SAP C_MDG_90 Exam Prep
SAP Certified Application Associate - SAP Master Data Governance (Page 31 )

• Laws and regulations
• Litigation holds
• Industry or contractual obligations
• Tax, financial, health, or privacy requirements

• Business strategy and direction: May influence retention, but cannot override legal requirements.
• Storage capacity and longevity: Practical considerations, not the primary driver.
• Business ease and value analysis: May support decisions after compliance obligations are identified.

• Cloud architecture
• Data architecture
• Platform engineering
• Data engineering
• Provisioning and modernization

• Data protection is associated mainly with security and risk management.
• Data governance belongs to the governance perspective.
• Data science is not an AWS CAF capability.

• Continuous deployment: Automates software releases; it does not specifically test input handling.
• Static code analysis: Examines source or compiled code without executing it. It can find coding flaws but does not directly stress the application with malformed inputs.
• Manual peer review: Developers inspect code or design manually. Useful, but not the best practice specifically for testing how a live product handles invalid input.

• C — Some risks cannot be eliminated.

• D — Accepting residual risk does not imply recklessness.

• E — Most companies in this industry will say something similar.

• The audience and stakeholders
• The complexity and type of requirements
• The communication method and level of detail needed
• Whether to use diagrams, models, documents, demonstrations, or slides

• B: Authority to host the presentation is not the key preparation activity.
• C: Stakeholder sign-off may occur later; presenting requirements does not always require formal approval beforehand.
• D: A scribe may be useful in a meeting, but hiring one is not a core preparation requirement for presenting.

• Compare each server’s drive specifications and performance data.
• Identify the drive that is faulty, slow, or mismatched.
• Replace it with a drive that matches the required interface, capacity, and performance characteristics.
• Avoid selecting a slower drive, because storage performance can bottleneck the entire server.
• In a redundant array, use a compatible replacement so rebuilding does not create unnecessary performance degradation.

• Confirm the required columns and data types
• Identify the target/label column
• Handle missing or duplicate records if present
• Transform data into a suitable format
• Split it into training and validation/test datasets

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

• 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.

• The product is already in production.
• The organization is examining the product’s functions and cost drivers.
• The objective is to reduce cost without reducing perceived value or required quality.

• Kaizen costing focuses on continuous, usually incremental, cost reductions during the manufacturing stage. It is not specifically the systematic examination of a product’s functions.
• Standard costing compares actual costs with predetermined standards; it is a control technique, not a product redesign method.
• Process innovation concerns developing significantly improved production processes, rather than analysing the product’s functions and value.

1. Create a custom Sensitive Information Type (SIT) in the Microsoft Purview portal.
2. Use a regular expression to match the 32-character alphanumeric account number.
3. Reference that SIT in the DLP policy protecting SharePoint Online.

• Format-based data ? custom SIT with RegEx
• Built-in sensitive data ? Microsoft-provided SIT
• Document classification/protection ? sensitivity labels
• Security investigation queries ? Advanced Hunting, not DLP detection

• Server provisioning
• Operating systems and runtime infrastructure
• Scaling
• Much of the maintenance and patching

• Thin clients reduce endpoint hardware requirements but do not specifically streamline code deployment.
• Private cloud provides dedicated cloud infrastructure but usually requires more management and expense.
• Virtual machines improve resource utilization, but administrators still manage the VMs, operating systems, and deployments.

• Un AG puede tener réplicas en Windows y Linux desde SQL Server 2017; por tanto, una réplica Windows y otra Linux es posible.
• Sin embargo, las réplicas de un AG deben utilizar normalmente la misma versión principal de SQL Server. Una instancia SQL Server 2017 no puede tener directamente una réplica secundaria SQL Server 2019 como configuración normal y permanente.
• En tu escenario, SQL Server 2017 en Windows y SQL Server 2019 en Linux no se pueden añadir directamente como réplicas equivalentes de AG1. Primero habría que realizar un proceso de actualización/migración compatible, por ejemplo mediante una actualización gradual o una tecnología de migración como log shipping o distributed availability groups, según el diseño.

• Tipo de clúster y mecanismo de quorum.
• Failover normalmente manual en configuraciones multiplataforma.
• Edición y características compatibles.
• Configuración de endpoints y permisos.
• Limitaciones específicas de SQL Server en Linux.

• The S3 bucket as an origin for static content
• The Application Load Balancer (ALB) as an origin for dynamic content
• An Amazon Route 53 alias record pointing the application domain to CloudFront

Why this works

• Static data: CloudFront caches objects from S3 at edge locations, reducing latency for users worldwide.
• Dynamic data: CloudFront forwards requests that require application processing to the ALB. It can also maintain persistent connections and use the AWS global edge network to improve delivery performance.
• One domain: CloudFront behaviors can route different path patterns to different origins—for example, /static/* to S3 and other paths to the ALB.

Why the other options are incorrect

• Global Accelerator is designed primarily for accelerating traffic to applications with endpoints such as ALBs, not for caching S3 content.
• Using separate domains or splitting static and dynamic traffic adds unnecessary complexity.
• CloudFront already provides the required global edge distribution and caching, so combining it with Global Accelerator is unnecessary here.

