OMG OMG-Certified Systems Modeling Professional - Model Builder - Intermediate Exam Prep
OMG-Certified Systems Modeling Professional - Model Builder - Intermediate (Page 3 )

• Geo-redundant storage (GRS) replicates data to a secondary Azure region, but the secondary copy is normally unavailable for read access.
• RA-GRS provides geo-replication and read-only access to the secondary region, satisfying all requirements.
• Zone-redundant storage (ZRS) replicates data across availability zones within the same Azure region, not separate geographic regions.
• Locally redundant storage (LRS) keeps copies within a single datacenter or region and does not provide geographic resiliency.

• A — IDS attack signatures: An IDS generally detects suspicious network activity but does not necessarily scan uploaded PDF files or prevent them from being accepted.
• C — Load balancer: Distributes traffic among servers; it does not inspect files for malware.
• D — WAF command-injection blocking: A WAF can help block web attacks such as command injection, SQL injection, and cross-site scripting, but this option does not specifically address malicious PDF uploads.

• C — Schema.describeSObjects(new String[]{myObject})[0].fields.getMap()

• D — Schema.getGlobalDescribe().get(myObject).getDescribe().fields.getMap()

• A: sObjectType is not used this way, and fieldSet() is not the appropriate method for retrieving all fields.
• B: mySObject.myObject is not valid dynamic Apex syntax.

Simple explanation

• The Azure VPN gateway to connect to
• Authentication settings
• Routes for networks that the client can access

• Hardware and infrastructure
• System software
• Networks and communications
• Technology platforms and services

• Business Architecture: Defines business strategy, organization, functions, and processes.
• Data Architecture: Defines the structure and management of enterprise data.
• Application Architecture: Describes application systems and how they interact to support business and data processing.

• The 99.99% availability SLA for VMs is achieved when you run VMs across two or more Availability Zones.
• Two VMs in a single Availability Zone do not meet the 99.99% target (their SLA is lower, e.g., around 99.95% or less depending on configuration).

• Deploy at least two VMs across two different Availability Zones (one VM in each zone, or both in two zones with a load balancer).
• This provides the required zone redundancy and the 99.99% SLA.

• A. Implement retries with exponential backoff

• C. Reduce the frequency and/or size of requests

• B. Use PutRecord instead of PutRecords — PutRecord sends one record per call and does not remove the underlying throughput limitation. It may increase request overhead.
• D. Use Amazon SNS instead — SNS is not a direct fix for Kinesis shard throttling and changes the required streaming architecture.
• E. Reduce KCL consumers — KCL consumers read from Kinesis; they do not solve producer-side PutRecords throttling.

• Answer: C – netstat -an

• netstat -an lists all active connections and listening ports with numeric addresses, without resolving names. This lets you spot DoS patterns such as a flood of connections to a specific port or many connections from a single or few IPs.
• The other options don’t help as directly:

• Windows: netstat -an and look for numerous ESTABLISHED connections to a service or many SYNs to a port.
• Filter by port, e.g., netstat -an | findstr :80, or on Linux: ss -tunap | grep ':80'.

• Netstat provides a snapshot. DoS detection often benefits from continuous monitoring, flow data, and IDS/IPS logs.

• A: Security groups do not control traffic to an S3 gateway endpoint in this way. Gateway endpoints are configured through route tables.
• B: An S3 bucket policy may be needed for authorization, but the error specifically indicates a connectivity or endpoint-routing problem.
• C: Glue connection settings do not require a fully qualified domain name to resolve this endpoint issue.

• Server — provides services or resources
• Endpoint — a user device connected to the network
• Ethernet — a networking technology, not a filtering device
• Firewall — filters and controls traffic

• Active vs passive: Active assessment involves actively scanning targets by sending probes/packets to identify hosts, services, and vulnerabilities. Passive assessment observes traffic without probing.
• External vs internal: External assessment is about testing from outside the network perimeter; the scenario doesn’t specify external vantage, only that tools are identifying hosts/services across the enterprise network.

• Remote and global access: Employees can authenticate from anywhere, not just a specific location.
• Seamless login: The device can authenticate in the background, reducing repeated password or MFA prompts.
• Minimal equipment: It uses devices employees already have, rather than requiring separate hardware.

