Salesforce ARC-101 Exam Prep
Certified Integration Architect (Page 4 )

• Large initial load (2M Accounts, 5.5M Contacts, 4.3M Opportunities, 45k Products): use Bulk API for high-volume, asynchronous data loads (preferred over SOAP/REST for big batches).
• Notify external systems of new/updated Accounts/Contacts: use Streaming API to publish events in real time to external systems.
• Expose custom business logic to 5 external apps securely: use Apex REST API to create secure REST endpoints (easily protected with OAuth/Named Credentials).
• Schedule nightly dataflows/recipes/data syncs: use Analytics REST API to manage Einstein Analytics dataflows/Recipes and scheduling.

• A and B lack the Streaming API for real-time notifications.
• D uses Apex SOAP API instead of REST; REST is generally preferred for new integrations and easier to secure and manage.

• Platform Event (C) — This is the best choice. Platform Events are designed for pub/sub, real-time updates inside Salesforce. A Lightning component can subscribe to the event (e.g., via the empApi) and refresh the count as soon as a Case is closed.

• Push Topic (A) — Primarily for external systems to subscribe to Salesforce data changes. It’s not the ideal pattern for updating an internal Salesforce UI component.

• Change Data Capture (B) — Used to notify external systems about data changes. It can feed external dashboards, but it isn’t the most straightforward way to drive an in-Salesforce UI in real time.

• Generic Event (D) — Not a standard or recommended pattern for this use case.

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

• 25 – Traditional SMTP server-to-server mail transfer; often blocked for client submission and not inherently secure.
• 110 – POP3 for receiving email; unencrypted by default.
• 143 – IMAP for accessing email; unencrypted by default.
• 587 – Authenticated email submission and commonly secured with TLS.

• 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.

1. Initiate — establish the project, scope, team, and governance.
2. Plan — develop the detailed plan, schedule, resources, and implementation approach.
3. Execute — configure, integrate, migrate, test, and prepare the solution.
4. Deploy — move the solution into production and support go-live.
5. Close — complete handover, confirm outcomes, and formally close the project.

• 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.

• Self-signed certificate: Causes a browser security warning, not incorrect name resolution.
• Nameserver record: A DNS problem would typically affect multiple users, not just one workstation.
• IP helper: Relays services such as DHCP across network segments; it does not resolve website names.

• 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.

• 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.

• 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.

• Free: Doesn’t support the required custom domain and SSL configuration.
• Shared: Doesn’t provide the required SSL support or scalability.
• Basic: Supports multiple instances and SSL, but its storage limit is insufficient for the required 12 GB.
• Standard: Supports:

Statement 1 — Correct

Statement 2 — Correct

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

• 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.

• Storage usage of files stored in Microsoft Teams: SharePoint site usage report

• Number of active users per team: Microsoft Teams usage report

1. SharePoint site usage report
2. Microsoft Teams usage report

• Accept: Acknowledge the risk and take no additional action.
• Transfer: Shift the risk or its financial impact to another party, such as through insurance or outsourcing.
• Mitigate: Reduce the likelihood or impact of the risk, such as by implementing security controls.
• Avoid: Eliminate the activity or exposure that creates the risk.

• 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.

• 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.

• 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.

• GPS coordinates
• Date and time the image was taken
• Camera or device model
• Exposure settings

• Log data: Records events or activities, such as system or application activity.
• Encrypted data: Information intentionally encoded to prevent unauthorized access.
• Sensitive data: A broad classification for information requiring protection; geolocation may be sensitive, but the technical type stored in the image is metadata.

• The Intune device limit restriction does not apply in the normal way; DEM enrollment supports up to 1,000 devices.
• However, the Microsoft Entra maximum number of devices per user setting can still impose a limit when the enrollment creates an Entra device object.
• Therefore, a DEM account is not automatically unlimited. The effective limit depends on the Entra device setting and the enrollment/join type.

• Shared capacity

• Fabric capacity — F SKUs

• Fabric trial capacity

• Existing Power BI Premium — P SKUs

• 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.

• 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.

• Windows 11 Pro ? Windows 11 Enterprise
• Windows 10 Pro ? Windows 10 Enterprise

• 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.

• Espionage: Stealing confidential information, often for a competitor or foreign entity.
• Data exfiltration: Unauthorized removal or transfer of data.
• Nation-state attack: A cyberattack sponsored or conducted by a government.
• Shadow IT: Unapproved technology or services used outside IT oversight.

• 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

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

• 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.

• Red team: Offensive security; simulates attackers and validates exploitability.
• Blue team: Defensive security; monitors, detects, and responds to attacks.
• Purple team: Helps red and blue teams collaborate and improve defenses; not usually the primary testing role.
• White team: Oversees and coordinates the rules, scope, and authorization of an exercise.

• Behavioral and anomaly detection
• Threat intelligence integration
• User and entity behavior analytics
• Automated response actions, often through SOAR integration

• Virus signatures: Associated primarily with antivirus or endpoint protection.
• Security agent deployment: Usually an endpoint-management or EDR function.
• Vulnerability scanning: Typically performed by vulnerability-management tools, though a SIEM may integrate their results.

• 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.

• NTLM: Uses Windows challenge-response authentication and does not provide the normal web-based MFA redirect flow.
• Single Sign-On: Automatically reuses existing credentials; it is intended to avoid prompting, not to support an MFA workflow.
• Transparent: Intercepts the session without redirecting the user to a separate authentication page.

• Dark web: A place where leaked credentials may be sold or shared, not usually the original source.
• Threat feeds: Collections of intelligence about threats, not a typical leakage source.
• State actors: A type of attacker, not an accidental corporate disclosure source.
• Vulnerability databases: Track known vulnerabilities, rather than leaked credentials.

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

• 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.

• A class/teacher fact should contain one row per Class ID. It can support the count of classes and contain attributes such as Teacher First Name and Period Number.
• An attendance fact should contain one row per attendance event, such as Class ID + student + date. It supports attendance counts by day and monthly averages.

• Teacher First Name ? Teacher fact
• Period Number ? Attendance fact

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.

• 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.

• A is incorrect: Flow Debugger is for debugging Salesforce Flows, not Trust Layer masking.
• B is incomplete/misleading: Requesting audit data may be part of reviewing the results, but collection and storage must first be enabled.
• C is correct: It describes the initial validation step.

• Initial Intrusion: The compromised VPN account and stolen phishing credentials describe how the attacker first gained access, but that happened months earlier.
• Persistence: The scheduled tasks and recurring C2 connections show how the attacker maintained and automated continued access.
• Search and Exfiltration: This would involve locating and transferring data. The scenario does not primarily describe data discovery or theft.
• Cleanup: Cleanup involves removing evidence or covering tracks. Obfuscated scripts may make detection harder, but the main behavior here is maintaining access.

• 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.

• 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.

apex 
Set<Id> accountIds = new Set<Id>{ accountId1, accountId2 }; 


List<Account> accounts = [ 
    SELECT Id, Name 
    FROM Account 
    WHERE Id IN :accountIds 
];

• A: LIMIT accepts a number, not a collection of IDs.
• B: Set.containsAll() checks set contents in Apex; it does not filter SOQL results.
• C: Database.query() accepts a dynamic SOQL string, not a Set<Id> directly.

• Explain questions from the exam page
• Check whether the stated answer is technically correct
• Compare answer choices and eliminate distractors
• Clarify Azure AI concepts and terminology
• Point out when an answer key appears unreliable or when an image is missing

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