Avixa AVIXA-CTS Exam Prep
Certified Technology Specialist (Page 4 )

• Each driver: Z = 8 O.
• If drivers are in series, impedances add: Z_series = Z1 + Z2 + ... = 8 × (number in series).
• If drivers are in parallel, impedances combine as: 1/Z_parallel = 1/Z1 + 1/Z2 + ...; for identical drivers: Z_parallel = 8 O ÷ (number in parallel).
• For mixed arrangements, reduce step by step (combine small groups first, then combine those results).

• Four pairs in parallel, with the four pairs in series: each pair = 8||8 = 4 O; four in series ? 4 × 4 O = 16 O.
• Two banks of four in parallel, connected in series: each bank = 8||8||8||8 = 2 O; in series ? 2 O + 2 O = 4 O.

• 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.

• VLAN 10 for data
• VLAN 20 for voice

• A: Describes physical trunking or logical switch ports, not an SVI.
• B: An SVI can provide management access, but that is only one use—not the best description here.
• D: SVI use is not related to running out of physical ports.

• C — Create a form extension and implement validation

• D — Use Chain of Command (CoC) with a form extension class

• Reporting relationships
• Organizational structures
• Leadership styles
• Team maturity
• Individual and group behavior
• Communication and motivation

• Acquire Project Team: Focuses on obtaining the people needed for the project.
• Develop Project Team: Focuses on improving team skills, relationships, and performance.
• Manage Project Team: Focuses on tracking performance, resolving issues, and managing changes within the team.

• 10 minutes have elapsed, or
• 20 MB of accounting data has accumulated

• Customers may boycott V’s products.
• Supermarket customers may stop buying from V.
• Investors may view V as having higher legal, ethical and reputational risk.
• V could face fines, lawsuits, contract losses and higher costs.
• Expected future profits may fall.

• Form layout
• Related lists
• Dictionary settings
• UI policies
• Client scripts
• Views and field visibility

• Personalization usually affects only the individual user.
• System configuration can affect other users, depending on its scope and conditions.

• Honeypots: Deliberately vulnerable or attractive systems designed to lure attackers. Legitimate users should not access them, so activity on a honeypot is a strong indicator of compromise.
• DNS sinkholes: Redirect requests for known malicious domains to a controlled internal system instead of allowing the connection. This can identify infected hosts attempting to contact command-and-control infrastructure.

• Tokenization: Replaces sensitive data with non-sensitive tokens; it protects data but does not primarily detect attackers.
• CI/CD: Automates software development and deployment processes.
• Threat modeling: Identifies potential threats and weaknesses before or during system design.
• Data obfuscation: Makes data harder to understand, but it is not an attacker-detection method.

• Layer 1: Check cables, power, and link lights.
• Layer 2: Check switching, VLANs, and MAC learning.
• Layer 3: Check IP addressing, routing, and gateways.
• Higher layers: Check services, applications, and user settings.

• Create a plan of action: Decide how to implement the fix.
• Implement the solution: Apply the selected fix.
• Verify functionality: Confirm the problem is resolved and systems work normally.

• Fine-tuning requires a properly formatted training dataset.
• For classification or instruction-style fine-tuning, examples are supplied in JSONL format.
• Each line represents one training example, typically containing the input prompt and the desired completion or label.
• The file must then be uploaded or made available to the Microsoft Foundry fine-tuning workflow.

• A: Prompt Flow is useful for prompt experimentation, but it is not required to start fine-tuning.
• B: You do not need to deploy the base model to an online endpoint before fine-tuning.
• C: Tracing supports observability and evaluation, but it does not prepare the fine-tuning job or dataset.

1. Append Table1 and Table2 as a new query

1. Select the product column in the appended query.

1. Choose Remove Rows > Remove Duplicates

• Matching hashes: The software is likely unchanged.
• Different hashes: The software or its contents have been modified.

• Encryption: Protects confidentiality, not primarily integrity.
• Baselines: Document expected configurations and support comparison, but hashing is more directly suited to verifying file integrity.
• Tokenization: Replaces sensitive data with tokens and is unrelated to software tampering.

• 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.

• Minimum and maximum values
• Number of distinct values
• NULL information
• Other metadata used for pruning

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

• state preserves the client’s original context, such as the specific idea URL the user requested.
• The portal sends that value in the OAuth authorization request.
• Salesforce returns it after authorization, allowing the portal to redirect the user to the original idea rather than the Ideas home page.

• ?? ?? ?? ??
• ?? NFS ?? SMB ?? ??
• ?? ???? ???
• ?? IP ??? ???? ?? ???
• ??? ?? ???? ?????

