Salesforce Field Service Lightning Consultant Exam Prep
Salesforce Certified Field Service Lightning Consultant (Page 16 )

1. It examines the source MAC address and learns it on the incoming port.
2. It examines the destination MAC address.
3. If the destination MAC is already in the MAC/CAM table, it forwards the frame only through the associated port.
4. If the destination MAC is unknown, it performs unknown-unicast flooding:

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

• Creating and training machine-learning models
• Testing and evaluating models
• Deploying models as usable endpoints

• Deficiency found before patient use: usually does not require an adverse-event report because no patient exposure occurred.
• Event caused solely by the patient’s condition: may not be reportable if the device did not contribute.
• Malfunction protection operated correctly: generally exempt when the device’s safety mechanism worked as intended and prevented harm.

• Reconnaissance: Gathering information about the target.
• Weaponization: Creating or combining a malicious payload with a delivery method.
• Delivery: Sending the payload, such as through phishing.
• Exploitation: Triggering a vulnerability or weakness to gain execution or access.

• Code signing: Verifies the software’s authenticity and integrity; it does not hide the source code or prevent reverse engineering.
• Tokenization: Replaces sensitive data with tokens, mainly for protecting data such as payment information—not software logic.
• Blockchain: Provides a tamper-resistant record of transactions or data; it does not protect compiled code from analysis.

1. Horizontal scaling — Yes

1. Vertical scaling — Yes

1. Scaling can manage costs — Yes

• Horizontal = more or fewer instances
• Vertical = larger or smaller instances

• Render thousands of animation frames
• Generate product images in multiple sizes
• Apply filters or transformations to a large image collection
• Produce visual effects for a video

• Firewall
• Intrusion prevention and detection
• Antivirus or antimalware
• Web and email filtering
• Virtual private networking (VPN)
• Sometimes content filtering and centralized reporting

• 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.

1. Create a temporary Onboarding OU.
2. Move the new account into it.
3. Move the restrictive SCPs from the organization root to the Production OU.
4. Allow the account to update AWS Config.
5. Move the account into Production after onboarding.

• An SCP attached at the organization root applies to every account and OU beneath it.
• An SCP attached to the Production OU applies only to accounts in that OU.
• Therefore, moving the restrictive SCP from the root to Production temporarily exempts the onboarding account without weakening the policies for existing production accounts.
• Once onboarding is complete, moving the account into Production subjects it to the normal restrictions.

• Annual interest payments net of tax relief (A): future cash outflows for the issuer.
• Redemption value (B): the final cash outflow when the bond is redeemed.
• Market value now (C): the cash proceeds received now, acting as the initial cash flow in the IRR calculation.

• Data owners: Decide who should have access and approve the access rules.
• Business process owners: May help define business requirements, but normally do not enforce technical permissions.
• Security steering committee: Provides governance and direction; it does not manage individual access rights.
• Security administrators: Apply and enforce the approved access controls.

• 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.

• S3 Glacier Deep Archive is designed for long-term archival data with very infrequent access and has a lower storage cost than S3 One Zone-IA.
• The documents are copies stored elsewhere, so reduced availability and delayed retrieval are acceptable.
• An S3 interface VPC endpoint allows private access from the VPC without exposing the bucket through the public internet.
• A bucket policy can restrict access to requests coming through that endpoint.

• 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. Wireless AP

1. Router

1. Firewall

1. Device placement

• 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. Adjust resolution: Incorrect because an incompatible resolution usually causes no display, distortion, or an unsupported-mode message—not intermittent flickering.
• B. Swap the HDMI cable: Correct. Replacing the common, easily tested component is the appropriate troubleshooting step.
• C. Replace the projector: Incorrect because the issue also occurs with a monitor.
• D. Configure refresh rate: A mismatched refresh rate can cause visual problems, but the repeated flicker across displays points more strongly to the cable.

• 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.

• C — Before update
• D — Before insert

apex 
trigger AccountTrigger on Account (before insert, before update) { 
    for (Account acct : Trigger.new) { 
        acct.Description = 'Updated automatically'; 
    } 
}

• In after insert and after update, Trigger.new records are read-only.
• Use after triggers when you need the record’s final database Id or want to create/update related records.
• Attempting to change a field directly in an after trigger causes a read-only error.

• 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.

• C — Create a form extension and implement validation

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

• 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

• 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

• Early units show relatively large time savings.
• Later units still take less time, but the reduction becomes progressively smaller.
• The curve therefore becomes flatter as production approaches 256 units.

• B: The reduction is not constant; learning normally diminishes over time.
• C: Time does not reduce at an increasing rate.
• D: A steady state may eventually be reached, but the question concerns the first 255 units while learning is still occurring.

