CFA CFA I Exam Prep
CFA Level I Chartered Financial Analyst (Page 172 )

• Each team’s Bedrock workflow uses a separate IAM service role.
• The role’s Amazon S3 permissions can be limited to only that team’s customer folder or objects.
• This enforces least privilege and prevents one team’s Bedrock application from accessing another team’s data.
• Access is enforced by AWS permissions, not by asking users to provide a customer name in each request.

• A single role with broad S3 access does not provide team-level isolation.
• Asking teams to specify a customer name is not an access-control mechanism.
• Redacting data does not prevent unauthorized access.
• A bucket policy alone is insufficient unless it explicitly enforces the required team-role restrictions.

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

• The requirement is to obtain an assessment of the Azure environment’s design.
• The proposed solution is the Premier support plan.
• Premier can provide this type of guidance, but it is a higher-tier, more expensive option.
• The question specifically says to keep costs to a minimum. A lower tier—typically Professional Direct in the support-plan model used by this question—provides architectural/design guidance.

• 50% memory utilization baseline: The environment can be provisioned with excess capacity, leaving room for growth and workload spikes.
• Storage scalability: Cloud storage can generally be expanded as needed without redesigning the physical platform.
• Single circuit failure resilience: A properly designed IaaS provider uses redundant power circuits and infrastructure, so failure of one circuit should not take the platform offline.

• A — Dual PDUs: Helps with power redundancy but does not provide storage scalability.
• C — Network load balancing: Provides network-path resilience, not memory or storage scalability, and does not address a power-circuit failure.
• D — Multiple NAS devices: May improve storage capacity, but does not inherently provide power resilience or the required compute-capacity baseline.

• 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.

apex 
Set<Id> accountIds = new Set<Id>{ accountId1, accountId2 }; 


List<Account> accounts = [ 
    SELECT Id, Name 
    FROM Account 
    WHERE Id IN :accountIds 
];

• A: LIMIT accepts a number, not a collection of IDs.
• B: Set.containsAll() checks set contents in Apex; it does not filter SOQL results.
• C: Database.query() accepts a dynamic SOQL string, not a Set<Id> directly.

• Business risks
• Potential financial, operational, legal, or reputational impact
• How governance reduces risk to organizational objectives
• How much risk the organization is willing to accept

• Initial Intrusion: The compromised VPN account and stolen phishing credentials describe how the attacker first gained access, but that happened months earlier.
• Persistence: The scheduled tasks and recurring C2 connections show how the attacker maintained and automated continued access.
• Search and Exfiltration: This would involve locating and transferring data. The scenario does not primarily describe data discovery or theft.
• Cleanup: Cleanup involves removing evidence or covering tracks. Obfuscated scripts may make detection harder, but the main behavior here is maintaining access.

• 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 learning.
• NGFW: Protects at network boundaries but does not directly limit MAC addresses learned on access ports.

• NIDS: Monitors network traffic for suspicious activity and network-based attacks targeting the application or its supporting services.
• HIPS: Protects an individual host by monitoring processes, files, and system activity. It can help secure the web server, but it is not focused specifically on the application’s network attack surface.
• SIEM: Aggregates and correlates logs; it does not directly prevent attacks.
• Honeypot: A decoy system, not the primary protection for a production web application.
• Certificate revocation list: Deals with certificate trust, not application exploitation.

text 
ip route vrf Customer1 172.16.1.0 255.255.255.0 172.16.1.1 global 
ip route vrf Customer2 192.168.1.200 255.255.255.255 192.168.1.1 global 
ip route 192.168.1.0 255.255.255.0 Vlan10 
ip route 172.16.1.0 255.255.255.0 Vlan20

• The route in Customer1 VRF provides a path back to the Customer2 subnet, 172.16.1.0/24.
• The route in Customer2 VRF provides a path to the FTP server, 192.168.1.200.
• The keyword global tells the router to resolve the next hop using the global routing table, enabling controlled route leaking between the VRF and global table.
• The global routes identify the VLAN interfaces used to reach each customer network.

• 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.

• GPS coordinates
• Date and time the image was taken
• Camera or device information
• Image dimensions and software used

• Log data: Records generated by systems or applications, not normally embedded in image files.
• Encrypted data: Information intentionally encoded to prevent unauthorized access.
• Sensitive data: A broad classification, not the specific type of information being extracted.

• Managerial: policies, standards, risk management, governance
• Operational: procedures carried out by people, such as training, incident response, and backups
• Technical: firewalls, encryption, access-control systems
• Physical: locks, guards, cameras

• An Adj-SID does not necessarily need manual configuration.
• It can often be dynamically allocated by the router, although manual configuration may also be possible.
• The adjacency information is advertised through the IGP, such as IS-IS or OSPF.

