CFA ESG-Investing Exam Prep
Certificate in ESG Investing (Page 26 )

• The current and previous versions
• Which clauses were changed
• When each revision occurred
• Potentially, who made the changes

• Version validation: Verifies a version’s accuracy or integrity but does not primarily track revisions.
• Version changes: Not the standard name for a formal document-management process.
• Version updates: Describes updating a document, not the complete process of managing and tracking its revisions.

• Product Owner: May attend, but is not required unless also working as a Developer.
• Scrum Master: May attend to help facilitate or coach, but is not required.
• Developers: Must participate because the event is specifically for them.

Flat organisation

• Few levels of management
• A wide span of control—managers supervise many employees
• Shorter communication channels
• More employee autonomy and quicker decisions
• Fewer formal promotion levels

Tall organisation

• Many levels of management
• A narrow span of control—managers supervise relatively few employees
• A clear hierarchy and reporting structure
• More formal supervision and communication channels
• More obvious promotion and career stages

• A valid input returns the expected result
• An invalid input raises an error
• Boundary values are handled correctly

• B: Copilot may help generate tests, but it does not automatically write all necessary tests.
• C: Writing the implementation does not verify that it works correctly.
• D: Copilot can suggest test commands or test code, but the developer or development environment must execute and validate the tests.

• A. Microsoft 365 group with Assigned membership
• C. Microsoft 365 group with Dynamic User membership

Why?

• Assigned membership: You explicitly add User1, User2, and User3.
• Dynamic User membership: Membership is automatically determined by a rule based on user attributes.

Why the other options are incorrect

• B and D: Security groups do not support the Microsoft 365 group expiration policy.
• E: Dynamic Device groups are intended for devices, not these users, and are also security groups.

• SOW
• SLA
• MOA
• MOU

• Modelo de embeddings de texto: trabalha principalmente com texto, não sendo adequado para imagens.
• Modelo generativo multimodal: pode interpretar ou gerar conteúdo de vários tipos, mas não é a opção específica para busca por similaridade.
• Modelo de geração de imagens: cria imagens a partir de entradas, não realiza busca multimodal.

• File1.png — Yes: User1 can apply Label1 with the Microsoft Purview Information Protection client. The client supports labeling image files such as .png in this scenario.

• Folder2 — No: Folder2 is the root folder. The client does not allow labeling the root folder itself. Although the client can label ordinary folders, selecting one applies the label to existing files and subfolders—not automatically to future files.

• File1.docx — Yes: .docx is a supported Microsoft Word file type, so User1 can apply Label1 to it.

• Career enhancement — A mentor can provide guidance, advice, networking support and help the mentee identify career opportunities.
• Support with new challenges — A mentor can help the mentee think through unfamiliar situations and develop confidence and practical solutions.
• Personal development — Mentoring can improve skills such as communication, leadership, decision-making and self-awareness.

• Solving all problems — The mentor supports and guides the mentee but should not take responsibility for solving every problem.
• Discipline would be dispensed if they make a mistake — Mentoring does not remove normal accountability or workplace consequences. Mistakes should instead become learning opportunities.

• Árvores de decisão: usam regras sequenciais, como “se característica X > valor, siga para este ramo”. São fáceis de visualizar e explicar. Atendem bem a problemas de classificação e regressão com alta interpretabilidade.

• Regressão linear: prevê um valor numérico contínuo, como preço, custo ou temperatura. Não é a escolha principal para classificar genes em categorias.

• Regressão logística: calcula a probabilidade de uma categoria. Pode atender à classificação, inclusive multiclasses, mas sua explicação costuma ser menos intuitiva que uma árvore para documentar decisões.

• Redes neurais: atendem a tarefas complexas, como imagens, texto e padrões não lineares. Porém, são menos interpretáveis, funcionando mais como uma “caixa-preta”.

• Entradas grandes, de até aproximadamente 1 GB.
• Processamentos demorados, que podem levar até cerca de 1 hora.
• O cliente envia a solicitação e consulta o resultado depois, sem precisar manter uma conexão aberta durante todo o processamento.

• Real-time inference: indicada para respostas imediatas, com entradas menores e processamento rápido.
• Serverless inference: adequada para cargas variáveis e solicitações menores; não é ideal para processamento longo e arquivos grandes.
• Batch transform: processa grandes volumes em lote, mas não atende à necessidade de respostas próximas do tempo real.