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

• A — Tables
• B — Named file formats
• C — Schemas
• E — Databases

Why these are correct

• Tables: Can be cloned using CREATE TABLE ... CLONE. The clone initially uses zero-copy cloning, so storage is shared until changes are made.
• Named file formats: Can be cloned as database objects, preserving the file-format definition.
• Schemas: A schema and its eligible objects can be cloned.
• Databases: A database and its eligible schemas and objects can be cloned.

Why the others are incorrect

• Shares: A share is an account-level data-sharing object, not a normal cloneable database object.
• Users: Users are security principals and cannot be cloned with CLONE.

• Documented and formally requested
• Analyzed for security, cost, and operational impact
• Reviewed and approved by the appropriate personnel
• Tested before implementation
• Tracked and reversible if problems occur

• Risk management process: Identifies and evaluates risk, but does not directly authorize design changes.
• Product design process: Applies primarily while creating or developing the product.
• Design review process: May have identified the issues, but the next step for changing an already released design is controlled change management.

• 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.

• 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.

• Type 1 hypervisor: Runs directly on the physical hardware (“bare metal”).
• Type 2 hypervisor: Runs inside the host OS as an application.

• Bare-metal installation: Type 1
• Local management only: Not a defining characteristic
• Specific hardware requirements: Not the key distinction

• Least privilege: Limits users to only the access necessary for their job.
• Background checks: Help identify potentially risky individuals before employment.
• Separation of duties: Ensures that one person cannot complete a sensitive process alone, reducing fraud and abuse.

• Input validation: Prevents malicious or malformed input within an application; it does not authenticate a software package.
• Secure cookies: Protect web-session cookies; they do not protect downloadable software.
• Fuzzing: Tests software by supplying unexpected input to find vulnerabilities; it does not verify software integrity.

• Treatment one – easier to prepare: Convenience for the accounting team is not the main objective of financial reporting.
• Treatment two – fair representation: This is the correct choice because financial statements must faithfully represent the underlying transaction and its economic substance.
• Treatment three – maximises profit: Accounting policies must not be selected simply to manipulate or inflate reported profit.
• Treatment four – easier to understand: Understandability is important, but it cannot justify presenting information that is less faithfully represented.

• Periodic vulnerability assessments: Identify technical weaknesses but do not establish governance or ensure risks are managed.
• Established information security metrics: Help measure performance and report status, but measurement alone does not make governance effective.
• Advanced security technologies: Support security operations, but governance is primarily about direction, accountability, decision-making, and alignment with business objectives.

• 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.

• IKE (Internet Key Exchange) negotiates the IPsec security association, including:

• ESP (Encapsulating Security Payload) protects the data after negotiation by providing encryption and optionally authentication.
• AH provides authentication and integrity but does not encrypt traffic.
• TLS is used for protocols such as HTTPS, not for negotiating IPsec parameters.

• File hashes
• Strings and metadata
• Binary or code structure
• Known malicious patterns
• Embedded indicators or signatures

• Sandbox: Executes the file in an isolated environment; useful for observing behavior, but usually slower.
• Network traffic analysis: Examines communications generated by a system or application, not the file itself.
• Package monitoring: Tracks software packages or installations and is not the primary method for examining malware signatures.

• Row counts
• Minimum and maximum values for columns
• Distinct-value information
• Other characteristics used for optimization

• 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.

• 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.

• 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.

• Attack simulator — Used to run phishing and other attack simulations for user awareness training.
• Hunting — Used to proactively query security data and investigate potential threats.
• Incidents — Used to investigate and manage related alerts and active security events.

• Customer needs: Primary focus in agile; guides prioritization and decision-making.
• Organization’s needs: Important constraints, but processes should be tailored when they create waste.
• Agile lead/project manager: Their role is to facilitate value delivery, not prioritize their own preferences.

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.

• WPA3: Secures wireless traffic but does not normally verify whether someone has paid.
• PSK: A shared Wi-Fi password gives access to anyone who knows it; it cannot easily validate individual receipts.
• IEEE 802.1X: Provides user/device authentication, commonly through an authentication server, but is excessive and not designed specifically for a simple receipt-based guest-access workflow.

• Correct exam answer: A — HKEY_LOCAL_MACHINE
• The relevant location is associated with HKEY_LOCAL_MACHINE\SAM.
• The SAM does not store passwords in plain text; it stores password hashes.

• HKEY_CURRENT_USER contains settings for the currently logged-in user, not the account-password database.
• HKEY_USERS contains user profiles and settings loaded for users.
• HKEY_CURRENT_CONFIGURATION contains hardware/profile configuration information.

• 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.