• Geotagging: Identifies location but is not a complete authentication method and can be spoofed.
• Smart cards: Can provide strong authentication, but require cards and often readers, adding equipment and user steps.
• Time-based logins: Restrict access by time but do not verify the user or device adequately.

• Azure Resource Manager (ARM) templates define Azure resources in a declarative JSON file.
• You can deploy the same template repeatedly for each business unit, ensuring that identical resources are created consistently.
• Templates reduce manual administrative effort and support repeatable, automated deployments.
• Parameters can customize values such as names, regions, and sizes while keeping the overall resource configuration the same.

• Users retain their existing usernames and passwords.
• Existing accounts can be used to access Azure-based resources.
• Administrators avoid manually recreating thousands of accounts.
• The transition is less disruptive before the on-premises data center is retired.

• Disable default accounts: Default or unused accounts may have predictable names or credentials and can be abused by attackers. They should be disabled, removed, or secured with strong credentials where necessary.
• Remove unnecessary services: Every running service can contain vulnerabilities or provide an entry point. Removing services the server does not need reduces exposure.

• Add the server to the asset inventory: Important for asset management, but it does not directly harden the system.
• Document default passwords: Default passwords should be changed or disabled—not recorded for continued use.
• Send logs to the SIEM: Supports monitoring and detection, rather than directly reducing the attack surface.
• Join the corporate domain: A deployment/configuration decision, not inherently a hardening measure.

• Due Date
• Order Date
• Delivery Date

DAX 
Order Date = 'Due Date' 
Delivery Date = 'Due Date'

• Due Date[Date] ? Sales[Due Date]
• Order Date[Date] ? Sales[Order Date]
• Delivery Date[Date] ? Sales[Delivery Date]

• Disabling GPS: Affects location services, not email connectivity.
• Configuring 4G usage only: Does not enable international data access and could prevent connectivity if 4G is unavailable.
• Connecting using a hotspot: Could provide data, but it is not the most direct solution and depends on another network or device.

• Le rôle n’a pas de clés propres. Des identifiants temporaires (via STS) sont émis lorsque quelqu’un ou quelque chose « assume » le rôle.
• La trust policy déclare qui peut assumer le rôle (par ex. une instance EC2, un utilisateur IAM, ou un service comme Lambda).
• Une fois attaché à une ressource (par exemple comme un instance profile sur une EC2), l’application peut appeler les services AWS avec les permissions du rôle.

• Respect du principe du moindre privilège: on accorde uniquement ce qui est nécessaire.
• Pas de stockages de clés sur les instances; les credentials se renouvellent automatiquement.

• Rôles pour EC2, rôles pour Lambda, accès cross-compte, etc.

• Correct answer: D) Amazon Aurora Serverless

• Aurora Serverless is serverless, so compute capacity scales automatically and can pause during idle periods. This minimizes ongoing administration and you pay only for actual usage, which is ideal for infrequent workloads.
• PostgreSQL on EC2 requires full OS and DB administration.
• RDS for PostgreSQL is managed but still involves provisioning capacity and some maintenance tasks.
• Aurora PostgreSQL (non-Serverless) is managed but requires you to manage capacity, though with some automation; it’s not as hands-off as Serverless for intermittent usage.

• Basic: Self-help only; no technical support or design assessment.
• Developer/Standard: Technical support, but generally not the full proactive architecture guidance required here.
• Professional Direct: Includes proactive guidance and architecture recommendations.
• Premier: Also supports this, but is not the minimum-cost option.

• A Layer 2 switch checks the destination MAC address in its MAC address table (CAM table).
• If the destination MAC is unknown, the switch cannot select a specific outgoing port.
• It therefore performs unknown-unicast flooding, sending the frame out every other port in that VLAN.
• The frame is not sent back through the port where it arrived.

• Honeypots: Decoy systems or services designed to attract attackers. Legitimate users should not access them, so activity on a honeypot is a strong indicator of unauthorized activity. Security teams can also observe attacker behavior.

• DNS sinkhole: Redirects requests for known malicious domains to a controlled internal server or blocks them. If an infected workstation attempts to contact command-and-control infrastructure, the sinkhole records the request and helps identify the compromised device.