• It is identified by an Adj-SID.
• It represents a particular adjacency of a node.
• Its meaning is generally local to the advertising node; unlike a Node-SID, it is not a globally reusable instruction across the network.

• Default network device credentials: More associated with external attackers or poor device configuration.
• Spear phishing emails: Commonly used to compromise users, but less characteristic of an insider who already has access.
• Typosquatting and impersonation: Primarily social-engineering techniques aimed at deceiving users.
• Unidentified removable devices: Provide a direct way to transfer data outside the organization and may bypass network monitoring.

• Plenum: Describes a fire-resistant cable jacket rating, not a transmission medium or speed.
• Ethernet: Describes a networking technology; Ethernet can use copper or fiber, so the term alone does not identify the fastest cable type.
• DAC (Direct Attach Copper): Uses copper and is typically intended for short-distance, high-speed connections in data centers.

• Each Azure VM must have at least one network interface (NIC).
• A single NIC can have:

• Therefore, each of the five VMs needs only one NIC:

apex 
for (Account updatedAccount : Trigger.new) { 
    AccountTriggerHelper.notinyxternalSystem(updatedAccount.Id); 
}

• Too many callouts: The callout occurs asynchronously in the future method, and each future transaction can perform its permitted callouts.
• Too many SOQL queries: The SOQL query is inside the future execution, not repeatedly in the trigger transaction.
• Callout from triggers not supported: Direct callouts from triggers are prohibited, but the trigger delegates the callout to asynchronous Apex, which is the correct pattern.

• Code suggestions: Inline completions as you write code, such as lines, functions, or blocks.
• Chat: An interactive interface for asking questions, explaining code, generating code, and helping with debugging.

• Knowledge Base: Not listed as a standard Copilot Individual IDE feature in this context.
• Pull Request Diff Analysis: More closely associated with GitHub-based code review or pull-request features, not the core Individual IDE extension capabilities.

• 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.

• 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.

1. The specific table — for example, incident
2. The parent table — for example, task
3. The wildcard table — *, which applies broadly

• Ease of exploitation
• Required privileges
• User interaction
• Impact on confidentiality, integrity, and availability

• CVE: Identifies and names a specific publicly known vulnerability; it does not measure severity.
• OSINT: Refers to intelligence gathered from publicly available sources.
• SOAR: Automates and coordinates security operations, such as alert response and playbooks.

• IaaS: você gerencia a VM e o sistema operacional.
• PaaS: o Azure gerencia a infraestrutura; você se concentra no aplicativo.

• IaaS: You deploy and manage virtual machines, including the operating system and installed software. Azure manages the physical datacenter, hosts, and networking infrastructure.
• PaaS: Azure manages the infrastructure and operating system, while you deploy and manage your application code. Examples include Azure App Service and Azure Functions.

• Existing measures
• Relationships
• Calculated columns
• Tables and fields
• Existing transformations in the model

• SharePoint folder: Reconnects to the source files. You would likely need to recreate the model and measures.
• Power BI dataflows: Primarily provide reusable data preparation and storage, but they do not automatically provide the existing semantic model and measures.
• Excel workbook: Connects directly to the source file and would also require rebuilding the model and measures.

• Box 1: No — The rule requires user.department to equal Engineering. Engineer does not match, so User1 is not in AU1. Admin1 cannot reset User1’s password.
• Box 2: No — Admin1’s role is scoped to AU1 and cannot manage users outside that AU.
• Box 3: Yes — Admin2 is a Global Administrator and can reset User3’s password.

• IRR assumes that interim cash flows can be reinvested at the project’s own IRR. This may be unrealistic, especially when the IRR is very high.
• MIRR assumes reinvestment at a specified rate, usually the company’s cost of capital or another realistic reinvestment rate.

• B: MIRR does not specifically favour projects with long payback periods.
• C: MIRR and IRR can rank competing projects differently.
• D: MIRR is not always higher than IRR; it may be higher or lower depending on the cash flows and reinvestment rate.

• The product is already in production.
• The organization is examining the product’s functions and cost drivers.
• The objective is to reduce cost without reducing perceived value or required quality.

• Kaizen costing focuses on continuous, usually incremental, cost reductions during the manufacturing stage. It is not specifically the systematic examination of a product’s functions.
• Standard costing compares actual costs with predetermined standards; it is a control technique, not a product redesign method.
• Process innovation concerns developing significantly improved production processes, rather than analysing the product’s functions and value.

