SAP C_TS4C_2023 Exam Prep
SAP Certified Application Associate - SAP S/4HANA Cloud, public edition implementation with SAP Activate (Page 3 )

• To identify the number of errors: select Column quality. It shows the percentage and count of Valid, Error, and Empty values for each column.
• To resolve errors: use the appropriate error transformation:

• B — Data source settings in Power BI Desktop:

• D — Formula bar in Power Query Editor:

m 
  Excel.Workbook(File.Contents("new path"))

• E — Advanced Editor in Power Query Editor:

• A: Dataset settings in the Power BI service mainly handle credentials and gateway settings, not changing the local file path embedded in the PBIX.
• C: Current File data-load settings control refresh/load behavior, not the source location.

• The message came from the claimed sender (authentication)
• The message was not altered (integrity)
• The sender cannot easily deny sending it (non-repudiation)

• Attackers can send unsigned phishing emails.
• Attackers may compromise a legitimate account and send signed malicious emails.
• Users may still be tricked by a validly signed message.

text 
user<TAB>action<TAB>status

text 
user|action|status

• Colons: Although colons commonly appear in log data, they are not a supported delimiter choice in the FX workflow described by this exam question.
• Spaces: Spaces are not treated as a supported delimiter for this extraction method; ordinary text often contains variable spacing.

• Power BI dataset — Reuses the existing tables, relationships, and measures. You mainly create new visualizations.
• SharePoint folder — Connects to the source files, but you would need to rebuild the model and measures.
• Power BI dataflows — Primarily provide reusable data preparation; they do not automatically provide the existing report’s measures and model.
• Excel workbook — Requires reconnecting to and modeling the source data again.

• 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.

• Namespace: The namespace associated with the code where the checkpoint was set.
• Time: When the checkpoint was captured or executed.

• Exception: Exceptions are viewed through debug logs or execution results, not as the primary Checkpoints tab information.
• Debug Statement: System.debug() output belongs in the Logs tab. A checkpoint captures program state, such as variables and their values, at a specific point in execution.

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.

• Default route: 0.0.0.0/0; used only when no more specific route exists.
• Network route: A route covering the destination, such as 10.10.13.0/24.
• Host route: An exact 10.10.13.10/32 entry in the routing table.
• Floating static route: A backup static route with a higher administrative distance.

• 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.

sql 
ALTER TABLE dbo.DimCustomer 
ADD CONSTRAINT PK_DimCustomer 
PRIMARY KEY NONCLUSTERED (CustomerKey) 
NOT ENFORCED;

1. ALTER TABLE dbo.DimCustomer
2. ADD CONSTRAINT PK_DimCustomer PRIMARY KEY NONCLUSTERED (CustomerKey)
3. NOT ENFORCED

• When the MVP will be defined — the MVP should already be understood sufficiently when assessing the business case.
• What the MVP is — useful information, but not the key requirement tested here.
• That the MVP is the same as project viability — incorrect. The MVP helps test viability; it is not identical to viability itself.

• Static IP address: Not needed if the workstation already has network connectivity.
• Subnet mask: Incorrect subnetting would usually prevent local communication, including pinging the server.
• Default gateway: Primarily affects communication outside the local network; it does not normally prevent finding an internal domain controller.

• B — Incorporate contextual output encoding/escaping: Encode untrusted data based on its context—HTML, attribute, JavaScript, or URL—so the browser treats it as data rather than executable code.
• D — Run untrusted HTML input through an HTML sanitization engine: Sanitization removes or neutralizes dangerous elements and attributes, such as script-related content, while preserving safe HTML where needed.

• A: Enabling client-side scripts does not prevent XSS. Script restrictions may reduce risk in some environments, but “enable” is not a general XSS control.
• C: Cookie inspection is unrelated to preventing injected scripts.
• E: The SameSite cookie attribute primarily helps mitigate CSRF, not XSS. It should not generally be described as an XSS prevention measure.

• SOSL searches text across objects and is not appropriate for selecting Account table columns.
• describeSObjects() provides metadata about objects and fields, but it does not itself build or execute the query.
• Dynamic Schema binding supports runtime determination of object and field information, which is required here.
• REST API is unnecessary because this is being implemented in Apex.

• A. Periodically rotate responsibilities: May reduce some risks, but it does not directly detect unauthorized changes.
• B. Review segregation-of-duties conflicts: Identifies incompatible access combinations, not whether a specific data change was unauthorized.
• C. Log changes in an outside application: Logs provide evidence, but someone must review and analyze them. Logging alone does not detect misuse.
• D. Independent review: Directly detects unauthorized changes and reduces the risk that the person making the change can conceal it.

• MFA adds an additional authentication factor, such as a phone notification or verification code.
• It helps prevent unauthorized sign-ins, even if a password is compromised.
• It does not encrypt, store, or protect credentials used by deployment processes.

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

• 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.

• Controlar o fluxo de dados entre S3 e SageMaker;
• Aplicar regras de segurança por meio da VPC;
• Reduzir a exposição dos dados;
• Permitir acesso privado ao bucket do S3.

• Amazon Inspector: avalia vulnerabilidades, mas não gerencia o fluxo de dados.
• Amazon Macie: ajuda a descobrir e proteger dados sensíveis no S3, mas não cria a conexão com o SageMaker.
• S3 Glacier Deep Archive: é uma classe de armazenamento para arquivamento, não uma solução de conectividade.