• Tokenization: Protects sensitive data by replacing it with tokens.
• CI/CD: Automates software development and deployment.
• Threat modeling: Identifies potential risks before or during system design.
• Data obfuscation: Makes data harder to understand, but does not detect intruders.

• Answer:

• Why:

• Why the other centers aren’t the right fit here:

• The correct answer is A: CCTV recordings are not regularly reviewed.

• CCTV is a monitoring/control mechanism. If recordings aren’t reviewed, security events (break-ins, policy violations, equipment tampering) can go undetected and unaddressed.
• Regular review is essential for deterrence, incident response, and forensic evidence. Without it, the entire CCTV control provides little value.

• B (records deleted after one year) affects forensic availability, but it’s a data-retention issue rather than the ongoing effectiveness of the surveillance program.
• C (footage not recorded 24x7) creates gaps in coverage, which is a concern, but regular review of available footage still supports detection; 24x7 coverage is a separate policy/perimeter issue.
• D (cameras not in break rooms) is more about privacy and space planning than core data-center security monitoring.

• Writing with Apache Spark, typically as Delta tables.
• Reading with Apache Spark for processing and analysis.
• Reading with T-SQL through the lakehouse’s automatically generated SQL analytics endpoint.
• Reading with KQL through Fabric’s query capabilities that can access lakehouse data.

• Eventhouse: Optimized for real-time and KQL workloads, but it is not the natural destination for Spark-based writes or general lakehouse storage.
• Datamart: Intended mainly for relational analytics and Power BI; it is not designed for Spark-based data ingestion.
• Warehouse: Primarily T-SQL-based and structured. It does not provide the same native Spark write experience or flexibility for semi-structured data.

• Correct answer: A) Hashing

• Why: Hashing produces a fixed-size digest of the software. If the final build is altered in any way, the hash will change, enabling you to detect tampering by comparing the stored digest with a freshly computed one.

• Why not the others:

• Leadership and stakeholder commitment
• Business capability and skills
• Organizational culture
• Availability of resources
• Ability to manage and sustain change
• Impact of the proposed transformation

• How ready the organization is
• Which areas require urgent attention
• How difficult each issue may be to resolve
• Risks that could affect implementation

• A: Places the assessment in Phase B and refers vaguely to creating views; this is not the prescribed technique.
• B: An Implementation Factor Assessment and Deduction Matrix is not the primary TOGAF technique described for business transformation readiness.
• D: A Business Scenario helps identify requirements and stakeholder concerns, but it is not the main technique for assessing organizational readiness.

• Dynamics 365 Remote Assist — used for remote collaboration and mixed-reality scenarios.
• Dynamics 365 Finance — supports financial and operational management.
• Dynamics 365 Business Central — designed primarily for small and medium-sized businesses’ finance and operations.
• Dynamics 365 for Phones — provides mobile access to Dynamics 365 apps, including Sales, through the mobile Unified Interface.

• Creating and managing users and roles
• Granting and revoking roles and privileges
• Managing access-control responsibilities

• SYSADMIN: Manages warehouses, databases, schemas, and other objects—not primarily users and roles.
• PUBLIC: Automatically granted to every user; it is not an administrative role.
• ACCOUNTADMIN: Has the highest level of access, but should be reserved for account-level administration and emergencies rather than routine security tasks.

• Pay-as-you-go in Azure is an operating expense (OPEX) model, not an “elastic” expenditure model.
• Elastic or scalable terms describe capacity planning, not the cost category. The cost should be treated as OPEX since you pay for usage each month.
• The parallel question (Question 12) shows the correct approach is using an operational expenditure model.

python 
import azure.cognitiveservices.speech as speechsdk 


speech_config = speechsdk.SpeechConfig( 
    subscription="YOUR_KEY", 
    region="YOUR_REGION" 
)

Important Azure Speech SDK classes

• SpeechConfig

• AudioConfig

python 
  audio_config = speechsdk.audio.AudioConfig( 
      use_default_microphone=True 
  )

• SpeechRecognizer

python 
  recognizer = speechsdk.SpeechRecognizer( 
      speech_config=speech_config, 
      audio_config=audio_config 
  )

• SpeechSynthesizer

• AudioOutputConfig

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