Scrum PSD Exam Prep
Professional Scrum Developer (Page 10 )

• 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.

• Business
• People
• Governance
• Platform
• Security
• Operations

• Sustainability
• Performance efficiency
• Reliability

• A — Use getRecordTypeInfosByDeveloperName()

apex 
  Id rtId = Schema.SObjectType.Account 
      .getRecordTypeInfosByDeveloperName() 
      .get('Business_Account') 
      .getRecordTypeId();

• C — Query the RecordType object

apex 
  RecordType rt = [ 
      SELECT Id 
      FROM RecordType 
      WHERE SObjectType = 'Account' 
      AND Name = 'Business Account' 
      LIMIT 1 
  ];

• B: An outbound SOAP call is unnecessary and inefficient.
• D: Hardcoding an ID is not dynamic, and IDs can differ between orgs.

• 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.

• Run the backup with WITH CHECKSUM
• Store the backup on an SMB network share

sql 
BACKUP DATABASE DB1 
TO DISK = '\\FileServer\SqlBackups\DB1_full.bak' 
WITH CHECKSUM;

• DMS does not create the SQL Server backups for you.
• You must provide a valid full database backup.
• You must continue taking transaction log backups while the source database remains online.
• The full backup and subsequent log backups must be available in the SMB share that DMS can access.
• WITH CHECKSUM enables backup checksum validation, helping detect backup corruption.

• The JSON files contain one billion items, so this is a big-data workload.
• PySpark uses Apache Spark’s distributed, parallel processing, allowing the data to be processed across multiple compute nodes.
• It can read and transform data directly from OneLake, helping minimize unnecessary data movement or duplication.
• A Fabric notebook can also support exploration and visualization, as well as Spark-based analytics and anomaly-detection workflows.

• Pandas is primarily in-memory and generally suited to smaller datasets. One billion records would be impractical on a typical single machine.
• A Power BI report with core visuals is appropriate for visualization and sharing, but it is not the best tool for large-scale transformation, parallel processing, or anomaly detection. It would normally consume prepared data rather than perform the entire workload.

• Footprinting is reconnaissance used to map an organization’s network, hosts, naming conventions, and services.
• A name such as fshare.int.complia.org suggests an internal file-sharing host (fshare) and an internal naming structure (int).
• This can reveal useful information to an attacker before attempting exploitation.

• ISP-assigned address space: Usually determined through public registration and DNS data, not an internal hostname.
• DNS sinkhole bypass: Would involve avoiding redirected malicious-domain queries.
• Initial access: DNS reconnaissance alone does not compromise the server.
• Data exfiltration: DNS tunneling typically generates many encoded or unusually long subdomain queries, not simply a meaningful internal hostname.

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

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.

• 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.

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.

• A — Capacity: The system must handle all current records and anticipated future records. A system that cannot cope with volume will quickly become ineffective.
• C — Accuracy: Academic records are critical, so the new system must be at least as accurate as the existing system and comparable systems. Poor accuracy could cause serious administrative and reputational problems.
• D — Integration: Linking with the university’s financial systems supports consistency and avoids duplicate data entry, especially for registration, deregistration and fee-related transactions.

• B — Parallel running: This is a useful implementation and risk-control technique, but it is not an essential feature of the system itself. It may also be expensive and time-consuming.
• E — Internet access for all information: This creates significant confidentiality and security risks. External access might be needed for selected services, but unrestricted access to all information is not essential and would be inappropriate for student records.

• Escape to host: A virtualization attack where code escapes a guest VM and accesses the host system. Nothing in the scenario mentions virtualization.
• Browser extension: Can redirect or manipulate web-browser traffic, but not normally database-server traffic.
• Valid accounts: Describes using stolen or compromised credentials, not redirecting network traffic.
• Process injection: Injecting malicious code into a legitimate database or networking process could allow an attacker to alter how that process handles outgoing traffic.

• Deterrent control: The signs warning that people may be filmed can discourage unauthorized or malicious activity. They do not directly stop the action; they influence behavior.
• Detective control: CCTV records or monitors activity so security personnel can identify events or investigate them afterward.

• Preventive: Stops an incident from occurring, such as access control.
• Corrective: Restores systems after an incident.
• Directive: Instructs people to behave in a certain way, such as a security policy.
• Compensating: An alternative control used when the preferred control is not feasible.

• Sales processes: Define the available Opportunity stages for each team.
• Record types: Connect each team to its appropriate sales process and page layout.
• Page layouts: Control which fields and related sections each team sees.

• Solar market team 1
• Solar market team 2
• Installation Services team

• One sales process: Cannot provide different Opportunity stages for each team.
• One page layout: Cannot provide different field arrangements or fields by team.
• Three page layouts alone: Page layouts control fields, but not the available stages.

