Esri EAPA_2025 Exam Prep
ArcGIS Pro Associate 2025 (Page 6 )

• 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.

python 
def add_integers(a, b): 
    return a + b

• Uses def to define a function.
• Accepts two parameters, a and b.
• Uses return to send their sum back to the caller.
• Uses indentation to define the function body.

python 
result = add_integers(3, 4) 
result is 7

• A — Can help keep costs down and improve quality: The provider may have specialist expertise, efficient systems and economies of scale.
• B — There is a known fee if agreed in advance: A fixed or agreed fee can make costs more predictable and support budgeting.
• C — Allows management to focus on core operations and issues: Senior managers spend less time supervising routine finance processes and more time on strategic matters.

• Increased control: Control may decrease because the activity is performed externally.
• Increased independence: The organisation becomes dependent on the supplier.
• Increased understanding of the outsourcing business: The internal organisation usually has greater business knowledge; the provider may initially lack it.
• Increased confidentiality: Sharing financial information externally may create confidentiality risks.
• Internal expertise improved: Outsourcing can reduce opportunities to develop internal finance skills.

• Vertical scaling (scale up) means increasing the size of an existing VM—for example, adding CPU or RAM.
• Vertical scaling down means reducing the VM’s size when less capacity is needed.
• Horizontal scaling (scale out) means adding more VM instances rather than making one VM larger.
• Elasticity is the broader ability to automatically adjust resources based on demand; it does not specifically mean adding CPU or memory to one VM.
• Agility refers to the ability to provision or change resources quickly.

• Customize Opportunity Contact Role

• Add the Opportunity Contact Role related list to the Opportunity page layout

• Campaign Member Role relates contacts or leads to campaigns, not opportunities.
• Campaign Member related list would expose campaign participation, not the stakeholders for the opportunity.
• Customize Campaign Role also concerns campaigns.

• 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.

• 800 devices ? a scalable, centralized solution is needed.
• Four hardware/vendor classes ? the tool must handle different drivers and images.
• Two user groups ? it should allow different configurations for each group.
• “Distribute custom images” ? an imaging/deployment tool is required, not just a file-copy utility.

• Field name and label
• Data type
• Reference table
• Default value
• Whether the field is mandatory or read-only
• Field attributes and configuration

• A: Labels and translations are handled through documentation and translation-related records.
• C: Table relationships may be represented through reference fields, but this is not the primary description of the Dictionary.
• D: Spell-checking language data is unrelated to the System Dictionary.

• 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.

1. Which host originated the infection

1. Which remaining hosts are infected

• A laptop
• Software access
• A password reset
• A mobile phone

• They run behind the scenes — applies more to automation or workflows.
• They are optional — catalog items are fundamental to a request-based catalog.
• They provide options — variables and variable options collect the requester’s choices for an item; they are not the catalog item itself.

• 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.

• Microsoft Teams: Connects to Teams-related data, but it isn’t the primary connector for the Power Apps data tables.
• Personal Analytics: Provides personal productivity insights, not application data.
• SQL Server database: Only applies if the app explicitly uses SQL Server as its data source.
• Dataflows: Used for preparing and centralizing data, not as the normal direct connection to a Power Apps app.

• Disable default accounts: Default or unused accounts may have predictable names or credentials and can be abused by attackers. They should be disabled, removed, or secured with strong credentials where necessary.
• Remove unnecessary services: Every running service can contain vulnerabilities or provide an entry point. Removing services the server does not need reduces exposure.

• Add the server to the asset inventory: Important for asset management, but it does not directly harden the system.
• Document default passwords: Default passwords should be changed or disabled—not recorded for continued use.
• Send logs to the SIEM: Supports monitoring and detection, rather than directly reducing the attack surface.
• Join the corporate domain: A deployment/configuration decision, not inherently a hardening measure.

• ARP poisoning: Redirects or intercepts local network traffic; monitoring would typically show suspicious ARP changes or man-in-the-middle behavior.
• Jamming: Interferes with wireless or radio signals. It would affect connectivity, not usually show a server-specific overload.
• Kerberoasting: Attempts to obtain and crack Kerberos service-account hashes; it does not normally cause a system outage.

• 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.

