
• B: Security awareness training — primarily improves employee behavior, not senior management commitment.
• C: Periodic alignment reviews — ongoing reviews show that security remains relevant, supports business priorities, and uses resources appropriately.
• D: Senior management signoff on the strategy — useful for governance and accountability, but signoff is generally a one-time event.

• Insert is used when you are creating a new record. It saves the record to the table and then leaves the form.
• Update is used when editing an existing record. It saves the modifications and then leaves the form.

• MFA: Protects sign-in and authentication.
• Azure Key Vault: Protects deployment secrets and credentials.
• Answer: No (B).

• 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.

• Training data for potential bias before model training
• Trained models for bias in predictions
• Model features to help explain how they influence predictions

• A: RAG workflows are typically built using services such as Amazon Bedrock, knowledge bases, and data sources.
• B: Monitoring model quality in production is primarily associated with SageMaker Model Monitor.
• C: Documenting model details is handled by capabilities such as SageMaker Model Cards.

• The load balancer provides the listener’s frontend IP address.
• The active SQL Server node must also respond to that same listener IP.
• Enabling Floating IP allows the listener IP to be preserved and handled correctly by the active replica.
• Without it, SQL connections may be sent to a node that cannot correctly claim the listener address.

• A health probe for the SQL Server port
• A load-balancing rule using the listener port
• Floating IP enabled on that rule

• Namespace: The namespace associated with the code where the checkpoint was set.
• Time: When the checkpoint was captured or executed.

• Exception: Exceptions are viewed through debug logs or execution results, not as the primary Checkpoints tab information.
• Debug Statement: System.debug() output belongs in the Logs tab. A checkpoint captures program state, such as variables and their values, at a specific point in execution.

• terraform init is normally required first, especially for a new or changed working directory. It installs providers/modules and configures the backend.
• terraform plan previews the proposed changes.
• terraform apply applies those changes. It also creates a plan internally if you have not supplied a saved plan.

text 
terraform init 
terraform validate       # optional but recommended 
terraform plan 
terraform apply

• Azure DevOps Analytics views are accessed through the Power BI Azure DevOps (Boards only) connector.
• This connector authenticates directly to Azure DevOps Services and lets you select an Analytics view.
• Analytics views allow filtering and shaping data in the cloud before Power BI loads it.
• Azure DevOps Server (Boards only) is for an on-premises Azure DevOps Server instance, not Azure DevOps cloud.
• A generic OData Feed connection can access OData endpoints, but it is not the purpose-built connector for Azure DevOps Analytics views.
• “OData queries” describes the underlying technology or query approach, not the most appropriate Azure DevOps connector choice here.

• 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

• 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.

• A static IP gives the surveillance system a predictable local address, so users can reliably reach it on the LAN.
• However, a static IP does not block internet-based login attempts. If the router exposes the device through port forwarding, attackers could still reach it.
• Port mapping normally exposes an internal service externally, so A is a poor choice as written.
• Subnetting alone also does not block traffic; it would require routing/firewall rules.

• Reconnaissance: Gathering information about the target.
• Weaponization: Creating or combining a malicious payload with a delivery method.
• Delivery: Sending the payload, such as through phishing.
• Exploitation: Triggering a vulnerability or weakness to gain execution or access.

• B — The glass core component is encased in a cladding.

• D — Light is transmitted through the core of the fiber.

• BNC connectors are associated mainly with coaxial copper cabling, not standard fiber connections.
• Data does not pass through the cladding; the cladding helps reflect and contain the light.
• RJ-45 connectors are used with copper Ethernet cabling, not fiber-optic interfaces.

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.

• Default route: 0.0.0.0/0; used only when no more specific route exists.
• Network route: A route covering the destination, such as 10.10.13.0/24.
• Host route: An exact 10.10.13.10/32 entry in the routing table.
• Floating static route: A backup static route with a higher administrative distance.

• 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.

• File hashes
• Strings and metadata
• Binary or code structure
• Known malicious patterns
• Embedded indicators or signatures

• Sandbox: Executes the file in an isolated environment; useful for observing behavior, but usually slower.
• Network traffic analysis: Examines communications generated by a system or application, not the file itself.
• Package monitoring: Tracks software packages or installations and is not the primary method for examining malware signatures.