• B: ????? NFS ? Snowball Edge? ?? ?? ? AWS? ?? ? S3
• D: ????? NFS ? ????/Direct Connect ? File Gateway ? S3

• Reduce the training data: Usually makes overfitting worse.
• Add hyperparameters: Hyperparameters already control training; simply adding them does not solve the problem. Proper tuning could help, but that is not what the option states.
• Increase training time: More training can worsen overfitting if the model is already memorizing the training data.

• Deterrent control: The signs warning people they may be filmed discourage unauthorized or malicious behavior. They may prevent incidents by influencing behavior, but their primary purpose is to deter.
• Detective control: The CCTV system monitors and records activity so security personnel can identify suspicious or unauthorized actions.

• Preventive: Blocks or prevents an incident, such as a lock or access-control system.
• Corrective: Fixes or restores systems after an incident.
• Directive: Tells people what they must do, typically through policies or procedures.
• Compensating: Provides an alternative control when the preferred control cannot be used.

• C: Develop the rule in the Rules Editor, define the events, match, and condition sections, then use the test rule feature. This directly validates the YARA-L rule without enabling it in production.
• A: UDM Search can help investigate data and refine filters, but it does not fully test YARA-L logic—especially complex event joins, match windows, and conditions.

• User-generated content: precisa ser coletado, filtrado, anonimizado e rotulado.
• Moderation logs: podem conter dados inconsistentes, informações pessoais e decisões que precisam ser revisadas.
• Content moderation guidelines: são regras ou orientações, não dados diretamente utilizáveis para medir o comportamento do modelo.

• Data Cloud combines data from multiple systems.
• It resolves and organizes that data into a unified customer view.
• That unified view enables downstream actions such as personalized campaigns, segmentation, analytics, and activation.

• A = core platform value
• D = a resulting business use case or benefit

• On VirtualNetworkA: enable Allow gateway transit.
• On VirtualNetworkB: enable Use remote gateways.

• Process Builder: Automates actions based on record changes; it does not create interactive user forms.
• Approval Process: Routes records for approval and captures approval decisions.
• Outbound Message: Sends information to an external system; it does not provide a user interface.

• \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.

• Where to find the TiMOS runtime image
• Which configuration file to load
• The IP address and related settings for the CPM management Ethernet port

• A: User authorization is configured in the router’s security configuration, not primarily in the BOF.
• C: Hardware initialization is performed by the boot process and system software.
• D: The system date and time are configured separately, often through NTP or CLI settings.

• SQL injection
• Cross-site scripting (XSS)
• Malicious or malformed web requests
• Some application-layer attacks

• Layer 4 firewall: Filters based mainly on IP addresses, ports, and transport protocols; it cannot deeply inspect web application content.
• NGFW: Provides advanced network filtering and may include application awareness, but a WAF is more specifically designed to protect web applications.
• UTM: Combines several security functions in one appliance, but it is not the most targeted solution for a web portal.

• Storage usage of files stored in Microsoft Teams: SharePoint site usage report

• Number of active users per team: Microsoft Teams usage report

1. SharePoint site usage report
2. Microsoft Teams usage report

• The server accepts unauthenticated image uploads, which creates an opportunity for an attacker to upload a malicious script disguised as an image or using an unexpected file type.
• A web shell is a malicious script placed on a web server that gives an attacker remote command execution through web requests.
• The suspicious process and outbound connection to a low-reputation IP are consistent with the attacker using the web shell to execute commands or establish communication with command-and-control infrastructure.

• Worm: Usually self-propagates across multiple systems; the scenario focuses on the upload page.
• Cryptocurrency mining: Possible, but there is no indication of resource-intensive mining activity or insider involvement.
• Rootkit Trojan over RDP: The evidence points to the vulnerable upload functionality, not an exposed RDP service.

• Malware or malicious software
• Command-and-control tools
• Internet surveillance and intrusion software

• ITAR: A U.S. regulation controlling defense-related articles and services; it is not the international arrangement described.
• Palermo Convention: Focuses on transnational organized crime and related protocols, not export controls for cyber weapons.
• GDPR: European data-protection and privacy legislation.

• 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.

• 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.

DAX 
Previous Year Sales = 
CALCULATE( 
    [Total Sales], 
    PARALLELPERIOD('DATE'[Month], -1, YEAR) 
)

• CALCULATE evaluates [Total Sales] after modifying the filter context.
• PARALLELPERIOD shifts the current date period. -1 moves it backward, and YEAR specifies a one-year shift.
• 'DATE'[Month] is the date column used for the time calculation. In a proper date table, this should be a real date column or an appropriate calendar column—not merely text such as "January".

• A single summarized value, such as total annual sales
• Progress toward a defined target or goal
• Whether performance is below, near, or above the target

• Table: Displays detailed records or summarized rows, but not goal progress visually.
• Stacked Bar: Compares multiple categories and their parts.
• Donut: Shows how a total is divided among categories, not progress toward a target.

• 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.

