Test Prep CFA-Level-I Exam Prep
CFA® Level I Chartered Financial Analyst (Page 237 )

• 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.

• 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.

• The backup file is complete and uncorrupted.
• The required data can actually be recovered.
• The recovery process and documentation work as expected.
• Recovery objectives, such as acceptable downtime, can be met.

• Backup logs may show that a job completed, but not that the backup is usable.
• File size does not prove the contents are valid.
• Email notifications may confirm process completion, not recoverability.
• Appointing a DBA does not itself validate backups.

• VPC: A logically isolated virtual network within a cloud provider; it describes network design, not the user-access model.
• NFV: Runs network services as software instead of on dedicated hardware.
• SaaS: Delivers software over the internet. Although the application may be delivered as SaaS, the question emphasizes its availability to multiple user groups, which points to multitenancy.

• Feedback form: Captures opinions, not necessarily actual behavior; users may not respond.
• Questionnaire: Relies on memory and subjective judgments about usefulness.
• Interviews: Can provide valuable qualitative insights, but a sample of users may not represent overall usage accurately.

• 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.

• Accept: Acknowledging the risk and choosing not to take additional action.
• Transfer: Shifting the risk or financial consequences to another party, such as an insurer.
• Mitigate: Reducing the likelihood or impact through controls, such as patching or access restrictions.
• Avoid: Eliminating the activity that creates the risk.

• 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.

• Architects design overall Splunk infrastructure and data strategy.
• Administrators manage configuration, access, and system operations.
• Knowledge Managers create and maintain knowledge objects such as data models, field extractions, and event types. They may support pivots, but they are not the primary users of them.

• 25 – Traditional SMTP server-to-server mail transfer; often blocked for client submission and not inherently secure.
• 110 – POP3 for receiving email; unencrypted by default.
• 143 – IMAP for accessing email; unencrypted by default.
• 587 – Authenticated email submission and commonly secured with TLS.

• 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.

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• ?? Power Query Editor? ???? ???? Discount ?? ????:

• ???? ?????? 0.05.

• Remove Errors: ???? ?????? ???? ????? ??? ?????? ???? ????? ??? ???????? ??? ??????.
• Keep Errors: ????? ??? ??????? ???? ??? ?????? ???? ??? ???????.
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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.

• Deploy five individual VMs: This does not create a VM scale set.
• Modify Availability Zones or Size settings: These actions do not create the required scale set and add unnecessary steps.
• VM orchestration mode: This is Flexible orchestration, intended for more individually managed VMs and mixed configurations. It is not the best choice for a straightforward group of identical instances.

• Deterministic approve/reject results
• Strict adherence to predefined rules
• Consistent, reproducible outcomes
• Auditability and regulatory compliance

• transform() — modifies every element in an array
• filter() — keeps elements matching a condition
• exists() — checks whether any element matches
• aggregate() — reduces array elements to one result

sql 
SELECT transform(scores, x -> x * 2) 
FROM student_scores;

• A is incorrect because higher-order functions are mainly useful for nested or complex data.
• B is incorrect because they do not convert logic into Python.
• D is incorrect because their purpose is not to fix slow built-in functions, but to process arrays or maps with custom logic.

• 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.

• Prevention costs – costs incurred to stop defects occurring, such as staff training, quality planning and supplier evaluation.
• Appraisal costs – costs of checking whether products meet standards, such as inspection, testing and quality audits.
• Internal failure costs – costs of defects found before delivery to customers, such as scrap, rework and retesting.
• External failure costs – costs of defects found after delivery, such as warranty claims, returns, complaints and product recalls.

• B: Developer Edition has limited user, storage, and data-volume capacity, making realistic community testing difficult.
• C: A Developer Edition org cannot contain sandboxes, so it cannot provide separate environments for development, integration, and UAT.
• E: A standalone Developer Edition org is not part of the production org’s deployment path, so change sets cannot be used to deploy from it directly to that production org. The team would need Metadata API, Salesforce CLI, or another deployment method.

• 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.

• SAS (Serial Attached SCSI):

• SSD (solid-state drive):

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.

