UiPath UiRPA Exam Prep
UiPath Certified RPA Associate v1.0 (Page 5 )

• Workspace: Stores notebooks, libraries, jobs, and other project resources.
• Notebooks: Interactive documents containing code, queries, visualizations, and explanations. Common languages include Python, SQL, Scala, and R.
• Clusters: Groups of virtual machines that run Spark workloads. Clusters can be started, stopped, and automatically scaled.
• Data access: Databricks can read from services such as Azure Data Lake Storage, Azure Blob Storage, and Azure SQL.
• Jobs: Automate notebooks or data-processing workflows on a schedule or in response to events.

• 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.

• Elicited and documented customer requirements
• Converted them into clear, measurable specifications
• Validated the requirements with the customer
• Used them as the basis for design, quality checks, and acceptance

• A: Requirements should reflect the customer’s needs—not the supplier’s standards.
• B: Iteration review planning does not replace proper requirements collection.
• D: A retrospective occurs after work is completed and is mainly for process improvement, not initial requirements definition.

• Detect risky sign-ins from unfamiliar or unidentified IP addresses
• Evaluate user or sign-in risk
• Automatically require a password change because of a risky sign-in

• User risk policy: Can require a user to securely change their password when the account may be compromised.
• Sign-in risk policy: Can require MFA or block access based on the risk of a particular sign-in.

• 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.

• Identity provider (IdP): Authenticates users and asserts their identity.
• Service provider (SP): The application being accessed—in this case, Salesforce/the employee portal.
• Identity store: A directory that stores user identities, such as Active Directory.
• Authentication store: A system used to validate credentials.

kusto 
Event 
| summarize make_set(EventID) by Computer

• summarize groups records.
• by Computer creates one result row per virtual machine.
• make_set(EventID) returns an array containing unique event IDs for that computer.

kusto 
| summarize make_list(EventID) by Computer

• Idioma: “Responda em português.”
• Tamanho: “Responda em até três frases.”
• Formato: “Use uma lista com três recomendações.”
• Objetivo: “Recomende produtos com base nas necessidades do cliente.”

• Mudar o tamanho do LLM: pode alterar capacidade e custo, mas não garante idioma ou respostas curtas.
• Aumentar a temperatura: aumenta a criatividade e a aleatoriedade; não controla diretamente o tamanho ou idioma.
• Aumentar o Top K: permite considerar mais tokens prováveis, aumentando a variedade; também não é o mecanismo principal para controlar idioma ou comprimento.

• Filtering or reshaping columns
• Joining with an analysis-specific dataset
• Creating calculated fields
• Applying business logic for a particular project

• Data blending: Combining different data sources, not specifically the final processing step.
• Data enhancement: A broad term for enriching data.
• Data testing: Checking data quality or pipeline correctness.
• Last-mile ETL: The precise term for additional transformations performed after the main pipeline, often directly before analytics or reporting.

• Help the team identify the causes of delays.
• Encourage continuous improvement through retrospectives.
• Support the team in changing its process, tools, or collaboration methods.
• Help remove impediments that the team cannot resolve independently.

• A: An impediment log may help, but simply maintaining it does not ensure the impediments are resolved.
• B: Directing the team to solutions conflicts with agile self-management.
• C: Adding impediments to the product backlog could delay their resolution and treats them like product features.

• Batch processing, such as scheduled data transformations
• Streaming processing, such as continuously ingesting events

• Manipulating data with multiple languages: Mainly a benefit of Databricks and Spark.
• Real-time notebook collaboration: A workspace/notebook feature.
• Alerts for query failures: A Databricks SQL or job-monitoring feature.
• Distributing complex operations: Primarily a Spark compute capability.

• 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.

• Import mode loads the data into the Power BI model. Visuals query the in-memory model, which generally provides faster calculation and rendering than DirectQuery.
• Import mode also minimizes online processing because report interactions do not send queries back to the dataflow or SQL Server.
• A daily refresh can load data through the previous day, satisfying the freshness requirement without unnecessary hourly processing.

• DirectQuery keeps querying the data source or dataflow during report use, increasing online processing and potentially slowing visuals.
• Adding a gateway enables connectivity for on-premises sources, but it does not remove the performance disadvantages of DirectQuery.
• An hourly Power Automate refresh is unnecessary when the requirement is only data through the previous day and creates additional processing overhead.

• How quickly the vendor must respond to an incident or request
• Target resolution times
• Availability or uptime requirements
• Performance metrics and penalties for not meeting them

• SOW (Statement of Work): Describes the project’s scope, tasks, deliverables, and timeline.
• MOA (Memorandum of Agreement): Documents a formal agreement to cooperate or perform specific activities.
• MOU (Memorandum of Understanding): Records a mutual understanding or intent, often less binding than a contract.

• Check whether the data is accurate, complete, and properly prepared.
• Confirm that the pattern is not caused by an outlier, data-quality problem, or modeling issue.
• If the data is valid, treat the result as a potentially valuable new business insight.

• A: A data scientist may help, but expert validation and data-quality checking come first.
• C: Filtering out inconvenient data risks hiding a valid insight.
• D: Einstein’s result should not be accepted without verification simply because it produced the finding.