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

• Disable high concurrency: This changes session-sharing behavior but does not provide dedicated compute or true workload separation.
• Modify the number of executors: Adjusts resources within a Spark job; it does not isolate bronze and silver processes.
• Set the default environment: Controls libraries and runtime configuration, not compute isolation.

• The load balancer provides the listener’s frontend IP address.
• The active SQL Server node must also respond to that same listener IP.
• Enabling Floating IP allows the listener IP to be preserved and handled correctly by the active replica.
• Without it, SQL connections may be sent to a node that cannot correctly claim the listener address.

• A health probe for the SQL Server port
• A load-balancing rule using the listener port
• Floating IP enabled on that rule

• Data only needs to be current at 7 AM each day, so scheduled refresh is sufficient.
• Import mode provides the fastest report interaction because data is stored in Power BI’s in-memory engine.
• It supports row-level security (RLS), including the USERNAME() filter.
• You can limit the imported data to the current year and previous three years to reduce model size.
• DirectQuery would generally provide slower visual response times and is unnecessary here.
• Dual is mainly useful in composite models where some tables use DirectQuery and others use Import. That is not required by this scenario.
• Live connection is not appropriate because you are creating the semantic model.

• Limiting the number of MAC addresses learned on a switch port
• Allowing only specific, approved MAC addresses
• Taking action when the limit is exceeded, such as dropping frames or disabling the port

• Response and resolution times
• Availability or uptime requirements
• Performance targets
• Support responsibilities
• Penalties or remedies if requirements aren’t met

• SOW (Statement of Work): Describes the work, deliverables, scope, and schedule for a project.
• MOA (Memorandum of Agreement): Documents agreed-upon responsibilities or cooperation between parties.
• MOU (Memorandum of Understanding): Records a general mutual understanding, often without detailed enforceable service targets.

• 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.

• Process Builder: Automates actions based on record changes; it does not create interactive user forms.
• Approval Process: Routes records for approval and captures approval decisions.
• Outbound Message: Sends information to an external system; it does not provide a user interface.

• HTTPS: Secure web traffic, not general command-line server administration.
• SNMPv3: Secure network monitoring and management, not interactive server login.
• RDP: Provides graphical remote desktop access. It can be secure, but it is not the direct replacement for Telnet in this scenario.
• SMTP: Used to send email.

• Each directory is a separate identity boundary.
• Managing multiple directories increases administrative overhead.
• Users and administrators may need separate identities or additional configuration across tenants.
• Resources in a subscription are associated with one Microsoft Entra tenant.

• Management groups for governance across subscriptions
• Separate subscriptions for divisions when appropriate
• Resource groups to organize resources
• Azure role-based access control (RBAC) to give each division’s administrator access only to their own resources

• Allow only approved MAC addresses
• Limit the number of learned addresses
• Shut down or restrict a port when a violation occurs

• Load balancer: Distributes application traffic; it does not protect switch MAC tables.
• IPS: May detect some attack traffic, but it is not the direct control for limiting MAC addresses on switch ports.
• NGFW: Filters routed network traffic, while this attack targets Layer 2 switch behavior.

• contoso.onmicrosoft.com
• contoso1.onmicrosoft.com

• onmicrosoft.com domains: Maximum of five per tenant.
• Custom domains: Domains that your organization owns and verifies in Microsoft 365.

• Microsoft Foundry is an enterprise platform for developers, data scientists, and IT teams.
• It supports the full AI application lifecycle: selecting models, connecting enterprise data, developing, evaluating, deploying, monitoring, and scaling solutions.
• It can include visual tools and low-code experiences, but it is not primarily designed to enable business users to build complete generative AI solutions independently.

• B: You still need to select and configure an appropriate model.
• C: Business users may participate through visual tools, but they are not the primary target audience.
• D: Foundry includes low-code tools, but it is not fundamentally a low-code-only platform.

• 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.

• Something you know: Password or PIN
• Something you have: Security token, smart card, or phone receiving an authentication code
• Something you are: Fingerprint or facial recognition
• Somewhere you are: Location-based verification

• Prevention costs: Avoiding defects, such as staff training and improved product design. The company has invested in these.
• Appraisal costs: Detecting defects before products reach customers, such as inspection and testing. The planned batch sampling has not been implemented.
• Internal failure costs: Correcting defects found before delivery.
• External failure costs: Dealing with defects after delivery, such as refunds, replacements, complaints and lost sales.

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

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

• Disable high concurrency: Changes workspace-wide behavior and is not the targeted way to isolate these workloads.
• Modify the number of executors: Adjusts capacity and performance, but does not provide workload isolation.
• Set the default environment: Controls libraries and runtime configuration, not compute isolation.

