Snowflake GES-C01 Exam Prep
SnowPro Specialty Gen AI (Page 11 )

• Create a record-triggered Flow on Opportunity.
• Run it when the record is created or updated.
• Add entry criteria such as Probability > 50%.
• Use Create Records to create the related Sales Demo Request, populating its Opportunity lookup.

• Apex Trigger: Possible, but unnecessary custom code for a straightforward automation requirement.
• Workflow Rule: Cannot create a related custom record.
• Process Builder: Could create a record, but Flow is Salesforce’s preferred and more capable declarative automation tool.

• Import: Copies data into the Power BI model. It requires scheduled or manual refresh, so it may not meet the two-minute requirement.
• Live connection: Connects to an existing Power BI semantic model or Analysis Services model; it is not the appropriate choice for connecting directly to the Azure SQL database in this scenario.

• Customer: Dual
• Date: Dual
• Sales: DirectQuery
• SalesAggregate: Import

• Sales – DirectQuery: Near-real-time data should not rely on an imported cache. DirectQuery sends queries to the source when visuals are loaded, allowing recent sales data to appear.
• SalesAggregate – Import: A weekly refresh is sufficient, and imported data generally gives faster visual performance because it is stored in Power BI’s in-memory cache.
• Customer and Date – Dual: These are dimension tables used with both the DirectQuery Sales table and the imported SalesAggregate table. Dual allows Power BI to use cached data when possible, while still behaving appropriately in queries involving DirectQuery data. This can improve performance and reduce unnecessary limited relationships.

• A. Modify CommunitiesSelfRegController

• C. Configure Communities registration to use a custom Visualforce page

• B. Modify the self-registration trigger — There is no standard “self-registration trigger” intended for this configuration. The registration logic is handled by the Visualforce controller.
• D. Configure a custom Apex controller — The standard approach is to modify the provided CommunitiesSelfRegController, rather than simply selecting a separate controller configuration.

• Manage multiple organizations from one hierarchy.
• Enterprise-wide policies, including repository visibility, forking, and GitHub Copilot policies.
• Centralized identity and access management, such as SAML SSO, SCIM provisioning, and—where applicable—Enterprise Managed Users.
• Centralized billing and licensing, including organization and Copilot seat management.
• Enterprise audit log, which aggregates activity across organizations.
• Security and compliance oversight, such as organization security visibility and enterprise-wide controls.
• Enterprise support and account management features, depending on the plan.

• Organization: manages its own repositories, teams, members, and local policies.
• Enterprise: governs multiple organizations and can enforce policies across them.

• Numerical flexibility: Adjusting the number of employees, such as using temporary, part-time or contract staff.
• Temporal flexibility: Varying when employees work, such as through flexitime, overtime or different working hours.
• Shift system flexibility: Changing work patterns or shift arrangements; it is not specifically about moving between tasks.

• The files are stored in a document library, which is exposed through the SharePoint Folder connector.
• The connector returns file metadata, including Folder Path, Name, and Content.
• In Power Query, filter Folder Path so only files in the manufacturing reports folder are retained.
• You can then combine the remaining Excel files because they all have the same structure.

• SharePoint List is for SharePoint lists, not document-library files.
• Combine & Load combines files immediately, before you filter to the required folder, and may include unwanted files.
• Transform gives you the opportunity to filter the file list first, which is more efficient and targeted.

• Uses on-premises data or resources
• Runs components in the cloud
• Can scale across multiple cloud environments when demand increases

• Public cloud: Resources are hosted entirely by a cloud provider.
• Private cloud: Resources are dedicated to one organization, usually in its own environment.
• Hybrid: Combines on-premises and cloud resources.

• Árvores de decisão: usam regras sequenciais, como “se característica X > valor, siga para este ramo”. São fáceis de visualizar e explicar. Atendem bem a problemas de classificação e regressão com alta interpretabilidade.

• Regressão linear: prevê um valor numérico contínuo, como preço, custo ou temperatura. Não é a escolha principal para classificar genes em categorias.

