SAP C_TB1200_10 Exam Prep
SAP Certified Application Associate - SAP Business One Release 10.0 (Page 6 )

• Instant messaging/chat: Can be abused to send malicious links or attachments, but P2P file sharing is the more direct high-risk source.
• E-mail: A common malware delivery method, but this question specifically emphasizes an application type associated with direct file exchange.
• End-to-end applications: This describes communication protection or architecture, not a specific application category known for malware distribution.

• The job keeps 31 days of regular restore points. A backup from the week of January 1 is older than 31 days by March 20, so it is no longer expected to remain on the performance tier.
• It is also a weekly GFS full backup, retained for 14 weeks. Therefore, it is still protected and has not been deleted.
• In a Scale-out Backup Repository, older backups can be moved from the performance tier to the capacity tier—typically object storage—according to the configured offload policy.
• The archive tier is not selected because the question’s configuration does not indicate that the backup has been archived there.

• Physical: Protects facilities or equipment, such as locks and security cameras.
• Technical: Uses technology, such as firewalls, encryption, or access controls.
• Operational: Covers day-to-day actions and processes, such as training, backups, or incident response.
• Managerial: Includes policies, standards, risk assessments, and procedures.

• IaaS: você gerencia a VM e o sistema operacional.
• PaaS: o Azure gerencia a infraestrutura; você se concentra no aplicativo.

• Scanning is not essential during a power outage.
• A scanner can consume UPS battery power without helping the user save cloud documents or shut down safely.
• The UPS should be reserved for the computer, monitor, and necessary network equipment.
• The surge protector helps protect the scanner from voltage spikes, but it will not keep it running during an outage.

• Tokenization: Replaces the value with a nonsensitive token, often reversible through a secure token vault.
• Hashing: Converts data into a one-way fixed-length value, generally used for integrity checks or password storage.
• Obfuscation: A broad term for making data difficult to understand; it is less precise than masking in this context.

• 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.

• 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.

• Red team: Simulates attackers and tests exploitability.
• Blue team: Defends, monitors, detects, and responds to attacks.
• Purple team: Combines red- and blue-team activities to improve cooperation and defenses.
• White team: Manages and oversees the rules, scope, and authorization of the exercise.

• A is correct: It establishes the revised dates and identifies the effect on the critical path.
• B is premature: Stakeholders should be informed after the impact has been assessed and the updated schedule is understood.
• C is not automatically appropriate: Fast-tracking may introduce additional risk and should be considered only after analyzing schedule options.
• D is premature: Adding resources may not resolve a dependency and could increase costs without addressing the actual constraint.

• 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.

• Key-based authentication: Provides an endpoint secured with API keys.
• Real-time REST access: Supports online inference through an HTTP/REST endpoint.
• No VM vCPU quota consumption: Microsoft hosts and manages the underlying infrastructure, so your subscription’s VM quota isn’t used.

• Batch: Intended for asynchronous, large-volume processing rather than real-time requests.
• Self-hosted container: You manage the infrastructure and typically need compute resources and quota.
• Standard: This is not the clearest deployment type for the stated requirements; the specific Foundry option is serverless API.

• Feedback form: Captures opinions, not necessarily actual behavior; users may not respond.
• Questionnaire: Relies on memory and subjective judgments about usefulness.
• Interviews: Can provide valuable qualitative insights, but a sample of users may not represent overall usage accurately.

• 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

Why A is the best fit

Why the other options are weaker

• B — Create alerts in Dynamics 365 Finance: Alerts notify users about changes; they do not calculate tax.
• C — Implement the Common Data Model: CDM standardizes data structures but does not provide tax-calculation logic.
• D — Run a Power BI report: Power BI is primarily for analysis and reporting. A report might display tax rates, but it would not normally calculate and apply tax to sales orders operationally.
• E — Write scripts and code: This could work, but it is less aligned with the requirement for a quick, cost-effective implementation because custom development requires more time and maintenance.