• User preferences change, so the model must learn from recent data.
• Keeping the existing data helps preserve knowledge of older patterns and provides a broader training distribution.
• Training only on new data can cause catastrophic forgetting and may overfit if the new dataset is small.
• The new data should not automatically be used as the test set, because it is needed for training and the model must still be evaluated on separate, representative data.

• Online payment fraud
• Account takeover
• Fake account creation
• Suspicious transactions

• Aggregation happens once, during the scheduled job.
• Dashboard users query a relatively small, precomputed table.
• Repeated users do not trigger expensive aggregations against the detailed sales table.
• Overwriting is appropriate because the summary is rebuilt for the reporting period.

• B: Structured Streaming is unnecessary for data that only needs daily refreshes and adds operational/compute overhead.
• C: A view recomputes the aggregation at query time, increasing latency and query cost.
• D: Delta caching may improve reads but does not replace the need to materialize the expensive aggregation, and cache availability is not the main design guarantee.

• Azure Resource Manager (ARM) templates
• Or, in newer Azure terminology, Bicep files

• Continuous deployment: Automates software releases; it does not specifically test input handling.
• Static code analysis: Examines source or compiled code without executing it. It can find coding flaws but does not directly stress the application with malformed inputs.
• Manual peer review: Developers inspect code or design manually. Useful, but not the best practice specifically for testing how a live product handles invalid input.

• BIOS language support: Useful for usability, but not whether the PC can operate electrically.
• Supply chain security: Concerns procurement and hardware trust, not deployment across countries.
• Power efficiency: Important for energy usage, but it does not ensure compatibility with local power systems.

• Use private connectivity from a cloud provider
• Set up SSO for federated authentication

• Private connectivity—such as a cloud provider’s private endpoint—keeps Snowflake access within the company’s private network path instead of exposing access over the public internet. This fits the VPN/VDI requirement.
• SSO for federated authentication allows Snowflake users to authenticate using the credentials already managed by the company’s identity provider—the same identity system used for VDI—eliminating separate Snowflake passwords.

• Tri-Secret Secure protects encryption keys; it does not provide private network access or credential reuse.
• A proxy Snowflake account outside the VPN conflicts with the requirement that Snowflake have no internet visibility and is not the normal solution for federated login reuse.

• ADF: Automatic Document Feeder; a printer/scanner hardware component.
• USB: A short-range wired connection, not a protocol for accessing a remote shared folder.
• PCL: Printer Control Language; it describes how print jobs are formatted, not how files or printers are shared over a network.

• Data loss prevention (DLP): Helps detect or prevent unauthorized data transfers, but does not directly protect data on a stolen, powered-off laptop.
• Operating system hardening: Reduces vulnerabilities and attack surface, but does not adequately protect stored data if the device is stolen.
• Boot security: Helps prevent unauthorized operating systems or boot media from loading. It supports device security but is not the primary solution for protecting the data itself.

Why

cmd 
PowerShell.exe -ExecutionPolicy Bypass -File C:\Scripts\ConfigureVM.ps1

Why the other options are less suitable

• GPO logon script: Runs only when a user logs on and may not run during initial VM provisioning.
• GPO startup script: Can work, but requires the VM to be joined to the domain and the policy to be applied. It is also normally evaluated at each startup.
• Place scripts in a VHD: Merely placing scripts on a disk does not cause them to execute.

1. Selling price per unit: $750
2. Required annual return:

1. Required profit per unit:

1. Target cost per unit:

• A: My Domain is required for many SSO configurations, but if SSO works, it is unlikely to be the cause of losing the target record.
• B: HTTP-POST is a valid SAML binding and does not inherently prevent redirection.
• D: An incorrect Federation ID generally causes authentication or user-matching failure—not successful login to the home page.

• Creating and managing users and roles
• Granting and revoking roles and privileges
• Managing access-control responsibilities

• SYSADMIN: Manages warehouses, databases, schemas, and other objects—not primarily users and roles.
• PUBLIC: Automatically granted to every user; it is not an administrative role.
• ACCOUNTADMIN: Has the highest level of access, but should be reserved for account-level administration and emergencies rather than routine security tasks.

json 
"Resource": "arn:aws:s3:::bucket-name/*"

• A: Revoking or changing an instance profile does not reliably invalidate temporary credentials that have already been issued and may still be valid.
• B: Changing the EC2 security group does not necessarily stop the attacker from using the stolen credentials from elsewhere.
• C: Amazon Macie helps discover sensitive data; Object Lock prevents modification/deletion, not reads or downloads.