• Regressão logística: calcula a probabilidade de uma categoria. Pode atender à classificação, inclusive multiclasses, mas sua explicação costuma ser menos intuitiva que uma árvore para documentar decisões.

• Redes neurais: atendem a tarefas complexas, como imagens, texto e padrões não lineares. Porém, são menos interpretáveis, funcionando mais como uma “caixa-preta”.

Simple explanation

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

• s3:GetObject for the relevant objects
• s3:ListBucket if listing is required
• Appropriate bucket and object resource permissions

• B: Making the bucket public is insecure and unnecessary.
• C: Prompt engineering cannot override AWS IAM or encryption permissions.
• D: Data sensitivity does not determine whether the role can access it.

• Approve major information security policies
• Allocate funding and resources
• Set the organization’s risk appetite
• Ensure security supports business objectives

• Evaluating vendors is generally handled by security, procurement, or technical teams.
• Assessing risks is typically performed by security and risk-management professionals, with management accepting or prioritizing the risks.
• Monitoring regulatory adherence is usually handled by compliance, audit, or security functions.

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

• Program and project management
• Risk management
• Cloud financial management
• Data governance
• Portfolio management

• Sustainability
• Performance efficiency
• Reliability

• Aggregation happens once, during the scheduled job.
• Dashboard users query a relatively small, precomputed table.
• Repeated users do not trigger expensive aggregations against the detailed sales table.
• Overwriting is appropriate because the summary is rebuilt for the reporting period.

• B: Structured Streaming is unnecessary for data that only needs daily refreshes and adds operational/compute overhead.
• C: A view recomputes the aggregation at query time, increasing latency and query cost.
• D: Delta caching may improve reads but does not replace the need to materialize the expensive aggregation, and cache availability is not the main design guarantee.

• Fileless malware: Nothing in the command indicates malware executing only in memory.
• Living-off-the-land binaries: Mimikatz is a credential-access tool, not a normal system utility used for LOLBin abuse.
• Social engineering: The command shows technical credential abuse, not manipulation of an accountant.

• Code suggestions: Inline completions as you write code, such as lines, functions, or blocks.
• Chat: An interactive interface for asking questions, explaining code, generating code, and helping with debugging.

• Knowledge Base: Not listed as a standard Copilot Individual IDE feature in this context.
• Pull Request Diff Analysis: More closely associated with GitHub-based code review or pull-request features, not the core Individual IDE extension capabilities.

• A: Allow SAN certificates — SANs are used to identify valid hostnames in a certificate. They do not bypass trust validation.
• C: Open the secure LDAP port — A blocked port would normally cause a timeout or connection-refused error, not certificate errors.
• D: Increase the TLS version on the RA — The issue concerns certificate trust, not the organization’s registration authority.

• A — Too infrequent: Formal strategies are often reviewed only every three to five years. This can make the organisation slow to respond to rapid changes in technology, competitors, regulation or customer needs.

• C — Relies on predicting the future: The approach assumes senior managers can make reasonably reliable forecasts and assumptions. In uncertain environments, these assumptions may quickly become invalid.

• E — Can restrict radical innovation: Formal planning tends to favour existing information, established objectives and incremental improvements. This may discourage experimental or highly innovative strategies that emerge from lower levels of the organisation.

• B concerns the difficulty of achieving competitive advantage through core competences when competing with focused specialists. It is not specifically a drawback of the formal top-down planning process.
• D is an activity organisations should undertake—continuous monitoring—not a drawback of the approach itself.

• BCP (Business Continuity Plan): Ensures the organization can continue its broader business operations during and after a disruption. It is broader than the IT-focused recovery required here.
• Communication plan: Defines how information is shared with employees, the public, and other stakeholders; it does not restore systems.
• IRP (Incident Response Plan): Handles and contains security incidents, such as malware or unauthorized access. A tornado is a disaster, not primarily a cybersecurity incident.

• 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.

• A. Tuning system software: This is a corrective action, not an analysis method. Tuning should be based on measured performance data.
• B. User dissatisfaction reports: Useful as an indicator, but subjective and insufficient for diagnosing the cause.
• D. Off-peak utilization and response time: This may hide problems occurring during peak periods. Performance analysis should cover representative or peak workloads.