• Employees can work from any location, including remote sites and offices worldwide.
• Login can be relatively seamless after the device is registered.
• It does not require distributing additional physical authentication equipment.

• Geotagging: Identifies location, but location alone is not a strong authentication method and may prevent legitimate remote access.
• Smart cards: Provide strong authentication but require card readers and physical cards, increasing equipment and management requirements.
• Time-based logins: Typically involve one-time codes that users must enter, making the experience less seamless and potentially requiring a token or authenticator app.

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.

• 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.

• If the hashes match, the software has likely not changed.
• If they differ, the software was modified or corrupted.

• Encryption: Protects confidentiality by making data unreadable; it does not primarily verify that software was unchanged.
• Baselines: Establish expected configurations or states, but hashing is the specific method for checking file integrity.
• Tokenization: Replaces sensitive data with non-sensitive tokens and is unrelated to software integrity.

• Crash cart: Provides local physical access, not remote access.
• Jump box: A secured intermediary used to reach devices over the normal network; it may be inaccessible if the appliance has not booted.
• Secure Shell (SSH): Requires the device’s operating system and network services to be running properly.

• 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.

• The requirement is an assessment of the Azure environment’s design, which requires a support plan offering proactive architectural guidance.
• Premier support would provide this capability, but it is a high-cost option.
• Since the requirement says to minimize expenses, Premier is not the best recommendation.
• A lower-cost plan with the required advisory/design-review capability—historically Professional Direct in Azure’s support-plan model—would be more appropriate.

• 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.

• Install unauthorized or unapproved applications
• Access system areas normally restricted
• Add features unavailable in the default software
• Modify the device’s operating system

• SQL injection (SQLi): Attacks databases by inserting malicious SQL commands.
• Cross-site scripting (XSS): Injects malicious scripts into web pages viewed by users.
• Sideloading: Installs an application from outside the official app store, but it does not necessarily remove the phone’s operating-system restrictions.

• 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.

• 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.

• Accept: Acknowledges the risk without taking additional action.
• Transfer: Shifts the risk or financial impact to another party, such as an insurer.
• Mitigate: Reduces the likelihood or impact through controls like patching, MFA, or segmentation.
• Avoid: Eliminates the activity that creates the risk.

• 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.

• STIX: A standardized format for exchanging cyber-threat intelligence.
• OVAL: A language and framework for describing and assessing system vulnerabilities and configuration issues.
• Threat intelligence feed: Provides current indicators or threat information, but is not specifically a reference for common application exploitation techniques.
• CVE: A catalog of publicly disclosed vulnerabilities, identified by unique CVE numbers.

• 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

• 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.

• Complete MFA, or
• Securely change their password

• Identity Protection: evaluates user and sign-in risk and can trigger remediation.
• Privileged Identity Management (PIM): manages temporary, just-in-time access to privileged roles; it does not automatically require password changes for risky sign-ins.

• CPU: Number of virtual CPUs and, where applicable, CPU reservations.
• Memory: Amount of memory and memory reservations.

• Network interface: Usually configured through the VM or workload networking configuration.
• PCI devices: Specialized hardware and not a standard VM Class resource in this context.
• Storage: Typically selected through storage policies or the VM’s storage configuration.

Why this is correct

• Each user authenticates with their own Google account.
• Google manages the user’s SSH key association.
• IAM controls who can access instances.
• Access can be audited by user identity, so security can determine who accessed a VM.
• Granting the role to a Google group avoids managing permissions individually.

Why the others don’t apply

• A: A shared private key is difficult to distribute securely and cannot reliably identify which employee used it.
• B: Manually collecting and deploying keys on every instance is operationally inefficient and complicates auditing.
• D: A project-wide shared key has the same identity and key-management problems as option A. It also does not provide per-user accountability.

• 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

• 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.

• Each team’s Bedrock workflow uses a separate IAM service role.
• The role’s Amazon S3 permissions can be limited to only that team’s customer folder or objects.
• This enforces least privilege and prevents one team’s Bedrock application from accessing another team’s data.
• Access is enforced by AWS permissions, not by asking users to provide a customer name in each request.

