Talend Data-Integration-Developer Exam Prep
Talend Data Integration Certified Developer (Page 3 )

• The vulnerability scan identifies a vulnerability.
• The administrator verifies that the vulnerability is not present.
• Therefore, the scan produced a false positive.

• True positive: A vulnerability is reported and genuinely exists.
• False negative: A vulnerability exists, but the scan fails to detect it.
• True negative: No vulnerability exists, and the scan correctly reports no issue.

• Filtering harmful or inappropriate content
• Blocking specified topics
• Detecting and masking sensitive information
• Enforcing content policies suitable for children

• Amazon Rekognition analyzes images and videos; it does not control text generated by a language model.
• Amazon Bedrock playgrounds are for testing models and prompts, not enforcing production safety policies.
• Agents for Amazon Bedrock help models complete tasks and use tools; they do not primarily provide content-safety controls.

• Menerjemahkan soal ke bahasa Indonesia.
• Menyebutkan jawaban yang benar.
• Menjelaskan alasan jawaban tersebut.
• Memberi tahu jika kunci jawaban yang tersedia tampaknya keliru.
• Menjelaskan istilah teknis penting dalam soal.

• Assign endpoints to a group based on the result of one policy.
• Use that group as the scope of another policy.
• This effectively passes the endpoints from one policy’s processing flow to another.

• 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.

• contoso.onmicrosoft.com
• contoso1.onmicrosoft.com

• onmicrosoft.com domains: Maximum of five per tenant.
• Custom domains: Domains that your organization owns and verifies in Microsoft 365.

• CSIRT: A team that responds to and manages security incidents.
• CVSS: A scoring system for rating the severity of vulnerabilities.
• SOAR: A technology platform for automating and coordinating security operations and incident response.

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

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

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

• Bronze: Raw ingested data
• Silver: Cleaned, validated, and transformed data
• Gold: Business-level data for analytics, dashboards, and reporting

• SAS (Serial Attached SCSI):

• SSD (solid-state drive):

• A — Use a custom controller: An Apex class can contain the page’s logic.
• C — Use a standard controller with extensions: The standard controller provides basic CRUD behavior, while an extension adds custom logic.
• E — Use a standard controller: Useful when the page works mainly with one Salesforce object and needs standard functionality.

• A page with no controller for static or controller-free content.
• A custom controller with extensions; extensions are not limited only to standard controllers.

• 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.

• Confirming the data has the required columns and data types
• Handling missing or duplicate records
• Converting data into a suitable format
• Selecting or engineering useful features
• Splitting it into training, validation, and test sets

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

• Note the question number before leaving—for example, Question 38.
• Use the exam’s question navigator or Back/Previous button to return to that number.
• If you close or refresh the page, your position may not be saved, depending on the site. Reopen the page and select the question number again.
• Avoid using the browser’s Back button if it causes the exam page to reload; use the exam’s built-in navigation instead.

• JDBC
• SnowSQL
• Snowflake Web Interface (UI)
• ODBC
• Python connector

• Future costs — Only costs occurring in the future can be affected by the investment decision. Past costs are sunk and irrelevant.
• Incremental costs — These are additional costs caused by choosing the investment. They are relevant because they differ between alternatives.
• Cash flows — Capital investment decisions are based on future cash inflows and outflows, usually discounted to present value.

• Committed costs have already been agreed or incurred and generally cannot be changed by the decision.
• Unavoidable costs will arise regardless of which option is selected, so they do not affect the choice.

• B: Extending credit to customers increases receivables, so more cash is tied up in working capital.
• C: Replacing obsolete inventory does not reduce the overall inventory investment; it simply changes its composition.
• D: Paying suppliers earlier reduces payables. This uses cash and therefore increases the funds tied up in working capital.

• If the attachment is safe, it is released to the user.
• If malware is detected, the attachment is blocked or removed according to the policy.
• This reduces delivery delays without disabling malware scanning.

• Replace removes the original attachment and replaces it with a text file explaining that it was blocked. It does not primarily optimize delivery time.
• Block and Enable redirect blocks messages with suspicious attachments and can redirect them for review; it does not provide the required faster delivery experience.
• Monitor and Enable redirect is for observation and does not reliably block malicious attachments.

• Document feeder: A scratch, dirt, or debris on the feeder glass or rollers can create a line on every scanned image.
• Pickup rollers: Move paper through the printer; they would not normally create a scanner-only line.
• Corona wire: Affects toner charging and would cause defects on printed output.
• Drum assembly: Also affects printed pages, so faxes and computer print jobs would show the line too.

• B. Deploy to a SageMaker endpoint: This is needed for SageMaker-hosted models, not for a model intended to be used directly in Amazon Bedrock.
• C. Register with SageMaker Model Registry: SageMaker Model Registry is unrelated to invoking custom models in Bedrock.
• D. Grant access in Bedrock: Access permissions may be necessary, but they do not replace the required provisioned capacity.

