IIA IIA-CRMA Exam Actual Questions
Certification in Risk Management Assurance (CRMA) Exam (Page 14 )

• Correct answer: Power BI dataset

• The scenario says the data model already contains several measures and you want to create a report from the existing data with minimal development. Reusing a published Power BI dataset lets you inherit the existing measures and data model, so you don’t have to recreate them.
• How to do it: In Power BI Desktop, use the connector Power BI datasets (Get Data > Power BI datasets) and connect to the existing dataset, then build visuals using the pre-defined measures.
• Why the other options are less suitable:

• 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.

Why

cmd 
PowerShell.exe -ExecutionPolicy Bypass -File C:\Scripts\ConfigureVM.ps1

Why the other options are less suitable

• GPO logon script: Runs only when a user logs on and may not run during initial VM provisioning.
• GPO startup script: Can work, but requires the VM to be joined to the domain and the policy to be applied. It is also normally evaluated at each startup.
• Place scripts in a VHD: Merely placing scripts on a disk does not cause them to execute.

• Correct answer: B) Context window.

• Why: The context window is the number of tokens the foundation model can process in a single inference. It sets the maximum length of the combined input (prompt) and the model’s output. A larger context window allows more content to be included in one prompt.

• How to use: Check the FM’s context window value and ensure your prompt length plus the desired completion stays within that limit. If needed, summarize or split input across multiple prompts.

• Why the other options aren’t correct:

• Quick tip: Verify the specific FM’s context window for Bedrock, since different models have different token limits.

• In the source query: apply UPPER() or LOWER() to the column.
• In Power Query Editor: use Text.Upper or Text.Lower on the column, then load.

• This fixes the root cause when comparisons/joins depend on case.
• In DirectQuery, transformations are pushed to the source or query layer; ensure the transformation is supported by your data source/connector.
• After normalization, verify relationships and any downstream visuals that rely on that column.

• Active vs passive: Active assessment involves actively scanning targets by sending probes/packets to identify hosts, services, and vulnerabilities. Passive assessment observes traffic without probing.
• External vs internal: External assessment is about testing from outside the network perimeter; the scenario doesn’t specify external vantage, only that tools are identifying hosts/services across the enterprise network.

• The missing piece is to configure an event source mapping between the DynamoDB stream and the Lambda function. Enabling DynamoDB Streams alone doesn’t trigger the function—you must wire the stream to Lambda so events invoke the function.
• Note that changing StreamViewType (A) only affects what data is delivered (e.g., NEW_IMAGE) and does not trigger invocations. Options C and D are not required for invocation: you don’t need SNS, and increasing the timeout won’t enable the trigger.

• RPO (Recovery Point Objective) — maximum acceptable data loss, measured in time. It specifies how far back in time you can tolerate data loss. Example: RPO of 2 hours means backups must occur at least every 2 hours.

• ARO (Annualized Rate of Occurrence) — expected frequency of a threat occurring per year. It estimates how often a risk is likely to happen on average (used in risk calculations).

• MTTR (Mean Time To Recover) — average time to recover/restore service after an incident. It includes detection, repair, and restoration time, and helps gauge downtime and alignment with RTO.

• Control plane: Managed by Databricks and contains the Databricks web application, workspace services, cluster management, and job orchestration.
• Data plane: Runs in your cloud account and contains compute resources such as:

• Worker node: Data plane compute.
• Driver node: Data plane compute.
• JDBC data source: Usually an external data system.
• Databricks Filesystem (DBFS): Provides storage access and is backed by cloud object storage rather than being entirely part of the control plane.

• App Tag: a label that reflects the app’s enterprise readiness based on its Cloud Confidence Index (CCI) rating. It lets you quickly group apps (e.g., Poor, Average, Good) for policy decisions.
• App Score: a numeric value representing the CCI score. It provides a precise threshold you can use to enforce policies (e.g., block apps with Score below 50).

• You can create policies that block or restrict apps with a Poor App Tag or with an App Score under a chosen threshold.
• These two aspects let you filter cloud apps by CCI ratings during policy evaluation.

• CCL isn’t described as a real-time policy facet in this scenario.
• GDPR Readiness is a separate consideration and not the two CCI aspects used for real-time protection policy in this context.

• The problem: Guest users can’t create posts in the Monthly Reports channel.
• The recommended fix (answer B): Modify the Guest access settings in the Teams admin center.

• Guest access settings control what guests are allowed to do across Teams (for example, posting, chat, and channel participation). If guests are restricted from posting, enabling the appropriate guest permissions will let them post in channels like Monthly Reports.
• The other options don’t directly change guest permissions in the way that affects posting:

• Correct answer: B — A reservation for the server based on the MAC address.