• 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.

• Reviewing security policies and standards checks whether controls are documented, not whether they work.
• Reviewing security logs may show that monitoring is occurring, but does not directly establish that preventive controls are effective.
• Analyzing technical security practices is broad and may assess implementation, but it is less objective than an actual controlled attack.

• Design/compliance effectiveness: policies, standards, and procedures
• Operational effectiveness: logs, records, and evidence that controls operate
• Technical security effectiveness: penetration testing or vulnerability testing

• Accept: Acknowledge the risk and choose not to take 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 condition that creates the risk.

• 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.

• Resources that do not need internet access should remain on private network segments.
• Internet-facing access should be restricted to systems that require it.
• Access should be explicitly allowed rather than broadly exposed.

• A: A single administrator with access to core functions may violate least privilege if that access is broader than necessary.
• B: Inspecting traffic supports monitoring and defense, but does not itself limit privileges.
• C: Updating routing configurations supports availability and connectivity, not least privilege.

• 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.

• 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.

1. Identify the fact table

• Records something that happened, such as a sale, test, appointment, or measurement
• Contains foreign keys to other tables
• Contains measures or numeric results
• Has many rows

2. Identify a dimension table

• Describe people, products, dates, locations, or departments
• Contain descriptive columns
• Are referenced by the fact table
• Have fewer rows than the fact table

3. Identify the surrogate key

• System-generated
• Unique within the dimension
• Often named PatientKey, CustomerKey, or similar
• Usually an integer
• Not meaningful outside the model

• 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.

• BIOS language support: Useful for usability, but not whether the PC can operate electrically.
• Supply chain security: Concerns procurement and hardware trust, not deployment across countries.
• Power efficiency: Important for energy usage, but it does not ensure compatibility with local power systems.

• nomes de pessoas;
• organizações;
• locais;
• datas;
• números de processos;
• leis ou contratos.

• NER = identifica informações específicas e classificáveis.
• Sumarização = reduz um documento e apresenta seus pontos principais.

• An Azure pay-as-you-go subscription follows an operational expenditure (OpEx) model.
• With OpEx, the organization pays for services as they are used, typically based on consumption.
• There is no need to purchase and maintain physical servers upfront.
• This contrasts with capital expenditure (CapEx), where the company makes a significant upfront investment in infrastructure, such as on-premises Hyper-V hosts.

• 16GB RAM: A 64-bit OS is needed to use more than roughly 4GB effectively, but RAM capacity does not prove the CPU supports 64-bit operation.
• 500GB HDD: Storage capacity has no bearing on OS architecture.
• 1Gbps Ethernet: Network speed is unrelated to CPU architecture.

• B — Prompts and suggestions retained for 28 days
• C — User engagement data kept for two years

• The key distinction is between content data—your prompts, code context, and generated suggestions—and engagement data, such as usage activity.
• Do not confuse retention with training: enterprise Copilot data is generally not used to train GitHub’s models without appropriate authorization.
• For a current exam, verify the policy version cited by the exam provider. The key’s C is likely correct, but B should be treated cautiously and may no longer reflect the current policy.

• B. The community must be built with the Customer Account Portal template.

• C. An experience ID (expid) or placeholder parameter must be used in the URL.

• A: The Visualforce + Salesforce Tabs template does not provide this dynamic branding capability.
• D: An external CMS is not required. The branding configuration is handled within Salesforce Experience Cloud.

• A. IDS attack signatures: An IDS primarily detects suspicious network activity and usually does not provide dedicated file-upload malware scanning. It is generally detective rather than preventive.
• C. Load balancer: Distributes traffic among servers and improves availability; it does not inspect documents for malware.
• D. WAF: Helps block web-application attacks such as SQL injection, command injection, and XSS. Although a WAF may inspect upload requests, malware detection in PDF files is more directly addressed by antivirus or content-scanning functionality.

• Encryption to preserve confidentiality
• Integrity protection to detect alteration
• Authentication of the server through certificates

• SHA-256: A hashing algorithm; it does not encrypt data for transmission.
• SSL 3.0: Obsolete and insecure. It should not be used.
• AES-256: A strong encryption algorithm, but by itself it does not provide the complete secure communication protocol needed for data in transit.