• Business
• People
• Governance
• Platform
• Security
• Operations

• Cloud financial management
• Portfolio management
• Data governance
• Risk management
• Compliance

• A. IDS attack signatures: Primarily detects suspicious network activity, not necessarily malware embedded in uploaded files.
• C. Load balancer: Improves availability and distributes traffic; it does not inspect documents for malware.
• D. WAF: Protects web applications from attacks such as SQL injection and command injection, but its primary role is not scanning uploaded PDFs for malware.

• vSmart controls the overlay control plane. It uses OMP to exchange routing information, distribute policies, and determine how WAN Edge devices reach one another.
• vManage is the centralized management and configuration platform.
• vBond is the orchestrator. It helps devices authenticate, discover controllers, and traverse NAT during onboarding.
• APIC-EM is not the SD-WAN control-plane component described here.

• A — Add a Path for Stage: A Path lets users update the Opportunity’s Stage directly from the record page, without opening the full edit form. It can also display guidance and key fields.
• B — Use a Kanban list view: Users can move Opportunities between stages by dragging records between columns, which is ideal when Stage is the only field they normally change.

• Low usage during the first three weeks
• Very high usage during the last week

• High availability: Keeps services running despite failures.
• High latency: Means slow response times; it is not a benefit.
• Load balancing: Distributes traffic across resources but does not specifically address scaling resources up and down.

• R-squared: Typically used for regression, not classification.
• RMSE: Measures prediction error for continuous numerical values, so it is not the best fit here.
• Learning rate: A training hyperparameter that controls how quickly the model updates its weights; it is not an evaluation metric.

• Personally identifiable information (PII) detection

• Prompt Shields

• Self-harm content filtering addresses self-harm-related content.
• Violence content filtering addresses violent content.
• Neither protects customer PII or detects document-based prompt injection.

• Microsoft Teams: Connects to Teams-related data, but it isn’t the primary connector for the Power Apps data tables.
• Personal Analytics: Provides personal productivity insights, not application data.
• SQL Server database: Only applies if the app explicitly uses SQL Server as its data source.
• Dataflows: Used for preparing and centralizing data, not as the normal direct connection to a Power Apps app.

• A. A virtual network gateway
• D. A virtual network

• Azure virtual machines must be connected to an Azure virtual network (VNet). The VNet provides private IP addressing and network connectivity for the VMs.
• A virtual network gateway enables communication between the Azure VNet and the on-premises network, typically through a site-to-site VPN or ExpressRoute connection.

• Load balancer: Distributes traffic among Azure VMs; it does not connect Azure to an on-premises network.
• Application gateway: Provides web-application load balancing and Layer 7 routing; it is not the normal resource for on-premises connectivity.
• Gateway subnet: A gateway subnet is required inside the VNet when deploying a virtual network gateway, but the question’s intended two primary resources are the VNet and virtual network gateway.

• AWS AppSync is designed for serverless applications that need to retrieve and combine data from multiple sources.
• A pipeline resolver can invoke multiple functions or data-source resolvers, including resolvers connected to different DynamoDB tables.
• The application can receive the combined result through one GraphQL request, without requiring custom aggregation logic in the application.
• This is operationally efficient because AppSync manages the API layer and resolver execution.

• Athena Federated Query is intended primarily for analytics and ad hoc querying, not low-latency application data retrieval.
• Querying DynamoDB through Athena can consume DynamoDB read capacity and may affect table performance.
• It also introduces analytical-query overhead and is not the normal choice for a microservice web application.

• 16 VMs: one failure loses 25 GB and 10 cores—only 6.25% of memory.
• 8 VMs: one failure loses 12.5% of memory.
• 4 VMs: one failure loses 25%.
• 1 VM: one failure loses the entire application environment.

• 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.