• Why this is the best choice:

• Why the other options are less suitable:

• Quick takeaway: Use a DHCP reservation to give the file server a fixed IP while still benefiting from centralized DHCP management.

• 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.

• Correct answer: D – Do not enable default administrative accounts to ensure accountability.

• A – Do not use encryption methods … backups and sensitive information: Encryption helps protect data; not using it increases risk, not reduces insider threats.
• B – Do not allow administrators to use unique accounts during installation: We actually want unique admin accounts, not the opposite.
• C – Do not control the access to administrators and privileged users: Failing to control access directly enables misuse.

• 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.

• Answer: S3 Inventory report.

• Why: The S3 Inventory report provides a scheduled listing of objects within a bucket, including metadata about each object. When you configure it to include object tagging, you can see tags for each object, and the object keys (which reflect prefixes) and bucket scope are captured in the report. This makes it suitable for auditing and tracking “tags, buckets, and prefixes” across S3 objects.

• What the other options do (not suitable for this purpose):

• Tip: If you need tags in the report, enable the inventory option to include object tagging in the configuration.

• The answer: Question 51: C — Request trigger.

• To invoke a Logic App from an external service (here, the Azure Application Insights availability test) you need a trigger that starts on an incoming HTTP request. In Logic Apps, this is the trigger that exposes an HTTP endpoint — typically shown as "When a HTTP request is received" and referred to as the Request trigger.
• The other options aren’t appropriate:

• Create a Logic App with the Request trigger to generate a URL.
• Configure Application Insights to post the degraded-availability payload to that URL.
• Add actions (e.g., send email, follow-up) in the Logic App to notify the customer services team.

• Problème: le système d’alertes signale des fluctuations tout en manquant les activités qui restent anormalement constantes sur une période longue. Il faut donc un scénario qui capte les anomalies qui se maintiennent dans le temps plutôt que les pics ponctuels.
• Peer: permet de comparer un client à ses pairs; utile pour repérer des écarts relatifs, mais ne cible pas nécessairement les motifs d’anomalie persistante sur plusieurs périodes.
• Revenus mapping: relie les transactions à des sources ou flux de revenus; utile pour l’analyse des fonds, mais pas directement pour détecter une anomalie longue durée.
• Below-the-line: conçu pour détecter des activités qui passent en dessous des seuils habituels ou qui demeurent anormales sur une longue période, comblant ainsi la faiblesse des alertes à long terme.

1. Ingestion Lambda receives requests from API Gateway and places messages in an SQS queue.
2. Processing Lambda is triggered by the queue and loads records into Aurora PostgreSQL.

• Decoupling: API request handling is separated from database loading.
• Buffering: SQS absorbs bursts when incoming traffic exceeds the database’s processing capacity.
• Controlled concurrency: Configure the SQS-triggered Lambda’s concurrency and batch size to avoid overwhelming Aurora or exhausting database connections.
• Automatic retries: Messages that fail processing can return to the queue and be retried. A dead-letter queue can capture persistent failures.
• Lower operational effort: The solution remains serverless and avoids managing EC2 servers or Kubernetes clusters.

• A: EC2 and Tomcat add server-management overhead.
• B: DynamoDB/DAX would require changing the database model and does not solve the Aurora ingestion design.
• C: SNS is useful for notifications and fanout, but SQS is better for durable buffering and backpressure in this producer-consumer workflow.

• Answer: C – netstat -an

• netstat -an lists all active connections and listening ports with numeric addresses, without resolving names. This lets you spot DoS patterns such as a flood of connections to a specific port or many connections from a single or few IPs.
• The other options don’t help as directly:

• Windows: netstat -an and look for numerous ESTABLISHED connections to a service or many SYNs to a port.
• Filter by port, e.g., netstat -an | findstr :80, or on Linux: ss -tunap | grep ':80'.

• Netstat provides a snapshot. DoS detection often benefits from continuous monitoring, flow data, and IDS/IPS logs.

• Correct answer: A) Hashing

• Why: Hashing produces a fixed-size digest of the software. If the final build is altered in any way, the hash will change, enabling you to detect tampering by comparing the stored digest with a freshly computed one.

• Why not the others:

• a) True — To add a field to the form layout, drag the field from the Fields tab to the desired destination on the form. This adds to the form view only, without changing the table definition.
• b) True — To create a new field on the form’s table, drag a data type from the Field Types tab to the form and configure it. This creates a new column on the table and adds the field to the form view.
• c) True — To remove a field from the form layout, hover to enable the action buttons and select Delete. This removes the field from the form view but does not remove it from the table definition.
• d) False — You cannot add a section by dragging from the Field Types tab. Sections are added via the Add Section option (toolbar or right-click menu), not from the Field Types tab.