• Honeypots: Decoy systems designed to attract attackers. Legitimate users should not access them, so activity there is a strong indication of unauthorized access.
• DNS sinkholes: Redirect requests for known malicious domains to a controlled internal destination instead of the real attacker infrastructure. Security teams can then identify infected systems making those requests.

• Tokenization: Replaces sensitive data with non-sensitive tokens; it protects data but does not detect intruders.
• CI/CD: Software development and deployment processes.
• Threat modeling: Identifies potential threats before or during system design, rather than detecting successful infiltration.
• Data obfuscation: Makes information harder to understand, but is not an attacker-detection mechanism.

• Azure Machine Learning Studio is designed to build, test, train, and deploy machine-learning models, including predictive analytics.
• Azure Cosmos DB is a globally distributed NoSQL database. It can store data used by an AI solution, but it is not the primary service for developing and deploying predictive models.
• Therefore, the appropriate recommendation is Azure Machine Learning Studio, as shown in Question 15.

• 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.

• Disable default accounts: Default or unused accounts may have known usernames or predictable settings, making them targets. They should be disabled, removed, or securely configured.
• Remove unnecessary services: Every running service creates potential vulnerabilities. Removing services the server does not need reduces exploitable entry points.

• Add the server to the asset inventory: Important for asset management, but not a hardening step.
• Document default passwords: Default passwords should be changed or eliminated—not documented for continued use.
• Send server logs to the SIEM: Valuable for monitoring and detection, but generally performed as part of logging/monitoring configuration.
• Join the server to the corporate domain: May be necessary operationally, but does not itself harden the server.

• B. Versioned configuration files — Infrastructure is defined in machine-readable files and tracked in version control, allowing repeatable provisioning and change history.
• D. Docker files — Assuming “Doctor files” is a typo for Dockerfiles, a Dockerfile declaratively defines how to build a container image and is commonly considered infrastructure/configuration as code.

• A. Cloned virtual machine images — These are prebuilt infrastructure artifacts, but cloning an image is not itself a code-based infrastructure definition.
• C. Change management database records — A CMDB records information about infrastructure; it does not define or provision that infrastructure.

• Tracking who accessed or changed customer information
• Detecting unauthorized activity
• Supporting accountability and investigations
• Providing evidence for compliance and incident response

• Single sign-on not enabled: SSO improves convenience and centralized authentication, but it is not essential for access control.
• Complex passwords not required: This weakens authentication, but other controls may reduce the risk.
• Security baseline not consistently applied: A concern, but it is less specific and less immediately damaging than having no activity records at all.

• A Screen Flow can present a form that inspectors complete and submit on an Experience Cloud page.
• It can collect inspection findings, validate the input, and create or update records.
• An Autolaunched Flow has no user interface, so it cannot directly provide the form.
• A Related List only displays related records, and Record Detail is primarily for viewing or editing an existing record—not for a custom inspection submission form.

• 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.

• Required response time
• Resolution time
• Availability or uptime
• Support hours
• Performance targets
• Consequences if targets are missed

• SOW (Statement of Work): Defines the project’s scope, tasks, deliverables, and schedule.
• MOA (Memorandum of Agreement): Describes the responsibilities and commitments between parties.
• MOU (Memorandum of Understanding): Documents a general mutual understanding or intent, often before a formal agreement.

• The JSON files contain one billion items, so this is a big-data workload.
• PySpark uses Apache Spark’s distributed, parallel processing, allowing the data to be processed across multiple compute nodes.
• It can read and transform data directly from OneLake, helping minimize unnecessary data movement or duplication.
• A Fabric notebook can also support exploration and visualization, as well as Spark-based analytics and anomaly-detection workflows.

• Pandas is primarily in-memory and generally suited to smaller datasets. One billion records would be impractical on a typical single machine.
• A Power BI report with core visuals is appropriate for visualization and sharing, but it is not the best tool for large-scale transformation, parallel processing, or anomaly detection. It would normally consume prepared data rather than perform the entire workload.

• 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.

• A — Windows 11 with Azure CLI installed: Yes

• D — Chrome OS using Azure Cloud Shell: Yes

• E — Windows 10 with the Azure PowerShell module installed: Yes

• B — Linux with only Azure CLI: No, because the option does not state that PowerShell is installed.
• C — macOS with PowerShell Core only: No, because it does not state that Azure PowerShell modules or Azure CLI are installed.

• A: CEO-sponsored formal policy — demonstrates executive support, but sponsorship at one point in time may not sustain commitment.
• B: Security awareness training — primarily improves employee behavior, not senior management commitment.
• C: Periodic alignment reviews — ongoing reviews show that security remains relevant, supports business priorities, and uses resources appropriately.
• D: Senior management signoff on the strategy — useful for governance and accountability, but signoff is generally a one-time event.

• Install unauthorized or unsupported software
• Access features blocked by the manufacturer or operating system
• Customize system behavior beyond normal settings

• A user connects with their Google account.
• Google associates the user’s SSH key with that identity.
• IAM roles determine whether they can log in.
• Access can be tied to a specific employee for auditing.
• Removing the IAM role removes their login access.