• Filtering or reshaping columns
• Joining with an analysis-specific dataset
• Creating calculated fields
• Applying business logic for a particular project

• Data blending: Combining different data sources, not specifically the final processing step.
• Data enhancement: A broad term for enriching data.
• Data testing: Checking data quality or pipeline correctness.
• Last-mile ETL: The precise term for additional transformations performed after the main pipeline, often directly before analytics or reporting.

bash 
docker run -it microsoft/azure-cli:0.10.17

• docker run starts an Azure CLI container; it does not automatically connect to the AKS cluster.
• The command does not run kubectl apply.
• The container would need the appropriate Kubernetes tools and AKS credentials.
• The device or container must obtain cluster credentials, typically using an AKS credential command, before running Kubernetes commands.

bash 
az aks get-credentials --resource-group <resource-group> --name <aks-cluster> 
kubectl apply -f myapp.yaml

• Accept: Acknowledge the risk and choose not to take additional action.
• Transfer: Shift the risk or its financial impact to another party, such as through insurance or outsourcing.
• Mitigate: Reduce the likelihood or impact of the risk, such as by implementing security controls.
• Avoid: Eliminate the activity or condition that creates the risk.

• Cloud architecture
• Data architecture
• Platform engineering
• Data engineering
• Provisioning and modernization

• Data protection is associated mainly with security and risk management.
• Data governance belongs to the governance perspective.
• Data science is not an AWS CAF capability.

• Leaf switches provide access ports for servers, endpoints, and other devices.
• Spine switches form the fabric’s backbone.
• Every leaf connects to every spine, creating a predictable, high-bandwidth, low-latency path.

• A: Adding both a spine and leaf is unnecessary for simply adding access ports.
• B: Adding a spine does not directly provide endpoint access ports.
• D: A single connection to one spine creates a bottleneck and a single point of failure.

• Due Date
• Order Date
• Delivery Date

DAX 
Order Date = 'Due Date' 
Delivery Date = 'Due Date'

• Due Date[Date] ? Sales[Due Date]
• Order Date[Date] ? Sales[Order Date]
• Delivery Date[Date] ? Sales[Delivery Date]

• Users logging in more frequently than average
• Logins occurring during non-business hours
• Patterns that may indicate compromised credentials or suspicious access

• Login History: Shows individual login attempts and basic details, but does not provide behavioral analysis or averages.
• Login Inspector: Used to troubleshoot or inspect a specific login attempt, rather than analyze organization-wide patterns.
• Login Report: May provide reportable login information, but it is not the specialized tool for forensic behavioral analysis.

• Data lakes: scalable, low-cost storage for structured, semi-structured, and unstructured data.
• Data warehouses: reliable SQL analytics, governance, and performance features.

• Data lake: Primarily provides flexible, scalable storage but may lack warehouse-style reliability and governance.
• Data warehouse: Strong for structured analytics but less flexible for raw and unstructured data.
• All of these: The individual lake and warehouse do not, by themselves, unify the siloed architecture.

Correct choices

• DB1: Azure Data Box Heavy
• Virtual machines: Azure Migrate

Why

• Replication with minimal downtime
• A test migration
• Final cutover after validation

• Writing with Apache Spark, typically as Delta tables.
• Reading with Apache Spark for processing and analysis.
• Reading with T-SQL through the lakehouse’s automatically generated SQL analytics endpoint.
• Reading with KQL through Fabric’s query capabilities that can access lakehouse data.

• Eventhouse: Optimized for real-time and KQL workloads, but it is not the natural destination for Spark-based writes or general lakehouse storage.
• Datamart: Intended mainly for relational analytics and Power BI; it is not designed for Spark-based data ingestion.
• Warehouse: Primarily T-SQL-based and structured. It does not provide the same native Spark write experience or flexibility for semi-structured data.

• A — Can help keep costs down and improve quality: The provider may have specialist expertise, efficient systems and economies of scale.
• B — There is a known fee if agreed in advance: A fixed or agreed fee can make costs more predictable and support budgeting.
• C — Allows management to focus on core operations and issues: Senior managers spend less time supervising routine finance processes and more time on strategic matters.

• Increased control: Control may decrease because the activity is performed externally.
• Increased independence: The organisation becomes dependent on the supplier.
• Increased understanding of the outsourcing business: The internal organisation usually has greater business knowledge; the provider may initially lack it.
• Increased confidentiality: Sharing financial information externally may create confidentiality risks.
• Internal expertise improved: Outsourcing can reduce opportunities to develop internal finance skills.

• SQL injection (SQLi): Attacks databases by inserting malicious SQL commands.
• Cross-site scripting (XSS): Injects scripts into web pages viewed by other users.
• Sideloading: Installing an application from outside the official app store. It may install unauthorized apps, but it does not generally unlock the operating system or enable restricted system features.