IIBA CCBA Exam Prep
Certification of Competency in Business Analysis (Page 37 )

• To mitigate resistance, the BA should directly engage the stakeholders who are pushing back (the technical team) to uncover their concerns, constraints, and reasons for resisting the end-of-project handover.
• This enables collaborative problem-solving and may lead to adjustments (e.g., intermediate deliverables, phased rollouts, or alignment of acceptance criteria) that satisfy both business and technical needs.
• Escalating to the sponsor or emailing the business team may not address the root causes of resistance. Reassessing objectives could be useful later, but the immediate best practice is to have a targeted discussion with the technical team to understand and resolve concerns.

• Job shadowing is an elicitation technique that is part of the broader job observation approach. The observer watches workers perform tasks (either passively or actively) to understand the workflow, especially when the worker cannot articulate the process themselves.
• The other options are not elicitation techniques tied to job observation: A) Identifying stakeholders is an initial BA activity; C) Defining and determining business analysis processes is part of planning; D) Planning how requirements will be approached, traced, and prioritized is elicitation planning (a precursor to elicitation), not the observation-based elicitation.

• There are two solutions: A is worth $456,000 to the organization, B is worth $565,000.
• Management chooses A due to lower cost, less risk, and faster completion.
• The opportunity cost is the value of the best alternative that was not chosen. Since B has the higher value ($565,000) and wasn’t chosen, the foregone value is $565,000.
• Note: The \(|565k - 456k| = 109k\) is the difference in value, not the opportunity cost.

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

• PC A: 192.168.1.10/24
• PC B: 192.168.2.10/24

• Both PCs have a correct default gateway
• A router or Layer 3 switch connects the subnets
• Routing and firewall rules allow the traffic

• Security controls
• Processes and procedures
• Compliance evidence
• Performance against contractual requirements

• Service-level agreement (SLA): Defines expected service performance, such as uptime and response times.
• Memorandum of agreement (MOA): Documents a general agreement between parties, but does not necessarily provide audit rights.
• Supply chain analysis: Identifies risks across suppliers and dependencies, but is not a contractual mechanism for reviewing vendor controls.

Manager role

DAX 
Country[Manager] = USERPRINCIPALNAME()

• Sales
• Human Resources

CFO role

• See sales for all countries
• See no Human Resources data

• Do not restrict the Country table or Sales table.
• Apply a filter to Human Resources that always returns false, such as:

DAX 
FALSE()

• Sustainability
• Performance efficiency
• Reliability

• Deterrent control: The signs warning that people may be filmed can discourage unauthorized or malicious activity. They do not directly stop the action; they influence behavior.
• Detective control: CCTV records or monitors activity so security personnel can identify events or investigate them afterward.

• Preventive: Stops an incident from occurring, such as access control.
• Corrective: Restores systems after an incident.
• Directive: Instructs people to behave in a certain way, such as a security policy.
• Compensating: An alternative control used when the preferred control is not feasible.

• Each Case must follow defined support steps.
• Each step must be completed within a specified time limit.

• Case Escalation Rules: Escalate Cases based mainly on age or criteria; they do not model a complete sequence of service steps.
• Process Builder with Scheduled Actions: Can automate time-based actions but is not the standard framework for Case service-level commitments.
• Omni-Channel Routing: Routes work to agents based on capacity and priority; it does not track Case lifecycle deadlines.

• 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.

• Company documents
• Databases
• Knowledge bases
• Current web or business data

• A: Describes diversity and inclusive design, not grounding.
• B: Describes explainability or model interpretability.
• D: Describes documenting a model’s capabilities and limitations.

• Sales revenue is affected because internal sales are recorded at the transfer price.
• Operating profit is affected because revenue changes while costs may remain unchanged.
• Return on investment (ROI) is affected because ROI depends on operating profit and the division’s investment.
• Cost of components purchased is not affected by the transfer price. These are costs incurred when buying components from external suppliers, not the internal price charged for the division’s output.

• 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.

• Custom domains are supported.
• It provides dedicated compute instances.
• It offers enough storage for the applications.
• It supports multiple instances with load balancing between them.
• It is less expensive than higher tiers such as Premium.

• Free and Shared use shared compute and have limited storage, so they cannot meet the dedicated-instance requirement.
• Basic provides dedicated compute and custom domains, but the question’s requirement for the broader multi-instance/load-balancing capability is intended to point to Standard.

• Allow only approved MAC addresses
• Limit the number of learned addresses
• Shut down or restrict a port when a violation occurs

• Load balancer: Distributes application traffic; it does not protect switch MAC tables.
• IPS: May detect some attack traffic, but it is not the direct control for limiting MAC addresses on switch ports.
• NGFW: Filters routed network traffic, while this attack targets Layer 2 switch behavior.

