Salesforce ADX-201C Exam Prep
Administrative Essentials for New Admins in Lightning Experience + Certification (Page 22 )

• Compensating control: The server is end-of-life, so it may no longer receive security patches or support. Placing it on a restricted VLAN provides an alternative layer of protection by reducing who can access it and limiting its exposure.
• Technical control: VLAN segmentation and access control lists (ACLs) are technology-based mechanisms that enforce network access restrictions automatically.

• Managerial: Policies, procedures, and governance—not network configuration.
• Physical: Locks, guards, or barriers.
• Corrective: Restores systems after an incident.
• Detective: Identifies suspicious activity rather than restricting access.
• Deterrent: Discourages behavior but does not enforce access rules.

• The user starts in the corporate portal.
• The portal launches the Salesforce resource.
• The IdP sends the SAML response to Salesforce.

• Connected App + OAuth is for OAuth authorization and API/app access, not this SAML-based seamless login scenario.
• SP-initiated SSO would begin when the user first requests the Salesforce resource and Salesforce redirects them to the IdP. That is not the described starting point.

• 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.

• 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.

text 
heartrateheartrateheartrate

• Spark column objects can be multiplied, for example:

python 
  df["heartrate"] * 3

• A DataFrame itself cannot be multiplied, but the expression is referring to a column.
• It is also not primarily a Python syntax error; the code was parsed, then Spark failed while resolving the column name.

• Tactics: The attacker’s overall goal, such as gaining persistence or exfiltrating data
• Techniques: The methods used to achieve that goal
• Procedures: The specific implementation or sequence of actions

• IP addresses and hash values: Useful indicators, but they can change quickly.
• Indicators of compromise: TTPs may help identify IOCs, but their main value is describing behavior.
• Tools: Attackers can replace tools or use legitimate administrative utilities.

• MAC flooding: Overwhelms a switch’s MAC address table, potentially causing traffic to be broadcast.
• DNS spoofing: Provides false DNS responses to redirect users.
• ARP poisoning: Sends false ARP information to associate an attacker’s MAC address with another device’s IP address.

• 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.

• B: Trigger.Once + scheduled job

• C: 10-minute processing-time trigger

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

• Remote and global access: Employees can authenticate from anywhere, not just a specific location.
• Seamless login: The device can authenticate in the background, reducing repeated password or MFA prompts.
• Minimal equipment: It uses devices employees already have, rather than requiring separate hardware.

• Geotagging: Identifies location but is not a complete authentication method and can be spoofed.
• Smart cards: Can provide strong authentication, but require cards and often readers, adding equipment and user steps.
• Time-based logins: Restrict access by time but do not verify the user or device adequately.

1. Get Data ? Folder in Power BI Desktop.
2. In Power Query Editor, expand the Attributes column to expose metadata such as hidden status and other file attributes.
3. Remove the Content column (and any other data columns you do not need).

• Name
• Extension
• Date accessed
• Date modified
• Folder Path
• Attributes
• Content

• Subject: The entity that initiates an action—here, Derrick/user account.
• Object: The resource being accessed— the file.
• Action: Reading the file.

1. Convert text and images into numerical embeddings.
2. Store or compare those embeddings.
3. Retrieve the most semantically similar items.

• Embedding model: Best for similarity search and retrieval.
• Generation model: Best for producing new text or other content from multimodal input.

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

• 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]

sql 
SELECT COUNT(*) FROM table;

• A: It does not normally need to scan all data files for this operation.
• B: Results are not simply reused from a query cache every time. Caching is separate from Delta’s metadata optimization.
• D: The relevant metadata is maintained through the Delta transaction log, not directly treated as a Parquet-file metadata operation in this context.

• Encryption to preserve confidentiality
• Integrity protection to detect alteration
• Authentication of the server through certificates

• SHA-256: A hashing algorithm; it does not encrypt data for transmission.
• SSL 3.0: Obsolete and insecure. It should not be used.
• AES-256: A strong encryption algorithm, but by itself it does not provide the complete secure communication protocol needed for data in transit.

• 10 TB with maximum I/O performance: Use EC2 instance store. It provides very high-throughput, low-latency local storage suitable for temporary video-processing data. The application must tolerate data loss because instance store is ephemeral.
• 300 TB of highly durable media: Use Amazon S3, which is designed for highly durable object storage and can scale to this size.
• 900 TB of inactive archival media: Use S3 Glacier, which provides lower-cost storage for data that is rarely accessed.

• A: Amazon EBS offers high performance but is not the best fit for the question’s “maximum possible I/O” requirement compared with local instance store.
• B: Amazon EFS is durable and shared, but is generally more expensive and less suitable for very large archival storage.
• C: Uses EC2 instance store for performance, but incorrectly uses EFS for the 300-TB durable tier and S3 rather than Glacier for archival data.