• Compute: Not used; no virtual warehouse is required.
• Data Storage: Not scanned again.
• Metadata: May help Snowflake manage and validate cached results, but it is not the Snowflake architectural layer identified as serving the request.
• Cloud Services: Handles query coordination, metadata services, authentication, and result-cache access.

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

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

• Fine-tuning requires a properly formatted training dataset.
• For classification or instruction-style fine-tuning, examples are supplied in JSONL format.
• Each line represents one training example, typically containing the input prompt and the desired completion or label.
• The file must then be uploaded or made available to the Microsoft Foundry fine-tuning workflow.

• A: Prompt Flow is useful for prompt experimentation, but it is not required to start fine-tuning.
• B: You do not need to deploy the base model to an online endpoint before fine-tuning.
• C: Tracing supports observability and evaluation, but it does not prepare the fine-tuning job or dataset.

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

• 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.

• 25 — Traditional SMTP server-to-server mail delivery; often restricted and not the usual client submission port.
• 110 — POP3, used for retrieving email; normally unencrypted.
• 143 — IMAP, used for retrieving and synchronizing email; normally unencrypted.

• A is valid:

apex 
  for (Account theAccount : AccountList) { 
      // process theAccount 
  }

• D is conceptually valid, using an index:

apex 
  for (Integer i = 0; i < AccountList.size(); i++) { 
      Account theAccount = AccountList[i]; 
  }

• B is invalid because for(AccountList) is not valid loop syntax.
• C is invalid because each item is an Account, not a List.

• Reduce the training data: Usually makes overfitting worse.
• Add hyperparameters: Hyperparameters already control training; simply adding them does not solve the problem. Proper tuning could help, but that is not what the option states.
• Increase training time: More training can worsen overfitting if the model is already memorizing the training data.

• Azure Cosmos DB is a globally distributed NoSQL database service. It stores and retrieves application data, but it does not provide the complete environment for building, testing, and deploying predictive analytics models.
• Azure Machine Learning is the appropriate service for this requirement. It supports creating experiments, training and testing models, and deploying them for predictions.
• Azure Machine Learning Studio provides the browser-based interface for these tasks.

• Labels control access and protection, not blanket exclusion.
• If the user has permission to open a labeled file—especially if the label allows authenticated users to view it—Copilot can use that file in a summary.
• If the label applies encryption and the user lacks the required usage rights, Copilot should not use the file or reveal its contents.
• Copilot honors the user’s existing permissions, so it should not expose labeled content to an unauthorized user.

• Build, measure, learn: Create something, assess real feedback or results, and adapt.
• Minimum viable product (MVP): Produce the smallest useful version to test assumptions and reduce uncertainty.
• Fail fast: Test ideas early so that unsuccessful approaches can be identified before significant time or cost is invested.

• Domínios personalizados.
• Armazenamento suficiente.
• Instâncias dedicadas.
• Balanceamento de carga.
• Menor custo entre os planos que atendem a tudo.

• Sales revenue is affected because internal sales are recorded at the transfer price.
• Operating profit is affected because revenue changes while costs may remain unchanged.
• Return on investment (ROI) is affected because ROI depends on operating profit and the division’s investment.
• Cost of components purchased is not affected by the transfer price. These are costs incurred when buying components from external suppliers, not the internal price charged for the division’s output.

• 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.

• Espionage: Stealing information for intelligence or competitive purposes.
• Data exfiltration: Unauthorized removal or transfer of data.
• Nation-state attack: An attack sponsored or conducted by a government.
• Shadow IT: Unapproved technology or methods used to access organizational resources.

• Relationship cardinality:

• Filter direction:

• Active versus inactive relationships: only active relationships automatically propagate filters.
• Blank or unmatched values: a fact-table value without a matching dimension row can create the model’s blank/unknown member.
• Uniqueness: the “one” side must contain unique values; duplicate keys generally belong on the “many” side.

• Actions that call external APIs
• Subflows
• Connection and credential aliases
• Supporting integration logic

• Action — A reusable operation within a flow, such as “Create a record” or “Send email.”
• Connection — Defines how ServiceNow authenticates and communicates with an external system.
• Integration step — A general flow step, not the name for the packaged integration.

