Amazon AWS-Certified-Big-Data-Specialty Exam Prep
AWS-CERTIFIED-BIG-DATA-SPECIALTY (Page 49 )

• Error correction (ECC): Improves data reliability but does not maximize bandwidth.
• RAM voltage: Increasing voltage may affect stability or speed, but it is not the primary method for increasing module bandwidth.
• Physical module size: Refers to the capacity or form factor of the RAM, not its data-transfer bandwidth.

• Actions that call external APIs
• Subflows
• Connection and credential aliases
• Supporting integration logic

• Action — A reusable operation within a flow, such as “Create a record” or “Send email.”
• Connection — Defines how ServiceNow authenticates and communicates with an external system.
• Integration step — A general flow step, not the name for the packaged integration.

• Undefined or blank values
• Relationship matching problems
• Duplicate or conflicting keys
• Errors when querying the model

• Normalize all values to upper- or lowercase in the source query or Power Query.
• Add an index or surrogate key when values that differ only by case must remain distinct.

Recommended process

1. Access each switch’s terminal.
2. Use help to identify available commands.
3. Use the MAC table command, such as:

text 
   show mac-address-table

1. Use VLAN information, such as:

text 
   show vlan

1. Use interface information, such as:

text 
   show ip interface brief

1. Record each device’s:

• Create a CodeCommit repository in the secondary Region.
• Use CodeBuild to run a Git mirror operation from the primary repository to the secondary repository.
• Use EventBridge to detect relevant repository events, such as a pull request being merged.
• Invoke a Lambda function, which starts the CodeBuild project.

• B: Amazon S3 is object storage, not a Git repository that developers can use as a CodeCommit remote.
• C: CodeArtifact is intended for packages and artifacts, not source-code repository mirroring.
• D: An AWS Cloud9 environment is not an appropriate automated replication mechanism and would require manual or persistent infrastructure management.

• STP elects the switch with the lowest Bridge ID as the root bridge.
• The Bridge ID consists mainly of bridge priority + MAC address.
• If multiple switches have the same priority, the switch with the lower MAC address is preferred.
• STP bridge priority values are configured in increments of 4096, such as 0, 4096, 8192, and so on. 32768 is the standard default value.

• A — Technical review by business owner: A business owner may approve the business impact, but a technical review is normally performed by technical personnel.
• C — Cost-benefit analysis after implementation: Cost-benefit analysis should occur before implementation to support the approval decision.
• D — Business continuity testing: This can be appropriate for major changes, but it is primarily part of business continuity and disaster recovery planning—not a universal change-management activity.

• Proxy server: Acts as an intermediary for requests, but does not necessarily provide an encrypted connection to the corporate network.
• NGFW: A firewall with advanced inspection and filtering capabilities; it may support VPNs but is not the remote-access solution itself.
• Security zone: A logical network grouping based on trust or security requirements, not a method for remote access.

• 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.

• 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.

• A: Concerns task scheduling and avoiding missed runs, not directly sizing the warehouse.
• B: The amount of data in a stream alone does not reliably determine compute needs; the SQL processing is what matters.
• D: A multi-cluster warehouse addresses concurrency, not the compute size needed for one task execution.

• Restrict a port to a defined number of MAC addresses
• Use statically assigned or “sticky” MAC addresses
• Shut down or restrict the port when violations occur

• Load balancer: Distributes application traffic; it does not protect switch MAC tables.
• IPS: May detect suspicious network activity, but is not the primary control for limiting switch MAC entries.
• NGFW: Filters traffic at the network boundary; it does not directly prevent MAC table flooding on access switches.

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

• IaaS: You deploy and manage virtual machines, including the operating system and installed software. Azure manages the physical datacenter, hosts, and networking infrastructure.
• PaaS: Azure manages the infrastructure and operating system, while you deploy and manage your application code. Examples include Azure App Service and Azure Functions.

• 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.

• When the MVP will be defined — the MVP should already be understood sufficiently when assessing the business case.
• What the MVP is — useful information, but not the key requirement tested here.
• That the MVP is the same as project viability — incorrect. The MVP helps test viability; it is not identical to viability itself.

• Minimum
• Maximum
• Average
• Count
• Null/empty values
• Distinct values

• Enable column profile
• Enable details pane
• Show column profile in details pane

• 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.

spl 
error AND host=WWW3 
status=404 OR status=500 
NOT source=access.log

• Quotation marks are used for exact phrases or values containing spaces.
• Parentheses group parts of a Boolean expression, but they are not required for every Boolean search.