1. Create or verify cost groups

1. Set up the item model group

1. Create the costing version

1. Enter or calculate item costs

1. Activate the standard costs

• Input feature distributions differ from training data ? Analyze dataset drift metrics

• Model accuracy drops without code changes ? Analyze dataset drift metrics

• Endpoint latency increases under load ? Investigate scaling and infrastructure metrics

• A — Too infrequent: Formal strategies are often reviewed only every three to five years. This can make the organisation slow to respond to rapid changes in technology, competitors, regulation or customer needs.

• C — Relies on predicting the future: The approach assumes senior managers can make reasonably reliable forecasts and assumptions. In uncertain environments, these assumptions may quickly become invalid.

• E — Can restrict radical innovation: Formal planning tends to favour existing information, established objectives and incremental improvements. This may discourage experimental or highly innovative strategies that emerge from lower levels of the organisation.

• B concerns the difficulty of achieving competitive advantage through core competences when competing with focused specialists. It is not specifically a drawback of the formal top-down planning process.
• D is an activity organisations should undertake—continuous monitoring—not a drawback of the approach itself.

kusto 
Event | where EventType == "error"

• == is the KQL equality operator.
• -eq is a PowerShell operator, not KQL.
• is is not the correct equality operator in this context.

text 
Event | where EventType –eq "error"

• Event | search "error" — valid, broad search.
• search in (Event) "error" — valid, broad search.
• Event | where EventType == "error" — valid, targeted filter.

• The inference container image or built-in algorithm
• The location of model artifacts in Amazon S3
• IAM permissions through the execution role
• Optional environment variables and networking settings

1. Create AWS::SageMaker::Model
2. Create an AWS::SageMaker::EndpointConfig that references the model
3. Create AWS::SageMaker::Endpoint that references the endpoint configuration

• AWS::SageMaker::Endpoint hosts a model but does not define the model itself.
• AWS::SageMaker::NotebookInstance provides a development environment.
• AWS::SageMaker::Pipeline orchestrates ML workflow steps.

• Planning and designing products and services
• Developing and delivering them
• Managing risks, suppliers, and resources
• Measuring performance
• Continually improving value delivery

• Value stream steps describe activities used to create and deliver value; they do not themselves provide the broader capabilities.
• Vision and operating model provide direction and structure, but they are not the practical management capabilities that enable the work.
• Value chain is the operating model showing how activities combine to create value; it is enabled by practices and resources.

• Identified risks
• Risk owners or responsible parties
• Likelihood and impact
• Risk response plans
• Current status
• Risk thresholds or trigger conditions

• Risk tolerance: The amount and type of risk an organization is willing to accept; it is not primarily a tracking document.
• Risk transfer: Moving the financial or operational impact of a risk to another party, such as through insurance or outsourcing.
• Risk analysis: The process of evaluating a risk’s likelihood and impact.

• The identified risk
• Its likelihood and potential impact
• The person or team responsible for handling it
• The response or treatment plan
• Risk thresholds, such as when escalation or action is required
• Current status and review dates

• Risk tolerance: The amount of risk an organization is willing to accept; it is a concept or limit, not usually the primary documentation.
• Risk transfer: Moving the responsibility or financial impact of a risk to another party, such as through insurance.
• Risk analysis: The process of evaluating risk likelihood and impact.

• 16GB RAM: A 64-bit OS is needed to use more than roughly 4GB effectively, but RAM capacity does not prove the CPU supports 64-bit operation.
• 500GB HDD: Storage capacity has no bearing on OS architecture.
• 1Gbps Ethernet: Network speed is unrelated to CPU architecture.

Correct choices

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

Why

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

• Issuer: Identifies the party issuing a SAML message—usually the identity provider in the assertion. It is not the Salesforce-specific identifier the architect should provide for differentiating Salesforce.
• Identity Provider Login URL: The endpoint where users are sent to authenticate.
• SAML identity location: Determines where the user identity is found in the SAML assertion, such as the subject or an attribute.

• IaaS: You manage the virtual machine’s operating system, configuration, applications, and data. Azure manages the physical infrastructure and virtualization platform.
• PaaS: You deploy applications without managing the underlying operating system or servers.
• SaaS: You consume a complete application managed by the provider, such as Microsoft 365.

• vBond — orchestration plane: Authenticates devices, helps them discover each other, and assists with NAT traversal and initial control-connection setup.
• vSmart — control plane: Distributes routing and policy information to WAN Edge devices using the overlay control plane.
• vManage — management plane: Provides centralized configuration, monitoring, and orchestration through its GUI/API.
• WAN Edge — data plane: Forwards user traffic across the SD-WAN fabric.

• The listener has a virtual IP address on the load balancer.
• The active SQL Server replica must respond using the listener’s IP address, not its own VM IP.
• Floating IP allows the listener IP to be preserved and returned by the active replica.
• This is required for the SQL Always On listener configuration.

• A health probe for the SQL listener/cluster role
• The SQL Server listener port, commonly 1433
• Appropriate backend pool membership

1. Modify the database subnet NACL inbound rules to allow traffic from the new web subnet’s CIDR block on the MySQL port (3306).
2. Modify the database subnet NACL outbound rules to allow return traffic to the new web subnet’s CIDR block on the required ephemeral port range.