• SharePoint search: Finds documents based on search terms, but it does not reliably identify every 32-character account number for DLP enforcement.
• A hunting query in Microsoft 365 Defender: Used for security investigations, not for defining sensitive content in a DLP policy.
• Azure Information Protection: Uses classification and labeling; it does not automatically identify this specific account-number pattern unless configured with a matching sensitive information type.
• RegEx pattern matching: Best suited for structured identifiers with a known format, such as account numbers, employee IDs, or policy numbers.

• C series: CPU-optimized instances; not designed primarily for LLM training.
• G series: GPU instances generally optimized for graphics and some machine learning workloads, but not specifically large-scale model training efficiency.
• P series: Powerful GPU instances for ML training, but typically consume more energy than Trainium-based instances for suitable training workloads.

• Economy: Obtaining inputs at the lowest appropriate cost.
• Efficiency: Making the best use of resources, such as staff, money, and equipment.
• Effectiveness: Achieving the intended objectives or outcomes.

• terraform apply
• terraform destroy

• Confirm the required columns and data types
• Identify the target/label column
• Handle missing or duplicate records if present
• Transform data into a suitable format
• Split it into training and validation/test datasets

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

• 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.

• Liability accounts (2000–2999) would incorrectly require dimensions, although they should have none.
• Expense accounts (6000–6998) would incorrectly require Customer, which should be optional.
• Account 6999 needs a separate rule because it requires all four dimensions, including Customer.

• 2000–2999: no dimensions
• 4000–4999: Department and Division required; Project and Customer optional
• 6000–6998: Department, Division, and Project required; Customer optional
• 6999: Department, Division, Project, and Customer required

• Base table — the table containing common inherited fields
• Parent table — the table directly extended by the child
• Other tables in the hierarchy

• Azure Resource Manager (ARM) templates define the virtual machines and related Azure resources declaratively. You can deploy the same template repeatedly, ensuring consistent VM sizes, networking, storage, extensions, and other infrastructure settings.

• PowerShell DSC extension applies and maintains the required Windows configuration inside each VM. DSC is state-based: if a setting changes or becomes incorrect, DSC can bring it back to the desired configuration.

• Azure Pipelines deployment groups organize deployment targets, but they do not primarily enforce ongoing VM configuration.
• Custom Script Extension runs setup scripts, but it is generally less maintainable and does not continuously enforce configuration like DSC.
• Pipeline stage templates reuse pipeline workflow definitions; they do not configure the VMs themselves.

• No servers or database infrastructure to provision.
• Uses standard SQL.
• Supports formats such as JSON, CSV, Parquet, and ORC.
• You typically define the table structure with AWS Glue Data Catalog or Athena’s own schema definitions.
• Charges are generally based on the amount of data scanned, so partitioning and columnar formats can reduce cost.
• It does not copy the data into a separate database; it reads the files in S3 when you run a query.

• Understating expenses and liabilities
• Overstating profit
• Misleading users of the financial information
• Potentially breaching integrity, objectivity, and professional competence and due care

• \Pipeline1
• \Folder1\Lakehouse1

• Pipeline1 remains at the workspace root in Workspace1, so it is deployed to the root of Workspace2.
• Lakehouse1 was moved into Folder1, so its full path is preserved as \Folder1\Lakehouse1.
• Fabric deployment pipelines preserve folder paths because an item’s full path is treated as part of its name.

• Two-part tariff pricing: $10 per unit
• Dual pricing: $20 per unit

Two-part tariff pricing

Dual pricing

• Division X, the seller, is credited with the market price: \(\$20\)
• Division Y, the buyer, is charged the marginal cost: \(\$10\)

• Response and resolution time frames
• Availability or uptime requirements
• Performance targets
• Support obligations
• Penalties for failing to meet requirements

• SOW (Statement of Work): Defines the project’s scope, tasks, and deliverables.
• MOA (Memorandum of Agreement): Describes cooperation and responsibilities between parties.
• MOU (Memorandum of Understanding): Records a general mutual understanding, usually without detailed enforceable service targets.

• True positive: The scan reports a vulnerability that really exists.
• False positive: The scan reports a vulnerability that does not exist.
• True negative: The scan correctly reports no vulnerability.
• False negative: The scan fails to detect a vulnerability that is actually present.

• # 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.

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.

• 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.

1. Get Data > Folder

1. Expand the Attributes column

1. Remove the Content column

• Folder connector: lists files and their metadata, but also includes a Content binary column.
• Combine Files: processes and combines the actual CSV contents, which is explicitly disallowed here.

• 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.