• Works across SaaS and internal applications: TOTP is widely supported by authentication systems and can be integrated into many applications.
• Device manufacturer agnostic: A hardware token or authenticator application can generate the code without depending on a specific computer or phone manufacturer.
• Offline capability: The code is generated locally using a shared secret and the current time; an internet connection or cellular service is not required.

• Username and password: May work offline but provides weaker authentication and does not meet the intended improvement in security.
• Biometrics: Can depend on device hardware, operating-system support, and enrollment mechanisms.
• SMS verification: Requires cellular connectivity and is vulnerable to threats such as SIM swapping.

• Drop violating frames
• Log or alert on the violation
• Shut down or restrict the port

• Load balancer: Distributes application traffic; it does not control switch MAC learning.
• IPS: May detect some network attacks but is not the primary control for switch MAC-table exhaustion.
• NGFW: Protects traffic crossing network boundaries, while MAC flooding occurs at the switching/LAN layer.

• Microsoft 365 groups can contain users, but generally can’t contain other groups as members.
• Security groups can contain users and, where supported, other security groups.
• Distribution groups have different nesting restrictions and aren’t equivalent to security groups.
• Dynamic groups can’t be manually populated with members; their membership is calculated from rules.
• A group’s membership type (Assigned or Dynamic) and group type determine whether it can be added to another group.

• AWS Audit Manager continuously collects evidence from AWS services and helps assess whether workloads comply with regulatory frameworks and internal policies. It can produce audit-ready reports.
• AWS Config records resource configurations and evaluates them against compliance rules. For example, it can check whether encryption, logging, or access settings meet company requirements.

• Amazon Inspector identifies software vulnerabilities and unintended network exposure, not general policy or regulatory compliance.
• Amazon CloudWatch monitors metrics, logs, and operational events, but is not primarily a compliance assessment service.
• AWS CloudTrail records API activity for auditing and investigation. It supports compliance, but does not itself provide the structured compliance assessment capabilities of Audit Manager and Config.

• A — Add a Path for Stage: A Path lets users update the Opportunity’s Stage directly from the record page, without opening the full edit form. It can also display guidance and key fields.
• B — Use a Kanban list view: Users can move Opportunities between stages by dragging records between columns, which is ideal when Stage is the only field they normally change.

• Storage accounts: storage1, storage2, and storage3
• Log Analytics workspace: Analytics3

• Azure Backup reports can send the AzureBackupReports diagnostic log to eligible storage accounts. The storage account’s subscription and region do not have to match the Recovery Services vault, so all three listed storage accounts are valid.
• The Log Analytics workspace must be in the same region as the Recovery Services vault for this configuration. Vault1 and Analytics3 are both in West Europe, making Analytics3 the valid workspace.

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

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

• Sustainability
• Performance efficiency
• Reliability

• 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.

• Primary and core nodes: Use On-Demand Instances because the workload is business-critical. These nodes manage the cluster and store/process HDFS data.
• Task nodes: Use Spot Instances in an instance fleet. Task nodes are suitable for interruption because they do not hold essential cluster data and can be replaced or diversified across instance types.
• Terminate the entire cluster after processing: The job runs only about six hours each morning, and EMRFS stores data in Amazon S3. Keeping the cluster running for the rest of the day would waste money.

• A: Using Spot for primary and core nodes risks interruption of the critical cluster.
• C: All On-Demand is reliable but unnecessarily expensive; terminating the cluster helps, but Spot task nodes provide greater savings.
• D: Leaving primary and core nodes running after the task finishes continues to incur costs. Savings Plans also are less appropriate for this intermittent workload.

• 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.

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

• 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.

• Two VMs
• Distributed across two separate availability zones

Flat organisation

• Few levels of management
• A wide span of control—managers supervise many employees
• Shorter communication channels
• More employee autonomy and quicker decisions
• Fewer formal promotion levels

Tall organisation

• Many levels of management
• A narrow span of control—managers supervise relatively few employees
• A clear hierarchy and reporting structure
• More formal supervision and communication channels
• More obvious promotion and career stages

• 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.