• B — Sales staff will tender for riskier contracts:

• C — Sales staff will encroach on other territories:

• D — Sales staff will look for new jobs:

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

• Complete MFA, or
• Securely change their password

• Identity Protection: evaluates user and sign-in risk and can trigger remediation.
• Privileged Identity Management (PIM): manages temporary, just-in-time access to privileged roles; it does not automatically require password changes for risky sign-ins.

• A. IDS attack signatures: An IDS mainly detects suspicious network traffic. It is not the best control for scanning uploaded documents.
• C. Load balancer: Distributes traffic among servers and can improve availability, but does not specifically detect malware.
• D. WAF: Protects web applications from attacks such as SQL injection and command injection. It may inspect web requests, but malware scanning of PDF files is not its primary function.

• The underside clips or hinges are broken.
• The cap is stuck, loose, or misaligned.
• The cap no longer presses the switch correctly.
• The cap itself is missing or physically damaged.

• Information sources: Collect security-related data, such as network packets, system logs, audit records, or application events.
• Analysis: Examines the collected data to identify suspicious activity, attacks, or policy violations.
• Response: Takes or recommends action, such as generating alerts, logging the event, or supporting a protective response.

• 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.

1. Write a structured log entry to CloudWatch Logs containing:

1. Create a CloudWatch Logs metric filter that:

text 
ApiRequests 
Operation=GetOrders 
ResponseCode=500 
Version=2.4.0

• B is incorrect: CloudWatch Logs Insights queries analyze logs but do not directly publish metrics in this manner.
• C is incorrect: ALB access logs do not contain arbitrary Lambda response metadata as custom fields.
• D is incorrect: X-Ray traces and insights are not the appropriate mechanism for creating these custom, dimensioned application metrics.

• Domain controllers, because the requirement specifically excludes them. However, note that both member servers and domain controllers run Windows Server, so OS targeting alone cannot distinguish them unless the targeting option allows selecting the relevant server role/version. In the usual exam interpretation, target the applicable server OS category.
• Client computers, because they run a client Windows operating system.

• Domain: Targets membership in a domain, not the computer’s operating-system type.
• Security Group: Would require creating and maintaining a group containing all member servers, increasing administrative effort.
• Environment Variable: Not designed to reliably identify member servers.

• B: Extending credit to customers increases receivables, so more cash is tied up in working capital.
• C: Replacing obsolete inventory does not reduce the overall inventory investment; it simply changes its composition.
• D: Paying suppliers earlier reduces payables. This uses cash and therefore increases the funds tied up in working capital.

• 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.

• 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.

• 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.

• A: Concerns task scheduling and avoiding missed runs, not directly sizing the warehouse.
• B: The amount of data in a stream alone does not reliably determine compute needs; the SQL processing is what matters.
• D: A multi-cluster warehouse addresses concurrency, not the compute size needed for one task execution.

• Sets a high initial price for a new product.
• Targets customers willing to pay more, often called early adopters.
• Gradually reduces the price to attract more price-sensitive customers as the product becomes less novel and competition increases.

• Penetration pricing: starts with a low price to gain market share quickly.
• Premium pricing: maintains a high price to communicate superior quality or status; it does not necessarily involve later price reductions.
• Loss leader pricing: sells one product at a very low price, sometimes below cost, to attract customers who may buy other products.

• Floating IP must be enabled on the load-balancing rule.
• Session persistence should normally remain None.
• The health probe determines which replica should receive traffic.
• Client-IP persistence is unnecessary and can cause connections from the same client to remain associated with a backend replica longer than intended.

• Q9 — Client IP session persistence: No
• Q10 — Floating IP: Yes

• D — Value analysis: Correct. It examines an existing product to identify ways of reducing its cost while still providing the required functions, quality and reliability.
• E — Kaizen costing: Correct. It involves making continuous, small improvements and cost reductions while the product is already in production.

• Functional analysis: It is not limited to minimizing the cost of the originally defined functions. It examines what functions are required and how they can be provided at the lowest overall cost.
• Value engineering: Usually applies to the design and development of a new product, rather than being a fundamental redesign of existing organisational processes. That description is closer to business process re-engineering.
• Target costing: The target cost is generally established during the product development stage, before production begins. It is not continuously reset while the product is in production.