• A. Periodically rotate responsibilities: May reduce some risks, but it does not directly detect unauthorized changes.
• B. Review segregation-of-duties conflicts: Identifies incompatible access combinations, not whether a specific data change was unauthorized.
• C. Log changes in an outside application: Logs provide evidence, but someone must review and analyze them. Logging alone does not detect misuse.
• D. Independent review: Directly detects unauthorized changes and reduces the risk that the person making the change can conceal it.

• File policy in Microsoft Defender for Cloud Apps: Can detect activity involving files, but it is not designed specifically to investigate risk from departing or deleted users.
• Access review policy in Microsoft Entra: Reviews whether users should retain access to resources; it does not detect historical document downloads.
• Alert policy in Microsoft Defender for Office 365: Primarily handles alerts for email and collaboration threats, not insider-risk investigations involving departed users.

• Lower order numbers appear first.
• For example, a variable with order 100 appears before one with order 200.
• The Sequence field is not the control used for catalog variable display order.
• The Default Value sets a value, not placement.
• The Choice field defines selectable options, not the variable’s position.

• One network address
• Two usable host addresses—one for each router
• One broadcast address

• Router A: 10.2.1.1
• Router B: 10.2.1.2

• Driver node: Coordinates Spark jobs and runs in the compute environment.
• Worker node: Executes tasks and processes data.
• Databricks Filesystem (DBFS): Provides storage access for data used by compute resources.

1. Create Workspace2 with Lakehouse2 — F
2. Migrate the Employee table to Lakehouse2 — E
3. Assign the data engineer the Contributor role for Workspace1 — D

Why

• Sharing Lakehouse1 would not provide the required isolation.
• Viewer access would not allow writing to Customer.
• Giving Contributor access to Workspace2 would expose the sensitive table.

• SAS (Serial Attached SCSI):

• SSD (solid-state drive):

• Unrestricted data mining: Data mining is not automatically a privacy violation. It becomes an issue when personal data is collected or used improperly.
• Identity theft: This is a possible consequence of inadequate privacy protection, but it is not the central focus of privacy regulations.
• Human rights protection: Privacy can be considered a human right, but this option is broader than the specific regulatory focus.
• Identifiable personal data: Regulations such as HIPAA focus directly on controlling the collection, use, disclosure, and protection of personal information.

• Link-local — FE80::/10; valid only on the local link/subnet and not routed by routers.
• Multicast — FF00::/8; identifies a group of interfaces rather than a private address range.
• Global unicast — 2000::/3; publicly routable IPv6 addressing.

• CBWFQ (Class-Based Weighted Fair Queuing): Creates traffic classes and assigns each class a guaranteed bandwidth or queueing treatment.
• PQ (Priority Queuing): Uses multiple queues with strict priority. Higher-priority queues are serviced before lower-priority queues, making it useful for delay-sensitive traffic—but it can starve lower-priority traffic.

• FRTS: Traffic shaping for Frame Relay; it controls the transmission rate rather than selecting packets during congestion.
• CAR: Polices traffic by rate, typically dropping or remarking packets that exceed a limit.
• PBR: Policy-Based Routing; it selects forwarding paths and is not a QoS queueing mechanism.

• nmap - 10.11.1.130 — a network scanning command; mitigated with controls such as firewalls, monitoring, or access restrictions.
• “Click this link to get your free gift card.” — a phishing or social-engineering message; addressed through user awareness, email filtering, and authentication controls.
• “Your connection is not private.” — indicates a certificate or TLS validation problem; addressed by correcting the certificate or secure-connection configuration.

• FTP — Transfers files using a client/server model and supports authentication. It uses separate control and data connections.
• TFTP — A very simple file-transfer protocol with no authentication and minimal features. Commonly used to transfer router or switch configuration files and IOS images.
• SCP — Securely copies files over SSH. It provides encryption and authentication.
• SFTP — Also transfers files securely through SSH, but provides more file-management capabilities than traditional SCP.
• HTTP/HTTPS — Primarily web protocols, but can also download files; HTTPS encrypts the session.

• TFTP = simple, unauthenticated file transfer
• FTP = file transfer with authentication, but not inherently encrypted
• SCP/SFTP = secure file transfer using SSH

• Amazon EC2 instances — ???????? ?? ?? ??????? CPU, memory ??? instance size ???????? ???????
• AWS Lambda functions — memory configuration ?????????? ???????
• Amazon EBS volumes — volume type ?? size optimize ???? ???????
• ??????? ECS workloads — resource configuration ? cost optimization-?? ???????

• Memory ? compute usage ?????????? ???? custom code ????? ???? development ? maintenance ??????
• Cost allocation tags ???? ????? ??? ?????? ???? ??????? ???; inefficient resource ??????? ?? recommendation ???? ???
• CloudTrail resource ???? ?? API activity ??????, resource utilization ????