• C — “when the query finishes”

• D — “when the query began”

• 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.

sql 
CREATE TABLE my_table 
USING CSV 
OPTIONS (path '/path/to/csv');

sql 
CREATE TABLE my_table 
USING CSV 
LOCATION '/path/to/csv';

• USING CSV specifies the file format.
• path or LOCATION specifies where the files are stored.
• USING DELTA would be used only when the source data is in Delta format.
• FROM is used in a SELECT statement, not normally as the format declaration in CREATE TABLE.

• Residual neural network (ResNet): Primarily used for computer vision tasks such as image classification.
• Support vector machine (SVM): Commonly used for classification and regression, not natural-language query generation.
• WaveNet: Designed mainly for generating or modeling audio and speech.

• 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.

• Vulnerability scanner: Finds technical weaknesses in systems, applications, or devices. It does not usually analyze the entire supply chain.
• Penetration test: Simulates attacks against a defined target to identify exploitable weaknesses. Its scope is narrower.
• SCAP (Security Content Automation Protocol): Provides standardized formats and methods for automating security configuration and vulnerability checks, rather than mapping the full supply chain.

Why B works

• AWS KMS keys are Regional resources. A normal customer managed key in Region A cannot be used directly in Region B.
• A customer managed multi-Region KMS key (MRK) has related key replicas in both Regions. The replicas share key material and key ID, although each has a Regional ARN.
• With client-side encryption, the application encrypts the data before storing it in S3. Cross-Region replication then copies already-encrypted objects, so S3 does not need to decrypt and re-encrypt them with a different Regional key.

Why the other choices are weaker

• A and C: SSE-S3 uses Amazon-managed S3 keys, not the required customer managed KMS key.
• D: SSE-KMS can work only if the solution creates and configures the appropriate KMS key or multi-Region key replica in each Region. As written, it says to create a customer managed KMS key in each Region, which implies separate keys—not the same KMS key. Replication also requires additional KMS permissions and destination encryption configuration.

• Assignment
• Decision
• Get Records
• Loop

• Screen flow: Would include a Screen element.
• Inactive version: Inactive status does not restrict the available elements.
• Activated version: Activation status also does not determine the toolbox contents.

• Regional leads — Customer Community Plus

• Capacity planners — External Identity

• Customer Community does not provide the enhanced reporting/dashboard access required by regional leads.
• An Identity license is generally for internal Salesforce identity use and does not fit the external capacity-planning users as well as External Identity.

Simple explanation

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

• principal represents the source or initiating system.
• principal.port is the source port.
• target represents the destination system.
• target.port is the destination port.

text 
principal.port = 5555

• network.ApplicationProtocol = HTTP identifies HTTP traffic but not the backdoor specifically.
• target.port = 5555 finds traffic going to port 5555, rather than originating from it.
• network.ip_protocol = TCP is too broad because many services use TCP.

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

• The explanation states that Traffic Analytics can be enabled by a user with one of these subscription-level roles:

• Question 34 — Network Contributor: Yes
• Question 35 — Owner: Yes
• Question 36 — Reader: Yes, according to the stated explanation and documentation

• A: Person Accounts cannot be merged directly with standard Contact records.
• C: There is no Account Setup option that automatically merges Person Account duplicates.
• D: Matching rules and duplicate rules can help identify or prevent duplicates, but they do not automatically merge Person Accounts. Also, relationship considerations do not change the basic merge capability.

• 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.

• Looking up accounts, contacts, and opportunities
• Logging calls and updating Salesforce records
• Accessing previously available customer information when temporarily offline

• Salesforce Touch App: Primarily an older tablet-focused experience, not the best general solution for the sales team.
• Custom hybrid app: Unnecessary development when Salesforce provides the required capabilities natively.
• SalesforceA: Intended mainly for Salesforce administrators, not sales representatives.

• Azure Cosmos DB is a globally distributed NoSQL database service. It stores and retrieves application data, but it does not provide the tools needed to build, test, and deploy predictive analytics models.
• Azure Machine Learning—including the historical Azure Machine Learning Studio—is designed for the machine-learning lifecycle:

• Planning — identify the need, objectives, resources and feasibility.
• Analysis — determine user requirements and examine the existing system.
• Design — specify how the new system will work.
• Implementation — build, test, install and introduce the system.
• Maintenance/evaluation — monitor and improve the system after implementation.