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

• The message came from the claimed sender (authentication)
• The message was not altered (integrity)
• The sender cannot easily deny sending it (non-repudiation)

• Attackers can send unsigned phishing emails.
• Attackers may compromise a legitimate account and send signed malicious emails.
• Users may still be tricked by a validly signed message.

• netstat -tuln can show listening TCP ports.
• If the web service is not listening, or is bound only to 127.0.0.1, remote browsers cannot connect even though the server responds to ping.

• traceroute: Tests the path to the server, but ping already confirms basic reachability.
• tcpdump: Useful for detailed packet analysis, but it is more appropriate after checking whether a service is listening.
• arp: Helps troubleshoot local IP-to-MAC resolution, not an application-layer web connection.

• Espionage: Stealing confidential information, often for a competitor or government.
• Data exfiltration: Unauthorized transfer of data outside the organization. This could occur, but the question focuses on using unapproved access methods.
• Nation-state attack: An attack sponsored or conducted by a government.
• Shadow IT: Employees using technology or access methods outside the organization’s approved security controls.

• Security controls
• Processes and procedures
• Compliance evidence
• Performance against contractual requirements

• Service-level agreement (SLA): Defines expected service performance, such as uptime and response times.
• Memorandum of agreement (MOA): Documents a general agreement between parties, but does not necessarily provide audit rights.
• Supply chain analysis: Identifies risks across suppliers and dependencies, but is not a contractual mechanism for reviewing vendor controls.

1. Discovery tries the SSH probe first.
2. SSH fails.
3. Discovery tries SNMP, which succeeds.
4. Discovery records SNMP as the preferred service for that IP.
5. Future discoveries try SNMP first.

• Classification identifies the type of device, such as a server, router, or printer.
• Credential affinity remembers which credentials work for a device.
• MID Server affinity associates a device or network with a particular MID Server.
• IP service affinity specifically controls the preferred discovery protocol or service.

• Enforce organizational rules, such as allowed regions or required tags
• Audit resources for compliance
• Deny noncompliant deployments
• Aggregate compliance results across subscriptions

• Red team: Offensive security; attempts exploitation and simulates attackers.
• Blue team: Defensive security; monitors, detects, and responds to attacks.
• Purple team: Combines red- and blue-team activities to improve defenses, but is not the best direct answer here.
• White team: Usually oversees or coordinates an exercise, including rules of engagement and scope.

• Advanced Persistent Threat (APT): A sustained, targeted attack campaign or attacker group—not a vulnerability.
• Trojan: Malware disguised as legitimate software.
• Stealthware: A general term for malware designed to avoid detection; it does not specifically mean an unknown vulnerability.

• A class/teacher fact should contain one row per Class ID. It can support the count of classes and contain attributes such as Teacher First Name and Period Number.
• An attendance fact should contain one row per attendance event, such as Class ID + student + date. It supports attendance counts by day and monthly averages.

• Teacher First Name ? Teacher fact
• Period Number ? Attendance fact

• Dataset file: Use Import mode. Excel files are imported into Power BI, and the two Sales tables can be combined with Power Query.
• Report file: Use a live connection to the published dataset. This keeps the report separate from the dataset and avoids importing the data again.

• Report file: DirectQuery/live connection
• Dataset file: Import

• # Development
• # Testing
• # Production

• Separate endpoints: relate to compute or connectivity, not dashboard labels.
• Separate queries: retrieve or transform data but do not designate visual sections.
• Direct text written into the dashboard in editing mode: dashboards use text boxes, typically with Markdown formatting, rather than arbitrary text placed directly on the canvas.

• Remote and global work: Access is based on the approved device, not a specific office or geographic location.
• Seamless login: Users may not need to repeatedly enter credentials on a recognized device.
• Limited equipment: It uses devices employees already have rather than requiring separate hardware.

• Geotagging: Restricts access based on location and may prevent legitimate remote work.
• Smart cards: Require issuing and managing additional physical equipment.
• Time-based logins: Limit access by time and do not provide a seamless authentication experience.

• Products ? OrderHistory: Products is 1, OrderHistory is many (1:*)

• Date ? OrderHistory: Date is 1, OrderHistory is many (1:*)