• Prevent connections to malware command-and-control servers
• Identify infected systems making those DNS requests
• Collect information for incident response

• A: Attackers do not normally use sinkholes to map a company’s domain structure.
• B: Redirecting employees from legitimate sites to attacker-owned sites describes malicious DNS manipulation, not a defensive sinkhole.
• D: Attracting attackers away from real resources is more closely associated with a honeypot or deception system.

• Failed login attempts
• The account being targeted
• The source user or system
• Time and frequency of attempts

• Two-factor authentication: Helps prevent unauthorized access, but does not primarily detect the employee’s attempts.
• Firewall: Controls network traffic; it generally does not monitor individual login attempts.
• Intrusion prevention system (IPS): Can detect certain network attacks, but this scenario is best addressed through authentication and audit logging.

text 
interface GigabitEthernet0/0.10 
 encapsulation dot1Q 3

• .10 is the router’s local subinterface number.
• dot1Q 3 identifies the 802.1Q VLAN tag carried on the trunk.

text 
interface GigabitEthernet0/0.3 
 encapsulation dot1Q 3

text 
interface GigabitEthernet0/0.2 
 encapsulation dot1Q 2

• Matching hashes: The software is unchanged.
• Different hashes: The software was modified or corrupted.

• Encryption: Protects confidentiality.
• Baselines: Define approved configurations or normal performance.
• Tokenization: Replaces sensitive data with tokens.

• View/inspect configuration: Possible.
• Modify the installed application or its S-Controls: Typically restricted in a test-drive org.

sql 
SELECT COUNT(*) FROM table;

• A: It does not normally need to scan all data files for this operation.
• B: Results are not simply reused from a query cache every time. Caching is separate from Delta’s metadata optimization.
• D: The relevant metadata is maintained through the Delta transaction log, not directly treated as a Parquet-file metadata operation in this context.

• The listener has a virtual IP address on the load balancer.
• The active SQL Server replica must respond using the listener’s IP address, not its own VM IP.
• Floating IP allows the listener IP to be preserved and returned by the active replica.
• This is required for the SQL Always On listener configuration.

• A health probe for the SQL listener/cluster role
• The SQL Server listener port, commonly 1433
• Appropriate backend pool membership

sql 
GRANT ALTER ON SCHEMA::schemaA TO User1;

• TRUNCATE TABLE is a DDL operation, not a normal DELETE.
• Having DELETE permission on a table is not sufficient to truncate it.
• The minimum relevant permission is ALTER on the table.
• Granting ALTER on SCHEMA::schemaA allows the user to truncate tables within schemaA.
• It does not grant equivalent permissions on schemaB or schemaC, satisfying least privilege.

• A. Number ? Decimal — Correct. Salesforce Number fields are represented in Apex as Decimal.
• D. Date/Time ? Datetime — This is correct conceptually, but “Dateline” is not an Apex type. If the option literally says “Dateline,” it is incorrect.
• E. Checkbox ? Boolean — Correct. A checkbox contains true or false.

• Number ? Integer — A Number field maps to Decimal, even when its scale is zero.
• Text Area ? List<String> — A text area maps to a single String, not a list.

• D — Create sibling resource pools for the Production VMs and Test VMs.

• B — Configure a memory reservation on the Production resource pool.

• Shares only determine relative priority when resources are scarce; they do not guarantee memory.
• A parent resource pool alone does not provide a guarantee.
• A child pool for Test VMs does not reserve memory for Production.

• Modelo de embeddings multimodal: transforma texto e imagens em vetores no mesmo espaço semântico. Isso permite comparar uma consulta textual com imagens, ou uma imagem com textos relacionados.
• Modelo generativo multimodal: interpreta diferentes modalidades e gera conteúdo, mas não é a escolha específica para indexação e busca vetorial.
• Modelo de geração de imagens: cria imagens, portanto é inadequado.
• Modelo de embeddings de texto: não atende consultas com imagens.