1. insert con; ? 1
2. Database.setSavepoint(); ? 2
3. update con; ? 3
4. Database.rollback(sp_admin); ? 4

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

• Share of overall contribution: part of the organization’s total contribution is allocated to the supplying division.
• Dual pricing: the supplying division may record a higher transfer price while the receiving division records a lower price, with central accounts absorbing the difference.
• A centrally imposed price range: this may allow the transfer price to be set above variable cost, helping the supplying division recover fixed costs.

• 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.

• 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.

• A — .gitignore: Controls Git tracking; it does not configure Copilot exclusions.
• B — copilot.ignore: This is not the standard GitHub Copilot Business exclusion mechanism.
• D — Renaming files: Adding _no_copilot has no recognized effect.

• B — Sales staff will tender for riskier contracts:

• C — Sales staff will encroach on other territories:

• D — Sales staff will look for new jobs:

1. Yes — Microsoft Foundry provides a secure, governed environment for building and managing generative AI applications and agents. It brings together models, data, tools, evaluation, deployment, and monitoring.

1. Yes — Foundry is designed for enterprise workloads and supports scaling AI applications as usage grows. Scalability comes from the underlying Azure services and managed infrastructure.

1. Yes — Foundry can be used in solutions involving image recognition and computer vision. Applications can use vision-capable models and Azure AI vision capabilities for tasks such as image analysis, object detection, and OCR.

• 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.

• T?o m?t Systems Manager Automation runbook d? ch?y l?nh kh?i d?ng l?i ?ng d?ng trên các EC2 instance.
• T?o m?t Amazon EventBridge rule ph?n ?ng khi CloudWatch alarm chuy?n sang tr?ng thái ALARM.
• Ð?t Automation runbook làm target c?a EventBridge rule.

1. Log c?a ?ng d?ng du?c ghi vào CloudWatch Logs.
2. CloudWatch alarm phát hi?n nhi?u l?i liên quan d?n vi?c restart.
3. Alarm chuy?n sang tr?ng thái ALARM.
4. EventBridge nh?n s? ki?n thay d?i tr?ng thái này.
5. EventBridge g?i Systems Manager Automation runbook.
6. Runbook restart ?ng d?ng trên các EC2 instance, không restart c? instance.

• A: SNS không tr?c ti?p g?i Systems Manager Automation runbook nhu m?t target native.
• B: Lambda có th? th?c hi?n vi?c restart, nhung ph?i t? x? lý vi?c xác d?nh instance và ch?y l?nh t? xa.
• C: Lambda ch? làm trung gian d? g?i runbook, không c?n thi?t vì EventBridge có th? g?i runbook tr?c ti?p.

• Escape to host: A virtualization attack where code escapes a guest VM and accesses the host system. Nothing in the scenario mentions virtualization.
• Browser extension: Can redirect or manipulate web-browser traffic, but not normally database-server traffic.
• Valid accounts: Describes using stolen or compromised credentials, not redirecting network traffic.
• Process injection: Injecting malicious code into a legitimate database or networking process could allow an attacker to alter how that process handles outgoing traffic.

• Supervised learning requires labeled examples to learn how to classify customers.
• Reinforcement learning learns through actions, rewards, and penalties, which is not the main task here.
• RLHF uses human feedback to improve model behavior, typically for generative AI, not customer segmentation.

• 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.

• Regression predicts continuous numeric outcomes, such as house price, temperature, or sales amount.
• Linear regression assumes the target can be estimated from a linear relationship between the input features and the target.
• In Azure Machine Learning, you use a labeled dataset containing:

• Classification predicts a category or class, such as “spam” or “not spam.”
• Clustering groups similar records without a known label; it is an unsupervised learning technique.

• Microsoft Foundry is an enterprise platform for developers, data scientists, and IT teams.
• It supports the full AI application lifecycle: selecting models, connecting enterprise data, developing, evaluating, deploying, monitoring, and scaling solutions.
• It can include visual tools and low-code experiences, but it is not primarily designed to enable business users to build complete generative AI solutions independently.

• B: You still need to select and configure an appropriate model.
• C: Business users may participate through visual tools, but they are not the primary target audience.
• D: Foundry includes low-code tools, but it is not fundamentally a low-code-only platform.

• Suspended an operator who refused to use unsafe equipment.
• Paid another operator a bonus for using it.
• Prioritised short-term productivity over employee safety.