• A: Describes an update-set conflict, not a Dictionary Override.
• B: Describes a configuration item or change concept.
• C: Describes an approval or workflow activity.

xml 
<apex:page> 
    <apex:stylesheet value="{!URLFOR($Resource.MyStyles, 'styles/main.css')}" /> 
</apex:page>

• <apex:includeScript> is for JavaScript.
• <apex:includeStyle> is not a valid Visualforce component.
• <apex:require> is not the Visualforce tag used to load CSS.

• A — Increased call deflection: o KCS disponibiliza conhecimento reutilizável para clientes e agentes, ajudando a resolver dúvidas sem abrir ou continuar chamadas.
• C — Reduced issue resolution time: os representantes reutilizam artigos e soluções já documentadas, acelerando o atendimento.
• E — Optimized use of resources: o conhecimento compartilhado reduz retrabalho e melhora o uso dos recursos da equipe.

1. Write a structured log entry to CloudWatch Logs containing:

1. Create a CloudWatch Logs metric filter that:

text 
ApiRequests 
Operation=GetOrders 
ResponseCode=500 
Version=2.4.0

• B is incorrect: CloudWatch Logs Insights queries analyze logs but do not directly publish metrics in this manner.
• C is incorrect: ALB access logs do not contain arbitrary Lambda response metadata as custom fields.
• D is incorrect: X-Ray traces and insights are not the appropriate mechanism for creating these custom, dimensioned application metrics.

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.

• Liability accounts (2000–2999) would incorrectly require dimensions, although they should have none.
• Expense accounts (6000–6998) would incorrectly require Customer, which should be optional.
• Account 6999 needs a separate rule because it requires all four dimensions, including Customer.

• 2000–2999: no dimensions
• 4000–4999: Department and Division required; Project and Customer optional
• 6000–6998: Department, Division, and Project required; Customer optional
• 6999: Department, Division, Project, and Customer required

• Act as the default gateway for devices in that VLAN
• Route traffic between different VLANs
• Provide management access to the switch

text 
interface vlan 10 
 ip address 192.168.10.1 255.255.255.0

• Determine risk tolerance: Tolerance defines how much variation or exposure the organization is willing to accept. Scenarios may help apply tolerance, but they do not primarily determine it.
• Determine risk appetite: Risk appetite is established at an enterprise or governance level. Scenarios help compare risks with the appetite; they do not normally establish it.
• Develop risk responses: Once risks are identified and assessed, scenarios support response planning. However, response development comes later.

• Authentication: Verifies who the user is.
• Authorization: Determines what the authenticated user is allowed to access.
• Accounting: Records login activity and resource usage.

• CIA: Confidentiality, integrity, and availability—the core security objectives.
• ACL: Access Control List; rules that permit or deny traffic or access.
• PEM: A format and standard commonly associated with encoded certificates and keys.

• Labels control access and protection, not blanket exclusion.
• If the user has permission to open a labeled file—especially if the label allows authenticated users to view it—Copilot can use that file in a summary.
• If the label applies encryption and the user lacks the required usage rights, Copilot should not use the file or reveal its contents.
• Copilot honors the user’s existing permissions, so it should not expose labeled content to an unauthorized user.

• Injection
• Broken access control
• Authentication failures
• Security misconfiguration
• Cross-site scripting

• STIX: A standardized language and format for exchanging threat intelligence.
• OVAL: Used to describe and assess system vulnerabilities and configuration issues.
• Threat intelligence feed: Provides current indicators and intelligence about threats, but not necessarily a structured overview of common application exploitation methods.
• CVE: A catalog of individually identified, publicly disclosed vulnerabilities.

• ??????? ?? ??????? ????? ?? ???? Discount ????? ????? ??? 0.05.
• ?? Power Query Editor? ???? ???? Discount ?? ????:

• ???? ?????? 0.05.

• Remove Errors: ???? ?????? ???? ????? ??? ?????? ???? ????? ??? ???????? ??? ??????.
• Keep Errors: ????? ??? ??????? ???? ??? ?????? ???? ??? ???????.
• Edit the query in the Query Errors group: ???? ?? ???? ????????? ???????? ???? ?? ?????? ??? ????? ???? ???????? ???????.

• 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.

• 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.

• netstat -tuln can show listening TCP ports.
• If the web service is not listening, or is bound only to 127.0.0.1, remote browsers cannot connect even though the server responds to ping.

• traceroute: Tests the path to the server, but ping already confirms basic reachability.
• tcpdump: Useful for detailed packet analysis, but it is more appropriate after checking whether a service is listening.
• arp: Helps troubleshoot local IP-to-MAC resolution, not an application-layer web connection.