• A single role with broad S3 access does not provide team-level isolation.
• Asking teams to specify a customer name is not an access-control mechanism.
• Redacting data does not prevent unauthorized access.
• A bucket policy alone is insufficient unless it explicitly enforces the required team-role restrictions.

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

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

• 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.

• Set credit quotas for an account or individual virtual warehouses.
• Define monitoring intervals.
• Trigger actions when usage reaches thresholds, such as sending notifications or suspending a warehouse.
• Help control unexpected warehouse spending.

• Account Usage: Provides historical usage and billing data; it does not enforce credit limits.
• Warehouse Limit Parameter: Not the Snowflake object used for account-wide credit controls.
• Credit Consumption Tracker: Not a standard Snowflake object.

• Tokens: Individual units of text processed by a model, such as words, subwords, or characters.
• Models: Systems that learn patterns and generate predictions or outputs.
• Binaries: Data represented using the binary number system, not semantic representations.

• Constrained VMs: VMs whose workloads are experiencing resource pressure, such as insufficient CPU or memory. They may need additional resources or optimization.
• Overprovisioned VMs: VMs allocated more CPU, memory, or storage than their workloads require. Their resources may be reclaimed or reduced.

• Underprovisioned VMs: This is not the predefined view identified for this report question.
• Zombie VMs: These are typically inactive or unused VMs and are useful for cleanup, but they are not the two views specifically intended here to identify inefficient resource allocation.

• Admin access to the deployment pipeline
• Contributor access to the Development and Test workspaces
• Viewer access to the Production workspace

• BCP (Business Continuity Plan): è più ampio e mira a mantenere le funzioni essenziali dell’organizzazione durante un’interruzione. Il DRP è una componente più specifica del BCP.
• Communication plan: stabilisce come comunicare con dipendenti, cittadini e altre parti interessate, ma non ripristina i sistemi.
• IRP (Incident Response Plan): gestisce la risposta iniziale a un incidente di sicurezza, come un attacco informatico, non principalmente il recupero da un disastro fisico.

• MTTC: Time required to contain or limit the incident’s impact — best match.
• MTTR: Time required to remediate or recover from the incident; this may include eradication, restoration, and cleanup, which goes beyond merely stopping spread.
• MTTD: How long it takes to discover the incident.
• MTBF: Average time between failures, generally a reliability metric.

• B — The glass core component is encased in a cladding.

• D — Light is transmitted through the core of the fiber.

• BNC connectors are associated mainly with coaxial copper cabling, not standard fiber connections.
• Data does not pass through the cladding; the cladding helps reflect and contain the light.
• RJ-45 connectors are used with copper Ethernet cabling, not fiber-optic interfaces.

• # Development
• # Testing
• # Production

• Separate endpoints: relate to compute or connectivity, not dashboard labels.
• Separate queries: retrieve or transform data but do not designate visual sections.
• Direct text written into the dashboard in editing mode: dashboards use text boxes, typically with Markdown formatting, rather than arbitrary text placed directly on the canvas.

• Remote and global work: Access is based on the approved device, not a specific office or geographic location.
• Seamless login: Users may not need to repeatedly enter credentials on a recognized device.
• Limited equipment: It uses devices employees already have rather than requiring separate hardware.

• Geotagging: Restricts access based on location and may prevent legitimate remote work.
• Smart cards: Require issuing and managing additional physical equipment.
• Time-based logins: Limit access by time and do not provide a seamless authentication experience.

• 255.255.255.128 = /25: 128 total, 126 usable
• 255.255.255.192 = /26: 64 total, 62 usable
• 255.255.255.224 = /27: 32 total, 30 usable
• 255.255.255.240 = /28: 16 total, 14 usable

• One for the network address
• One for the broadcast address

• 8 total addresses
• 6 usable addresses
• Mask: 255.255.255.248