• A — Management is not particularly concerned with managing risks.

• B — Employees will perceive that management does not care about health and safety risks.

• C — The factory’s safety record is likely to be poor.

• Due diligence: Investigating and evaluating a third party before entering into or continuing a business relationship.
• Attestation: An independent party provides assurance about an organization’s claims or controls. A SOC 2 examination is an example of an attestation engagement, but the analyst requesting and reviewing the report is performing due diligence.
• Internal audit: Reviews the organization’s own internal controls.
• Penetration testing: Actively tests systems for exploitable vulnerabilities.

• Labels control access and protection, not blanket exclusion.
• If the user has permission to open a labeled file—especially if the label allows authenticated users to view it—Copilot can use that file in a summary.
• If the label applies encryption and the user lacks the required usage rights, Copilot should not use the file or reveal its contents.
• Copilot honors the user’s existing permissions, so it should not expose labeled content to an unauthorized user.

• 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.

• 50% memory utilization baseline: The environment can be provisioned with excess capacity, leaving room for growth and workload spikes.
• Storage scalability: Cloud storage can generally be expanded as needed without redesigning the physical platform.
• Single circuit failure resilience: A properly designed IaaS provider uses redundant power circuits and infrastructure, so failure of one circuit should not take the platform offline.

• A — Dual PDUs: Helps with power redundancy but does not provide storage scalability.
• C — Network load balancing: Provides network-path resilience, not memory or storage scalability, and does not address a power-circuit failure.
• D — Multiple NAS devices: May improve storage capacity, but does not inherently provide power resilience or the required compute-capacity baseline.

• 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.

• A. IDS attack signatures: An IDS primarily detects suspicious network activity; it is not the best tool for scanning uploaded files.
• C. Load balancer: Improves availability and distributes traffic but does not inspect files for malware.
• D. WAF: Protects web applications against attacks such as SQL injection and command injection. It may inspect HTTP requests, but malware scanning of uploaded PDFs is the key requirement here.

• Microsoft Purview portal: Create and manage sensitivity labels and configure support for sensitivity labels used with Office files in SharePoint and OneDrive.
• SharePoint admin center: Primarily manages SharePoint settings. Older guidance and PowerShell procedures used SharePoint tenant configuration, which can make this question confusing.
• IRM: Concerns Information Rights Management and is a separate protection mechanism; it should not be used to identify the portal for configuring Microsoft Purview sensitivity labels.

• The requirement is to obtain an assessment of the Azure environment’s design.
• The proposed solution is the Premier support plan.
• Premier can provide this type of guidance, but it is a higher-tier, more expensive option.
• The question specifically says to keep costs to a minimum. A lower tier—typically Professional Direct in the support-plan model used by this question—provides architectural/design guidance.

• Streams — track change data for tables or views.
• External tables — reference data stored in an external cloud storage location.

• Role — account-level security object.
• Warehouse — account-level compute resource.
• User — account-level security object.
• Share — account-level object used to share data.

1. Open the Microsoft Entra Connect wizard.
2. Select Configure.
3. Choose Customize synchronization options.
4. Authenticate when prompted.
5. On the Domain and OU filtering page, select:

1. Complete the wizard.

• Start-ADSyncSyncCycle only starts synchronization; it does not change which OUs are included.
• Manage federation configures federation settings, which are unrelated to OU filtering.
• Add-ADSyncConnectorAttributeInclusion concerns connector attributes, not selecting additional OUs for synchronization.

• Base table — the table containing common inherited fields
• Parent table — the table directly extended by the child
• Other tables in the hierarchy

• What information each stakeholder needs
• When and how often it should be communicated
• Which format or channel should be used
• Who is responsible for communicating it

• A: The team should not decide stakeholder communications without first checking the established plan and CEO’s needs.
• B: An executive summary may be appropriate, but choosing a solution before reviewing the plan is premature.
• D: The stakeholder engagement plan addresses how to engage stakeholders, but this is primarily a communication planning issue.

• 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.

• transform() — modifies every element in an array
• filter() — keeps elements matching a condition
• exists() — checks whether any element matches
• aggregate() — reduces array elements to one result

sql 
SELECT transform(scores, x -> x * 2) 
FROM student_scores;

• A is incorrect because higher-order functions are mainly useful for nested or complex data.
• B is incorrect because they do not convert logic into Python.
• D is incorrect because their purpose is not to fix slow built-in functions, but to process arrays or maps with custom logic.