• Valor maior: mais aderência às instruções e aos detalhes descritos.
• Valor menor: mais liberdade criativa e resultados potencialmente mais variados.
• Valor excessivamente alto: pode causar artefatos ou imagens menos naturais.

• Aumentar o número de passos de geração: pode melhorar qualidade e refinamento, mas não é o principal controle de especificidade do prompt.
• MASK_IMAGE_BLACK: relaciona-se ao uso de máscara em geração ou edição de imagens, não à especificidade textual.
• Prompt strength: é mais associado à força do prompt em processos como image-to-image; nesta questão, o parâmetro diretamente ligado à aderência textual é o CFG scale.

• Load balancer: Distributes application traffic; it does not protect switch MAC tables.
• IPS: May detect some attack traffic, but it is not the primary control for switch-port MAC learning.
• NGFW: Protects at network boundaries but does not directly limit MAC addresses learned on access ports.

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

• 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.

• 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.

• Database data: Aggregates are used to retrieve structured data, commonly from entities and database sources.
• Screen scope: A Screen Aggregate belongs to the screen where it is defined and is not directly reusable as a screen-level aggregate elsewhere.
• Asynchronous and parallel execution: Multiple Screen Aggregates can run asynchronously and in parallel, helping the screen load data efficiently.

• A — Correct: Flow Builder is declarative and visual, so administrators and other non-developers can participate in designing and improving business processes without writing Apex.
• D — Correct: Flow Builder provides visual debugging tools, allowing an admin to test paths, inspect variable values, and identify where a specific business case fails.
• E — Correct: A flow’s visual structure documents the logic and makes later maintenance easier than reading and updating custom Apex code.

• B — Incorrect: Flow debugging does not attach a debugger to live customer sessions. The admin uses Flow Builder’s debug functionality with test inputs; this is not live-session debugging and should not be used to monitor real customer transactions.

• A: Reduce management overhead — This is generally an advantage of public cloud, not hybrid cloud. Hybrid environments can increase management complexity.
• B: Cross-platform virtualization — Not the defining advantage of hybrid cloud.
• D: Leverage IaaS and PaaS — Public clouds commonly provide both IaaS and PaaS, so this is not unique to hybrid cloud.

• 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.

• The vulnerability scan identifies a vulnerability.
• The administrator verifies that the vulnerability is not present.
• Therefore, the scan produced a false positive.

• True positive: A vulnerability is reported and genuinely exists.
• False negative: A vulnerability exists, but the scan fails to detect it.
• True negative: No vulnerability exists, and the scan correctly reports no issue.

• SharePoint search: Finds documents based on search terms, but it does not reliably identify every 32-character account number for DLP enforcement.
• A hunting query in Microsoft 365 Defender: Used for security investigations, not for defining sensitive content in a DLP policy.
• Azure Information Protection: Uses classification and labeling; it does not automatically identify this specific account-number pattern unless configured with a matching sensitive information type.
• RegEx pattern matching: Best suited for structured identifiers with a known format, such as account numbers, employee IDs, or policy numbers.

• Guiding principles
• Governance
• Service value chain
• Practices
• Continual improvement

• Guiding principles: Recommendations that guide decisions and actions; they do not describe the entire system.
• Four dimensions: Perspectives used to ensure a balanced approach to service management.
• Service relationship: Describes cooperation between a service provider and service consumer, rather than the whole value-creation system.

• The selling division receives a credit based on a favourable transfer price, often market price or full cost plus a profit margin.
• The receiving division is charged a lower amount, such as marginal cost or another agreed price.
• The difference is accounted for centrally by head office or a corporate adjustment.

• 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.

• 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.

• Sets a high initial price for a new product.
• Targets customers willing to pay more, often called early adopters.
• Gradually reduces the price to attract more price-sensitive customers as the product becomes less novel and competition increases.

• Penetration pricing: starts with a low price to gain market share quickly.
• Premium pricing: maintains a high price to communicate superior quality or status; it does not necessarily involve later price reductions.
• Loss leader pricing: sells one product at a very low price, sometimes below cost, to attract customers who may buy other products.

• Application management: Controls which apps can be installed or used; it does not remove existing data after theft.
• Full-disk encryption: Protects data when the device is powered off or locked, but it may not help if the attacker has already unlocked the device.
• Containerization: Separates corporate data from personal data, but the attacker may still access the corporate container using the stolen credentials.

• Monitoring: Detects activity but does not remove the underlying risk.
• Patching: Useful for systems that must remain operational, but these desktops are unused.
• Isolating: Can be a temporary containment measure, but permanently removing unnecessary systems is more appropriate.

• A — Securing information assets: This is the responsibility of management and operational/security teams.
• B — Validating protection: Correct. The auditor checks whether controls—such as access restrictions, encryption, retention, and handling procedures—match the asset’s classification.
• C — Ensuring alignment with regulations: Management and legal/compliance functions typically establish classification requirements; the auditor may assess compliance but does not primarily define alignment.
• D — Defining classification levels: This is a management responsibility based on business needs, risk, and regulatory obligations.

