Salesforce MKT-101 Exam Prep
Build and Analyze Customer Journeys using Marketing Cloud (Page 4 )

• B — AWS DataSync: Transfers data between storage systems. It is not a marketplace or integration service for third-party datasets.
• C — Kinesis Data Streams and CodeCommit: CodeCommit stores source code, not third-party analytical datasets. Kinesis is for streaming data, not retrieving datasets from repositories.
• D — Kinesis Data Streams and ECR: Amazon ECR stores container images, not third-party datasets.

• Existing expected ROI: 15%
• New project ROI: 14%
• Cost of capital: 12%

• Project return = 14%
• Cost of capital = 12%
• It earns 2% more than the cost of capital, so it should increase shareholder value.

1. It examines the source MAC address and learns it on the incoming port.
2. It examines the destination MAC address.
3. If the destination MAC is already in the MAC/CAM table, it forwards the frame only through the associated port.
4. If the destination MAC is unknown, it performs unknown-unicast flooding:

• Least privilege: Limits users to only the access necessary for their job.
• Background checks: Help identify potentially risky individuals before employment.
• Separation of duties: Ensures that one person cannot complete a sensitive process alone, reducing fraud and abuse.

• 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.

• A — Use a custom controller: An Apex class can contain the page’s logic.
• C — Use a standard controller with extensions: The standard controller provides basic CRUD behavior, while an extension adds custom logic.
• E — Use a standard controller: Useful when the page works mainly with one Salesforce object and needs standard functionality.

• A page with no controller for static or controller-free content.
• A custom controller with extensions; extensions are not limited only to standard controllers.

• Crowd-sourced evaluation: Requires recruiting and managing many evaluators.
• Human-worker evaluation: Provides human judgment but requires coordination, labeling instructions, and quality control.
• RLHF: Is a training and alignment process, not simply a low-overhead model comparison method.
• Automatic model evaluation: Quickly evaluates outputs using predefined toxicity or quality metrics with minimal manual effort.

• Admin access to the deployment pipeline
• Contributor access to the Development and Test workspaces
• Viewer access to the Production workspace

• up ? down ? up
• Often happens rapidly or intermittently

• Faulty or loose cable or connector
• Failing transceiver, NIC, or switch port
• Speed/duplex or auto-negotiation problems
• Power or hardware instability
• Layer 1 interference

• Nothing plugged in: the port is simply down
• Latency: does not directly trigger err-disable
• shutdown: administratively disables the port, but that is not the same as an automatically detected err-disabled condition

• B. Deploy to a SageMaker endpoint: This is needed for SageMaker-hosted models, not for a model intended to be used directly in Amazon Bedrock.
• C. Register with SageMaker Model Registry: SageMaker Model Registry is unrelated to invoking custom models in Bedrock.
• D. Grant access in Bedrock: Access permissions may be necessary, but they do not replace the required provisioned capacity.

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

• Maintain head office control: Transfer pricing generally supports decentralisation rather than direct head-office control.
• Establish centralised decision making: This conflicts with divisional autonomy.
• Develop a top-down culture: Transfer pricing is intended to support empowered divisions and goal congruence, not impose purely top-down management.

• A user connects with their Google account.
• Google associates the user’s SSH key with that identity.
• IAM roles determine whether they can log in.
• Access can be tied to a specific employee for auditing.
• Removing the IAM role removes their login access.

• compute.osLogin: regular OS login access
• compute.osAdminLogin: OS login with administrative privileges, typically including sudo

text 
enable-oslogin=TRUE

• 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.

• AWS Network Firewall can inspect and block traffic across a VPC when traffic is routed through the firewall. A Drop action rule can deny traffic from the suspicious source IP.
• GuardDuty findings are sent to Security Hub.
• A Lambda function can be invoked when Security Hub receives a new GuardDuty finding, extract the source IP, and update the Network Firewall policy with a blocking rule.

• GuardDuty threat lists: Used to identify or increase the severity of findings; they do not directly block VPC traffic.
• AWS WAF: Protects supported web applications, such as CloudFront or Application Load Balancers. It does not provide general VPC-wide traffic blocking.
• GuardDuty suppression rules: Suppress or hide findings. They do not block the suspicious traffic.

• Existing Eventhouse data: remains available only in the KQL database.
• Data ingested after enabling the feature: is copied to OneLake and can be accessed through OneLake file explorer.
• New databases: are irrelevant; the setting applies to the selected KQL database.

• Which host first communicated with the suspected malicious source
• Whether that host initiated suspicious traffic or merely received it
• Which other hosts show evidence of infection, such as connections from the originating host
• Which hosts have no related suspicious activity and are therefore clean

• An outbound connection to a suspicious external address
• A downloaded or executed malicious file
• Later lateral connections from that host to other internal systems
• Firewall logs showing the direction and timing of the traffic

1. The original app version exists.
2. You create and publish a new version, so there are now two versions.
3. When you restore the previous version, Power Apps does not delete or overwrite the newer version. Instead, it creates another version based on the restored one.

• Original version
• Newly created and published version
• New version created by the restore operation

• 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.

• Guest access: Controls external users invited into your teams as guests. It is not the primary setting for restricting federated communication by domain.
• Messaging policy: Controls messaging features, such as chat or message editing, rather than which organizations users can communicate with.
• Org-wide Teams settings: Contains broad Teams-wide configuration, but domain-based external communication is configured under External access.

• Row counts
• Minimum and maximum values for columns
• Distinct-value information
• Other characteristics used for optimization

• The JSON files contain one billion items, so this is a big-data workload.
• PySpark uses Apache Spark’s distributed, parallel processing, allowing the data to be processed across multiple compute nodes.
• It can read and transform data directly from OneLake, helping minimize unnecessary data movement or duplication.
• A Fabric notebook can also support exploration and visualization, as well as Spark-based analytics and anomaly-detection workflows.

• Pandas is primarily in-memory and generally suited to smaller datasets. One billion records would be impractical on a typical single machine.
• A Power BI report with core visuals is appropriate for visualization and sharing, but it is not the best tool for large-scale transformation, parallel processing, or anomaly detection. It would normally consume prepared data rather than perform the entire workload.

1. Horizontal scaling — Yes

1. Vertical scaling — Yes

1. Scaling can manage costs — Yes

• Horizontal = more or fewer instances
• Vertical = larger or smaller instances

• 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.

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

• New investment: $536,500
• Resulting NPV: $0