• Replace the keyboard: More expensive and unnecessary before simpler causes are ruled out.
• Replace the key switch: Laptop keyboards generally aren’t designed for individual switch replacement.
• Replace the circuit board: Excessive for a single nonworking key and not a cost-effective first step.

• Progress iteratively with feedback focuses on making improvements in manageable steps and learning from feedback.
• Optimize and automate focuses on maximizing value from resources and automating suitable activities.
• Start where you are focuses on assessing the current situation and reusing what already exists.

• If the Facebook user is new, Salesforce invokes createUser.
• If the user already exists, Salesforce can invoke updateUser.
• The handler can read the latest data from Facebook, such as name, email, or other profile attributes, and update the corresponding Salesforce user.

• B: A scheduled job is unnecessary and would not provide real-time synchronization during authentication.
• C: A Facebook signed request is not the standard mechanism for updating Salesforce user records in this authentication-provider setup.
• D: SAML Just-in-Time provisioning applies to SAML identity providers, not Facebook OAuth authentication.

• A. A virtual network gateway
• D. A virtual network

• Azure virtual machines must be connected to an Azure virtual network (VNet). The VNet provides private IP addressing and network connectivity for the VMs.
• A virtual network gateway enables communication between the Azure VNet and the on-premises network, typically through a site-to-site VPN or ExpressRoute connection.

• Load balancer: Distributes traffic among Azure VMs; it does not connect Azure to an on-premises network.
• Application gateway: Provides web-application load balancing and Layer 7 routing; it is not the normal resource for on-premises connectivity.
• Gateway subnet: A gateway subnet is required inside the VNet when deploying a virtual network gateway, but the question’s intended two primary resources are the VNet and virtual network gateway.

• 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.

1. Ensure BOMs can include subcomponents ? Configure an entity relationship

1. Report changes made by engineers ? Enable auditing

• Configure entity relationship
• Configure auditing

• Define the contractor’s deliverables, responsibilities, acceptance criteria, and deadlines.
• Agree on a reporting cadence to monitor progress.
• Allow the local company to use its expertise and manage its own work.

• A: “Under the supervision of the project manager” suggests excessive direct control and is less empowering.
• B: Micromanaging prevents the contractor from functioning independently and is inefficient.
• D: Deploying the contractor’s staff under the PM’s supervision creates a staffing/control arrangement rather than empowering the contracted company.

• 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.

• Inherent risk: Risk that exists before controls are implemented.
• Avoided risk: Risk eliminated by choosing not to perform the risky activity.
• Operational risk: Risk arising from failures in processes, people, systems, or daily operations.

• AWS IoT Greengrass supports local ML inference using models trained in Amazon SageMaker.
• The model and inference code run on the factory’s local server, so processing continues even when internet connectivity is unavailable.
• A Greengrass component can:

• This provides low latency and avoids sending images to AWS for every inference.

• A: Uses AWS-hosted services and therefore depends on internet connectivity. It would fail during an outage.
• C: Snowball Edge is unnecessary for this use case and adds deployment complexity. A local Greengrass server is the intended edge-inference solution.
• D: Amazon Monitron is designed for monitoring industrial equipment health, not analyzing camera images with a custom SageMaker model.

• The policy is confidential, and the requester is no longer authorized merely because they used to work for the organization.
• The security professional should not disclose it by email or display it on a device without authorization.
• Using official channels allows the organization’s owner or information custodian to verify:

• 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.

• Multi-factor authentication
• A secure password change for users whose credentials may be compromised

• Interactive development and exploration
• Small datasets
• Lightweight transformations or testing
• Avoiding the overhead and cost of multiple workers

• Automated reports: Jobs may benefit from job clusters or SQL warehouses.
• Working with SQL in Databricks SQL: Databricks SQL warehouses are the relevant compute option.
• Automatically scaling for larger data: A multi-node cluster with autoscaling is more suitable.
• Large amounts of data: Distributed worker nodes are generally needed.

cmd 
powershell.exe -ExecutionPolicy Bypass -File C:\Scripts\Configure-VM.ps1

• GPO logon script: Runs only when a user logs on, so configuration may be delayed and is user-dependent.
• GPO startup script: Can work, but requires the VMs to be domain-joined and introduces GPO dependency. It is not specifically tied to Windows deployment.
• Place scripts in a VHD: Merely makes the files available; it does not execute them.

• 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.

• A. Microsoft 365 group with Assigned membership
• C. Microsoft 365 group with Dynamic User membership

Why?

• Assigned membership: You explicitly add User1, User2, and User3.
• Dynamic User membership: Membership is automatically determined by a rule based on user attributes.

Why the other options are incorrect

• B and D: Security groups do not support the Microsoft 365 group expiration policy.
• E: Dynamic Device groups are intended for devices, not these users, and are also security groups.