• The servers run different operating systems: Windows, Linux, and Unix.
• Containers generally share the host operating system’s kernel, so they cannot normally run workloads requiring unrelated kernels, such as Windows and Linux, on the same Linux host.
• A hypervisor can create separate virtual machines, allowing each VM to run its own guest OS.
• A Type 2 hypervisor runs on top of a host operating system and can support multiple guest operating systems.

• Keep earlier prompt versions.
• Identify the last version that produced acceptable output.
• Restore it as a baseline.
• Make small, controlled changes—ideally one significant change at a time.
• Test the output after each change.

• A: Discards useful information about what worked.
• B: Large simultaneous changes make it difficult to identify the cause of problems.
• D: Accepts output that does not meet the requirements.

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

• You can configure different pre-shared keys for different device groups.
• All cameras could use one key.
• All scanners could use another key.
• Each key can be associated with an appropriate role or access policy.

• A script of cloud CLI commands: IaC because the commands can be saved, reviewed, versioned, and rerun consistently.
• Manually run curl commands: Not necessarily IaC; they are manual actions unless organized into an automated script.
• A sequence of REST requests passed to an API: Could represent automation, but the wording does not explicitly say they are stored and executed as reusable code.
• Commands entered into a cloud console: Manual operation, not IaC.

• Outer packet: 10.5.1.1 > 52.165.16.154
• IPv4 protocol field: 41, which indicates IPv6 encapsulation
• Inner packet: IPv6 traffic between 2001:... addresses

• MAC address spoofing: Changes Layer 2 addressing; it does not explain the IPv6-in-IPv4 structure.
• Steganography: Hides data inside files or media, not visibly in a tunneled protocol.
• Broken encryption: No evidence of encryption being cracked.
• On-path sniffing: Involves intercepting traffic, not sending data to an external host.

1. Which host originated the infection

1. Which remaining hosts are infected

• Data Category Groups e categorias;
• Visibilidade dessas categorias para perfis ou permission sets.

• B e C: regras de compartilhamento não são o mecanismo apropriado para restringir resultados de busca do Knowledge por divisão.
• D: a role hierarchy não é o mecanismo principal para controlar a visibilidade de categorias do Knowledge. Além disso, a configuração correta é atribuir visibilidade a perfis ou permission sets.

• 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: Technology or access methods used outside approved IT processes.

• B: Developer Edition has limited user, storage, and data-volume capacity, making realistic community testing difficult.
• C: A Developer Edition org cannot contain sandboxes, so it cannot provide separate environments for development, integration, and UAT.
• E: A standalone Developer Edition org is not part of the production org’s deployment path, so change sets cannot be used to deploy from it directly to that production org. The team would need Metadata API, Salesforce CLI, or another deployment method.

• Azure Resource Manager (ARM) templates
• Or, in newer Azure terminology, Bicep files

• 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

sql 
CREATE PROCEDURE dbo.usp_CreateOrder 
AS 
BEGIN 
    SET NOCOUNT ON; 
    SET XACT_ABORT ON; 


    BEGIN TRY 
        BEGIN TRANSACTION; 


        INSERT INTO dbo.Orders (/ columns /) 
        VALUES (/ values /); 


        SET @OrderID = SCOPE_IDENTITY(); 


        COMMIT TRANSACTION; 
    END TRY 
    BEGIN CATCH 
        IF @@TRANCOUNT > 0 
            ROLLBACK TRANSACTION; 


        THROW; 
    END CATCH; 
END;

• BEGIN TRY contains the transactional work.
• SCOPE_IDENTITY() retrieves the identity generated by the INSERT; it belongs after the insert, not as the error-handling logic.
• COMMIT runs only if all statements succeed.
• BEGIN CATCH handles failures.
• IF @@TRANCOUNT > 0 prevents attempting a rollback when no transaction is active.
• ROLLBACK undoes partial changes.
• THROW re-raises the original error with consistent details for the application.
• SET XACT_ABORT ON ensures many run-time errors automatically terminate and roll back the transaction.

• Amazon EC2 instances — ???????? ?? ?? ??????? CPU, memory ??? instance size ???????? ???????
• AWS Lambda functions — memory configuration ?????????? ???????
• Amazon EBS volumes — volume type ?? size optimize ???? ???????
• ??????? ECS workloads — resource configuration ? cost optimization-?? ???????

• Memory ? compute usage ?????????? ???? custom code ????? ???? development ? maintenance ??????
• Cost allocation tags ???? ????? ??? ?????? ???? ??????? ???; inefficient resource ??????? ?? recommendation ???? ???
• CloudTrail resource ???? ?? API activity ??????, resource utilization ????

• netstat: Shows local network connections and listening ports, but not which WAN path carries the traffic.
• nslookup: Resolves domain names to IP addresses.
• ping: Tests reachability and latency but does not show the route.

• Restrict a port to a defined number of MAC addresses
• Use statically configured 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 traffic but is not the primary control for switch-port MAC limits.
• NGFW: Filters routed network traffic, not the switch’s CAM/MAC address table directly.

• 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.