• compute.osLogin: regular OS login access
• compute.osAdminLogin: OS login with administrative privileges, typically including sudo

text 
enable-oslogin=TRUE

• 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" } 
        ] 
      } 
    ] 
  } 
}

• Warehouse size: Larger warehouses use more credits per unit of time than smaller ones.
• Number of clusters: A multi-cluster warehouse can run multiple clusters, and each active cluster consumes credits. Therefore, increasing the maximum or active cluster count can increase consumption.

• Number of users: More users may cause more workload, but users themselves do not consume credits.
• Amount of data processed: Snowflake warehouses are not charged directly by the amount of data scanned. However, processing more data may cause the warehouse to run longer, indirectly increasing credits.

• Orders contains order-level information, such as the order date.
• Order Line Items contains the products, quantities, and line amounts associated with each order.
• Merging them on the order key, such as OrderID, places the order date alongside each line item. This allows you to calculate total order value and analyze it over time.
• Product attributes can remain in the Products table and be related to the resulting line-item table through ProductID.

• Merging line items with products addresses product attributes but does not first provide the order-level date and value needed for time analysis.
• DAX calculated columns or lists add unnecessary model complexity.
• Calculating order counts is not the first requirement and does not combine the required order and line-item data.

Step 1: Calculate the rights issue price

Step 2: Calculate the number of new shares

Step 3: Calculate the value after the issue and project

• Rights issue proceeds: $21.6m
• Project NPV: $5m

Step 4: Calculate the theoretical ex-rights price

• HTTPS: Secure web traffic, not general command-line server administration.
• SNMPv3: Secure network monitoring and management, not interactive server login.
• RDP: Provides graphical remote desktop access. It can be secure, but it is not the direct replacement for Telnet in this scenario.
• SMTP: Used to send email.

• Containment policy: controls permitted communication during containment.
• Detection/response configuration: determines when containment is initiated.

CIMA P3 topics

• IT governance and systems strategy
• Systems development and implementation
• Change and project governance
• Strategic and business risk

• A — Plan for new systems: The committee should help identify and prioritise systems requirements and ensure planned systems support organisational needs.
• D — Consider competitive issues: New information systems may affect Y’s competitive position, service quality and efficiency. These strategic implications should be considered.
• E — Ensure the system meets company goals: This is a key governance responsibility. The committee should ensure the project remains aligned with Y’s objectives and delivers business value.

• B — Develop new systems: Detailed system development should be performed by IT specialists and project teams, not the steering committee.
• C — Manage the project: The project manager should handle day-to-day project management. The steering committee should provide oversight, challenge and key decisions, rather than manage daily activities.

• A: It allows for branching and merging...

• C: It allows multiple engineers to work against the same code and configuration files and manage differences and conflicts.

• B: Build automation and infrastructure provisioning are handled by CI/CD and automation tools, not by version control alone.
• D: User Stories and backlogs are managed by project-management tools.
• E: Version control stores and tracks code, but it does not itself ensure that developers write effective unit tests.

• C. Case after-insert trigger that publishes a Platform Event

• D. Custom Apex controller that publishes a Platform Event

• A. Trigger with a callout: Salesforce triggers should not make direct synchronous callouts, and this tightly couples transaction processing to the external system.
• B. Workflow Rule with Outbound Message: This can react to record changes, but it cannot reliably capture a user clicking a menu item. It also does not provide the same flexible event-driven model as Platform Events.

• A: Describes an update-set conflict, not a Dictionary Override.
• B: Describes a configuration item or change concept.
• C: Describes an approval or workflow activity.

• Sales process: Controls which Opportunity Stage values are available.
• Record type: Associates the appropriate sales process with a business scenario and controls available picklist values.
• Page layout: Controls which fields are displayed and whether they are required or read-only.

• Energy Market Team 1 ? Record Type 1, Sales Process 1, Page Layout 1
• Energy Market Team 2 ? Record Type 2, Sales Process 2, Page Layout 2
• Services/Installation Team ? Record Type 3, Sales Process 3, Page Layout 3

• Scale out during the hours when customer traffic is high.
• Scale in during low-demand periods, reducing instance-hours and cost.
• Use scaling policies based on metrics such as CPU utilization or request count.

• Multiple Availability Zones: Improves availability and fault tolerance, but does not automatically reduce cost.
• Placement group: Helps with specialized performance or low-latency requirements, not cost optimization.
• Private subnets: Improve network security, but do not automatically adjust capacity or reduce EC2 usage costs.

• Training data for potential bias before model training
• Trained models for bias in predictions
• Model features to help explain how they influence predictions

• A: RAG workflows are typically built using services such as Amazon Bedrock, knowledge bases, and data sources.
• B: Monitoring model quality in production is primarily associated with SageMaker Model Monitor.
• C: Documenting model details is handled by capabilities such as SageMaker Model Cards.

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.