• SOW
• SLA
• MOA
• MOU

• A laptop
• Software access
• A password reset
• A mobile phone

• They run behind the scenes — applies more to automation or workflows.
• They are optional — catalog items are fundamental to a request-based catalog.
• They provide options — variables and variable options collect the requester’s choices for an item; they are not the catalog item itself.

• Microsoft 365 groups can contain users, but generally can’t contain other groups as members.
• Security groups can contain users and, where supported, other security groups.
• Distribution groups have different nesting restrictions and aren’t equivalent to security groups.
• Dynamic groups can’t be manually populated with members; their membership is calculated from rules.
• A group’s membership type (Assigned or Dynamic) and group type determine whether it can be added to another group.

• A Layer 2 switch checks the destination MAC address in its MAC address table (CAM table).
• If the destination MAC is unknown, the switch cannot select a specific outgoing port.
• It therefore performs unknown-unicast flooding, sending the frame out every other port in that VLAN.
• The frame is not sent back through the port where it arrived.

• A larger question bank with verified answers
• Explanations tied to ISACA exam domains
• Current content aligned with the exam blueprint
• Useful review or progress features

• Discovers sensitive data in Amazon S3 buckets
• Uses machine learning and pattern matching to identify data such as personally identifiable information (PII)
• Helps assess S3 security and privacy risks
• Generates findings for potentially sensitive or exposed data

• Amazon Detective: Investigates security findings and performs root-cause analysis.
• Amazon GuardDuty: Detects threats and suspicious activity across AWS accounts and workloads.
• AWS IAM Access Analyzer: Identifies resources that are accessible from outside their intended trust zone, such as publicly accessible S3 buckets.

• tag=Priv searches the tag field for values beginning with Priv. The wildcard can match the remaining characters, so it matches Privileged.
• tag=Priv would search for the exact tag Priv, not Privileged.
• tag=priv* uses lowercase priv; tag matching is treated as case-sensitive here, so it may not match the tag Privileged.
• tag=privileged uses the wrong capitalization for the exact tag.

• Modelo de embeddings multimodal: transforma texto e imagens em vetores no mesmo espaço semântico. Isso permite comparar uma consulta textual com imagens, ou uma imagem com textos relacionados.
• Modelo generativo multimodal: interpreta diferentes modalidades e gera conteúdo, mas não é a escolha específica para indexação e busca vetorial.
• Modelo de geração de imagens: cria imagens, portanto é inadequado.
• Modelo de embeddings de texto: não atende consultas com imagens.

• 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.

1. Identify the fact table

• Records something that happened, such as a sale, test, appointment, or measurement
• Contains foreign keys to other tables
• Contains measures or numeric results
• Has many rows

2. Identify a dimension table

• Describe people, products, dates, locations, or departments
• Contain descriptive columns
• Are referenced by the fact table
• Have fewer rows than the fact table

3. Identify the surrogate key

• System-generated
• Unique within the dimension
• Often named PatientKey, CustomerKey, or similar
• Usually an integer
• Not meaningful outside the model

• Idioma: “Responda em português.”
• Tamanho: “Responda em até três frases.”
• Formato: “Use uma lista com três recomendações.”
• Objetivo: “Recomende produtos com base nas necessidades do cliente.”

• Mudar o tamanho do LLM: pode alterar capacidade e custo, mas não garante idioma ou respostas curtas.
• Aumentar a temperatura: aumenta a criatividade e a aleatoriedade; não controla diretamente o tamanho ou idioma.
• Aumentar o Top K: permite considerar mais tokens prováveis, aumentando a variedade; também não é o mecanismo principal para controlar idioma ou comprimento.

• Threat perspective: Focuses on possible attacks, but may seem technical or hypothetical.
• Compliance perspective: Can motivate action, but compliance alone does not demonstrate the broader business value of governance.
• Policy perspective: Policies are important, but they are a means of implementing governance, not its primary business justification.

• Disable default accounts: Default or unused accounts may have predictable names or credentials and can be abused by attackers. They should be disabled, removed, or secured with strong credentials where necessary.
• Remove unnecessary services: Every running service can contain vulnerabilities or provide an entry point. Removing services the server does not need reduces exposure.

• Add the server to the asset inventory: Important for asset management, but it does not directly harden the system.
• Document default passwords: Default passwords should be changed or disabled—not recorded for continued use.
• Send logs to the SIEM: Supports monitoring and detection, rather than directly reducing the attack surface.
• Join the corporate domain: A deployment/configuration decision, not inherently a hardening measure.

• 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.

• The application failing to start or becoming unhealthy
• An incorrect probe path, port, or protocol
• The application needing more startup time
• Dependency or configuration failures
• A liveness probe being too aggressive

bash 
kubectl describe pod <pod-name> 
kubectl logs <pod-name> --previous

• Scale to more replicas: may hide the issue but does not diagnose it.
• Decrease initialDelaySeconds: makes probes run earlier and could worsen startup failures.
• Drain and reboot the node: node metrics are normal, so rebooting is not justified as the first step.

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