• B — The most significant risks are held by SQ.

• C — SQ should recognise the cars as inventory.

• F — SQ recognises revenue when LM sells a car to a third party.

• A: LM does not hold the most significant risks.
• D: LM does not recognise the cars as inventory.
• E: SQ should not recognise revenue when cars are merely delivered to LM.

• JobTitle: User1 and User3 only
• UsageLocation: User1, User2, and User3

• For a user whose source of authority is Windows Server Active Directory, attributes such as JobTitle are synchronized to Microsoft Entra ID. You must change them in on-premises AD; editing them in Entra ID is not allowed or will be overwritten.
• UsageLocation is a cloud-managed attribute used mainly for licensing and service availability. It can be set or changed in Microsoft Entra ID, including for synchronized users.

• 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.

• A — Capacity: The system must handle all current records and anticipated future records. A system that cannot cope with volume will quickly become ineffective.
• C — Accuracy: Academic records are critical, so the new system must be at least as accurate as the existing system and comparable systems. Poor accuracy could cause serious administrative and reputational problems.
• D — Integration: Linking with the university’s financial systems supports consistency and avoids duplicate data entry, especially for registration, deregistration and fee-related transactions.

• B — Parallel running: This is a useful implementation and risk-control technique, but it is not an essential feature of the system itself. It may also be expensive and time-consuming.
• E — Internet access for all information: This creates significant confidentiality and security risks. External access might be needed for selected services, but unrestricted access to all information is not essential and would be inappropriate for student records.

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.

• Power BI dataset — Reuses the existing tables, relationships, and measures. You mainly create new visualizations.
• SharePoint folder — Connects to the source files, but you would need to rebuild the model and measures.
• Power BI dataflows — Primarily provide reusable data preparation; they do not automatically provide the existing report’s measures and model.
• Excel workbook — Requires reconnecting to and modeling the source data again.

• User1 (user1@contoso.com) — This is an external guest in the Fabrikam tenant. Assuming the guest uses email one-time passcode authentication, Azure AD emails a passcode to user1@contoso.com.
• User2 (user2@outlook.com) — An Outlook.com address can authenticate with a Microsoft account, so Azure AD uses that account’s authentication rather than sending an email OTP. The fact that User2 has never accessed Fabrikam resources does not by itself trigger OTP.
• User3 (user3@fabrikam.com) — This is an internal Fabrikam user, so the user signs in with the organization’s normal credentials and does not receive a guest OTP.

• Distinct values = 69

• Unique values = 4

• /27 (255.255.255.224)

• /26 (255.255.255.192)

• /25: Creates only 2 subnets, not 3
• /28: Provides only 14 usable hosts per subnet

• 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.

• B — Data source settings in Power BI Desktop:

• D — Formula bar in Power Query Editor:

m 
  Excel.Workbook(File.Contents("new path"))

• E — Advanced Editor in Power Query Editor:

• A: Dataset settings in the Power BI service mainly handle credentials and gateway settings, not changing the local file path embedded in the PBIX.
• C: Current File data-load settings control refresh/load behavior, not the source location.

• Lead investigator: Coordinates the investigation and directs the response.
• Information security representative: Provides security expertise and helps assess the incident.
• Technical representative: Preserves system evidence, takes forensic backups, and supports technical analysis.
• Legal representative: Advises on legal, regulatory, privacy, and evidence-handling requirements.

• API tool matcher: runs a deterministic normalization command after the API tool returns.
• Write/Edit matcher: checks whether the target path begins with src/api/ and runs the linter.

json 
{ 
  "hooks": { 
    "PostToolUse": [ 
      { 
        "matcher": "api_tool", 
        "hooks": [ 
          { "type": "command", "command": "normalize-to-snake-case" } 
        ] 
      }, 
      { 
        "matcher": "Write|Edit", 
        "hooks": [ 
          { "type": "command", "command": "lint-if-under-src-api" } 
        ] 
      } 
    ] 
  } 
}

• Asynchronous inference is designed for applications that submit individual inference requests, place them in a queue, and retrieve results later. It is useful when requests may take a long time or when traffic is intermittent.
• Batch transform is designed specifically to run inference over an entire large dataset stored in Amazon S3 and produce an output dataset.

• Large dataset/offline processing ? Batch transform
• Large or slow individual requests processed later ? Asynchronous inference

• 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.

• 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.