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

• CIA: Confidentiality, integrity, and availability—the three core security goals.
• ACL: Access Control List, which defines permitted or denied traffic or access.
• PEM: A certificate and key encoding format, not the primary function of RADIUS.

• 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

1. The original app version exists.
2. You create and publish a new version, so there are now two versions.
3. When you restore the previous version, Power Apps does not delete or overwrite the newer version. Instead, it creates another version based on the restored one.

• Original version
• Newly created and published version
• New version created by the restore operation

1. Discovery tries the SSH probe first.
2. SSH fails.
3. Discovery tries SNMP, which succeeds.
4. Discovery records SNMP as the preferred service for that IP.
5. Future discoveries try SNMP first.

• Classification identifies the type of device, such as a server, router, or printer.
• Credential affinity remembers which credentials work for a device.
• MID Server affinity associates a device or network with a particular MID Server.
• IP service affinity specifically controls the preferred discovery protocol or service.

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.

• Azure Cosmos DB is a globally distributed NoSQL database service. It stores and retrieves application data, but it does not provide the complete environment for building, testing, and deploying predictive analytics models.
• Azure Machine Learning is the appropriate service for this requirement. It supports creating experiments, training and testing models, and deploying them for predictions.
• Azure Machine Learning Studio provides the browser-based interface for these tasks.

• Each team’s Bedrock workflow uses a separate IAM service role.
• The role’s Amazon S3 permissions can be limited to only that team’s customer folder or objects.
• This enforces least privilege and prevents one team’s Bedrock application from accessing another team’s data.
• Access is enforced by AWS permissions, not by asking users to provide a customer name in each request.

• A single role with broad S3 access does not provide team-level isolation.
• Asking teams to specify a customer name is not an access-control mechanism.
• Redacting data does not prevent unauthorized access.
• A bucket policy alone is insufficient unless it explicitly enforces the required team-role restrictions.

• CSIRT: A team that responds to and manages security incidents.
• CVSS: A scoring system for rating the severity of vulnerabilities.
• SOAR: A technology platform for automating and coordinating security operations and incident response.

• Recovery Services vault — stores Site Recovery configuration and recovery metadata.
• Hyper-V site — represents the on-premises Hyper-V environment.
• Azure virtual network — the target network where the replicated VM will run after failover. Since Azure VMs already use the same virtual network, that VNet can be selected as the target.
• Storage account or managed-disk target, depending on the ASR configuration and portal version.
• Provider/agent on the Hyper-V server — enables replication from Hyper-V to Azure.

• 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.

Correct reasoning

• Create storage5 as a General-purpose v2 (StorageV2) account.
• Configure Blob object replication from storage5 to an existing compatible storage account.
• The destination must support object replication—typically another StorageV2 or premium block blob account.
• Blob versioning must be enabled on both accounts.
• Blob change feed must be enabled on the source account.
• The accounts must meet Azure’s object-replication requirements, including being in supported regions and having compatible configuration.

• Accept: Acknowledge the risk and take no additional action.
• Transfer: Shift the risk or financial impact to another party, such as through insurance or a contract.
• Mitigate: Reduce the likelihood or impact using controls, such as firewalls, training, or backups.
• Avoid: Eliminate the activity that creates the risk.

• 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.

• Distinct values = 69

• Unique values = 4

• 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.

1. Clear principles and boundaries — Employees have freedom, but decisions must remain within clear organizational values, policies and limits.
2. High degree of freedom — Managers are trusted to make decisions rather than seeking continual approval from senior management.
3. Frontline customer responsibility — Customer-facing managers should be empowered to manage customer relationships and respond quickly to needs.
4. Transparent and ethical information — Information should be openly available and used honestly, supporting trust and informed decision-making.

• 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.

• One physical NIC is active and carries traffic.
• Another NIC remains on standby.
• If the active uplink fails, traffic switches to the backup uplink.
• This provides redundancy without requiring special switch-side link aggregation configuration.

• Balance-SLB: Distributes traffic based on source load balancing; not the default.
• Balance-TCP: Uses dynamic TCP traffic balancing and generally requires appropriate network-switch configuration.
• No Uplink Bond: Incorrect because vs0 is normally configured with redundant uplinks.

Step 1: Calculate the rights issue price

Step 2: Calculate the number of new shares

Step 3: Calculate the value after the issue and project

• Rights issue proceeds: $21.6m
• Project NPV: $5m

Step 4: Calculate the theoretical ex-rights price

• Required response and resolution times
• Availability or uptime targets
• Performance standards
• Support obligations
• Remedies or penalties for failing to meet the terms

• SOW (Statement of Work): Defines the project’s scope, tasks, deliverables, and schedule.
• MOA (Memorandum of Agreement): Describes agreed responsibilities between parties, often for a specific activity.
• MOU (Memorandum of Understanding): Records a mutual understanding or intention, usually less formal than a contract.

• B: Não é preciso implantar o modelo em um endpoint do Amazon SageMaker, pois o Bedrock já oferece a infraestrutura de inferência.
• C: O SageMaker Model Registry é usado para gerenciar modelos no SageMaker, não é requisito para modelos customizados no Bedrock.
• D: Não existe uma etapa geral de “conceder acesso” ao modelo customizado como requisito principal de uso. O ponto essencial é adquirir o Provisioned Throughput.

• 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.