1. Which host originated the infection

1. Which remaining hosts are infected

• Secret scope: A named container that groups related secrets and defines access permissions. Example: finance-prod.
• Secret key: The name of an individual secret stored inside that scope. Example: db-password.

text 
Scope: finance-prod 
  Key: db-username 
  Key: db-password

python 
dbutils.secrets.get( 
    scope="finance-prod", 
    key="db-password" 
)

• Issuer: Identifies the party issuing a SAML message, commonly the IdP in the SAML assertion. It is not the Salesforce setting used to distinguish Salesforce from other service providers.
• Identity Provider Login URL: Specifies where Salesforce sends users for authentication; it does not identify Salesforce.
• SAML Identity Location: Specifies where the user identity is found in the SAML assertion, such as the subject or an attribute.

• You provision the virtual machine.
• You manage the guest operating system, applications, and configuration.
• Azure manages the physical servers, datacenter, and underlying virtualization infrastructure.

• Create and manage approved IT services as products
• Control which users can deploy those products
• Apply governance, permissions, and constraints
• Use and manage infrastructure-as-code templates, such as AWS CloudFormation templates

• AWS Resource Explorer: Helps find and browse AWS resources; it does not govern IaC deployments.
• AWS Organizations: Manages accounts, consolidated billing, and organization-wide policies.
• AWS Systems Manager: Provides operational management, such as patching, automation, and parameter storage, but it is not primarily used to catalog and govern IaC-based service deployments.

• 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.

1. Determine which host was infected first—the originating host.
2. Decide whether each other host is clean or infected based on communication and event logs.

• Compare timestamps and find the earliest suspicious event.
• Look for the host that initiated the malicious connection, file transfer, exploit, or command—not merely a host that later received traffic.
• Follow the timeline through the firewall:

• A host is likely infected if it both receives suspicious activity and then initiates related malicious traffic.
• A host may be clean if the firewall blocked the connection and there is no evidence of execution or follow-on communication.

• Discovers sensitive data in Amazon S3 buckets
• Uses machine learning and pattern matching to identify data such as personally identifiable information (PII)
• Helps assess S3 security and privacy risks
• Generates findings for potentially sensitive or exposed data

• Amazon Detective: Investigates security findings and performs root-cause analysis.
• Amazon GuardDuty: Detects threats and suspicious activity across AWS accounts and workloads.
• AWS IAM Access Analyzer: Identifies resources that are accessible from outside their intended trust zone, such as publicly accessible S3 buckets.

• Create Power Query parameters for the Azure SQL server/database—or at least the database name.
• Use the parameter in the PBIX connection.
• Publish the same PBIX separately to the relevant development, test, and production workspaces.
• Set each dataset’s parameter value in the Power BI service so it points to the corresponding Azure SQL database.

• Development dataset ? DevelopmentDB
• Test dataset ? TestDB
• Production dataset ? ProductionDB

• The same PBIX is used for every lifecycle stage.
• Each stage consumes data from its matching database.
• Deployment pipelines are not required.
• Azure SQL is a cloud source, so gateway administration is generally avoided.
• Only the parameter value differs between published datasets, reducing maintenance.

bash 
docker run -it microsoft/azure-cli:0.10.17

• docker run starts an Azure CLI container; it does not automatically connect to the AKS cluster.
• The command does not run kubectl apply.
• The container would need the appropriate Kubernetes tools and AKS credentials.
• The device or container must obtain cluster credentials, typically using an AKS credential command, before running Kubernetes commands.

bash 
az aks get-credentials --resource-group <resource-group> --name <aks-cluster> 
kubectl apply -f myapp.yaml

• SQL injection
• Cross-site scripting (XSS)
• Malicious file uploads
• Common web-application exploits

• Layer 4 firewall: Filters primarily by IP addresses, ports, and transport protocols; it lacks detailed web-application inspection.
• NGFW: Provides advanced network filtering and may include application awareness, but a WAF is more specialized for protecting web applications.
• UTM: Combines several security functions in one device, but it is not specifically focused on web-application attacks.

• Modelo de embeddings de texto: trabalha principalmente com texto, não sendo adequado para imagens.
• Modelo generativo multimodal: pode interpretar ou gerar conteúdo de vários tipos, mas não é a opção específica para busca por similaridade.
• Modelo de geração de imagens: cria imagens a partir de entradas, não realiza busca multimodal.

• 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.

• 6-phone boxes: 6x
• 8-phone boxes: 8x

• Amazon DynamoDB — Managed NoSQL database, not PostgreSQL.
• Amazon Athena — Serverless service for querying data in S3; intended for analytics, not OLTP.
• Amazon EMR — Managed cluster platform for big-data frameworks such as Hadoop and Spark.

• 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.

• SQL injection (SQLi): Attacks databases by inserting malicious SQL commands.
• Cross-site scripting (XSS): Injects scripts into web pages viewed by other users.
• Sideloading: Installing an application from outside the official app store. It may install unauthorized apps, but it does not generally unlock the operating system or enable restricted system features.

• Voice devices ? VLAN 10
• Data devices ? VLAN 20
• SVI for VLAN 10 ? 192.168.10.1
• SVI for VLAN 20 ? 192.168.20.1

• A: Describes a physical trunk interface, not an SVI.
• B: An SVI can provide management access, but that is not its primary definition here.
• D: SVI does not compensate for insufficient physical ports; it is a logical interface.