1. Wireless AP

1. Router

1. Firewall

1. Device placement

• Share files with the wrong people
• Use public links unnecessarily
• Fail to classify sensitive data
• Upload data to unauthorized services
• Misunderstand company sharing policies

• A — Step-up authentication: Helps protect administrator accounts, but does not directly address improper file sharing by users.
• C — Password complexity: Helps reduce password attacks, not accidental data disclosure.
• D — Mobile device management: Secures managed mobile devices, but does not directly control file-sharing behavior across the organization.

• Shared capacity

• Fabric capacity — F SKUs

• Fabric trial capacity

• Existing Power BI Premium — P SKUs

• 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: \(\$10\)

• Which batches and markets are affected
• Whether the deficiency affects product quality, efficacy, or patient safety
• Whether the issue is an ongoing manufacturing problem
• Whether immediate containment or distribution suspension is needed

• A — Withdraw the product: may be necessary, but is premature before assessing the risk.
• B — “Dear Dr.” letter: may be appropriate later, depending on the risk.
• C — Notify global authorities: may become mandatory, but the scope and urgency depend on the assessment.

• 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.

• Accept: Acknowledge the risk and take no additional action.
• Transfer: Shift the risk or financial impact to another party, such as through insurance or a contract.
• Mitigate: Reduce the likelihood or impact using controls, such as firewalls, training, or backups.
• Avoid: Eliminate the activity that creates the risk.

• Accept: Acknowledging the risk without taking additional action.
• Transfer: Moving the risk’s financial impact to a third party, such as an insurer.
• Mitigate: Reducing the likelihood or impact through controls, such as patching or employee training.
• Avoid: Eliminating the activity that creates the risk.

• Disable high concurrency: Changes workspace-wide behavior and is not the targeted way to isolate these workloads.
• Modify the number of executors: Adjusts capacity and performance, but does not provide workload isolation.
• Set the default environment: Controls libraries and runtime configuration, not compute isolation.

• A — If there is no demand, there should be no production.

• B — Not all sales equal profit.

• C — Stocking up on inventory is bad for business.

• D — All costs, except materials, are considered fixed.

• E — Departments should operate at full capacity regardless of bottlenecks.

• Un AG puede tener réplicas en Windows y Linux desde SQL Server 2017; por tanto, una réplica Windows y otra Linux es posible.
• Sin embargo, las réplicas de un AG deben utilizar normalmente la misma versión principal de SQL Server. Una instancia SQL Server 2017 no puede tener directamente una réplica secundaria SQL Server 2019 como configuración normal y permanente.
• En tu escenario, SQL Server 2017 en Windows y SQL Server 2019 en Linux no se pueden añadir directamente como réplicas equivalentes de AG1. Primero habría que realizar un proceso de actualización/migración compatible, por ejemplo mediante una actualización gradual o una tecnología de migración como log shipping o distributed availability groups, según el diseño.

• Tipo de clúster y mecanismo de quorum.
• Failover normalmente manual en configuraciones multiplataforma.
• Edición y características compatibles.
• Configuración de endpoints y permisos.
• Limitaciones específicas de SQL Server en Linux.

• B: Prompt caching reduces cost and latency for repeated content, but cached content still occupies the context window. It does not solve context accumulation.
• C: Switching to a smaller model changes model capacity but does not address the growing context or remove irrelevant data.
• D: Keeping everything indefinitely increases token usage, risks context-window limits, and can distract the model with outdated information.

1. Discovery tries the SSH probe first.
2. SSH fails.
3. Discovery tries SNMP, which succeeds.
4. Discovery records SNMP as the preferred service for that IP.
5. Future discoveries try SNMP first.

• Classification identifies the type of device, such as a server, router, or printer.
• Credential affinity remembers which credentials work for a device.
• MID Server affinity associates a device or network with a particular MID Server.
• IP service affinity specifically controls the preferred discovery protocol or service.

• Amazon SageMaker — charges apply for compute, storage, and other resources used.
• AWS Config — generally charges for configuration recording and rule evaluations.
• Amazon CloudWatch — has a limited free tier, but many metrics, logs, alarms, and API usage can incur charges.

• Matching hashes: The software likely has not changed.
• Different hashes: The software was modified or corrupted.

• Encryption: Protects confidentiality by making data unreadable; it does not primarily detect changes.
• Baselines: Define an approved system or configuration state, but they are not the specific integrity mechanism here.
• Tokenization: Replaces sensitive data with substitute values.

• 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

• Advanced Persistent Threat (APT): A sustained, targeted attack campaign or attacker group—not a vulnerability.
• Trojan: Malware disguised as legitimate software.
• Stealthware: A general term for malware designed to avoid detection; it does not specifically mean an unknown vulnerability.