• Answer: Data enhancement.

• Why: Augmenting gold-layer tables with an additional dataset is enriching or enhancing the existing data to support the ad-hoc analysis. The other options don’t capture the idea of adding external data to improve the dataset (ad-hoc improvements = tweaks, last-mile dashboarding = building dashboards, last-mile ETL = ETL steps at the end of the pipeline). In practice, this is often also called data enrichment.

• administrators — Full access to switch configuration and REST API functions; excessive for this requirement.
• sysadmin — Intended for highly privileged system administration, not basic monitoring.
• helpdesk — More limited and focused on troubleshooting/support functions; it does not match the stated default role and level-1 requirement as directly.

• Side loading means installing software from sources outside official or trusted repositories.
• This process can bring in malicious payloads because the installed software hasn’t been vetted. A rootkit is a type of malware that hides its presence and maintains privileged access, making it a prime risk when using untrusted sources.
• Why not the other options:

• Only install apps from trusted sources; verify signatures.
• Use application whitelisting and security controls to block sideloading.
• Keep systems updated and use anti-malware tools capable of detecting rootkits.

• Answer: D: Making business cases for improvement action

• Continual Improvement focuses on identifying and planning improvements and ensuring they’re funded and prioritized. Creating a business case for an improvement action is part of justifying and obtaining support/resources to implement improvements.
• A (Identifying the cause of incidents) aligns with Problem Management.
• B (Authorizing changes) aligns with Change Enablement.
• C (Logging/managing incidents that result in improvement opportunities) aligns with Incident Management, not Continual Improvement.

• Answer: D. Select an IdP

• Why: To reduce the number of credentials across multiple SaaS apps, implement a single sign-on approach via an Identity Provider. The first step is choosing the IdP; once selected, you can enable SAML (A) or OAuth as supported by apps. Password vaulting (C) is not a true SSO solution, and B is not the foundational step.

• According to the provided answer key, the four options are: Upload File, User Criteria, HR Profiles, HR Criteria (options B, D, F, G).

• Upload File: Filter by a file you upload (e.g., CSV) that provides data for bulk case creation.
• User Criteria: Filter by criteria related to users (e.g., role, department) to select target users.
• HR Profiles: Filter by HR profile data associated with users.
• HR Criteria: Filter by HR-related criteria or attributes.

• 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.

kusto 
Event | where EventType == "error"

• == is the KQL equality operator.
• -eq is a PowerShell operator, not KQL.
• is is not the correct equality operator in this context.

text 
Event | where EventType –eq "error"

• Event | search "error" — valid, broad search.
• search in (Event) "error" — valid, broad search.
• Event | where EventType == "error" — valid, targeted filter.

• The correct answer: C. Tokenization

• Why:

• Why the others are weaker:

• Correct answer: A. Email templates

• Snippets are reusable content blocks that you insert into email content, and they require an email template (or at least an email draft) to render.
• You can store region-specific footers as snippets and include them in a template, but there would be nothing to render the snippet into without a template.
• The other options aren’t prerequisites for using snippets:

• This is a lookup relationship. Salesforce does not cascade access from a child (Opportunity) to its parent (Account) via implicit sharing.
• To view the Account, the user must have explicit access to the Account (via its OWD/sharing, or object permissions).

• The user has Read/View (or higher) on Account via profile/permission set.
• Manual sharing or a sharing rule grants that Account to the user.
• The Account is exposed by a broader permission like View All/Modify All on Account.
• Role hierarchy with Grant Access Using Hierarchies could grant access to Accounts owned by others, if applicable.

• The mapping and resolution of endpoint identities (EIDs) to their location (RLOCs) in an SD-Access fabric is handled by the control plane using the LISP protocol.
• Why not the others:

• In Spark, an executor is a JVM that can have multiple cores. Each task can consume some CPUs (spark.task.cpus).
• The executor’s resources are effectively partitioned into slots, where each slot can run one task. The number of slots per executor is roughly spark.executor.cores / spark.task.cpus.
• Therefore, multiple tasks can run in parallel within the same executor (via these slots). So the statement “Tasks run in parallel via slots” is correct.

• A: A slot is not another name for an executor; a slot is a unit inside an executor.
• B: There’s no requirement that there must be fewer executors than tasks; tasks can be scheduled over time across the available slots.
• C: An executor can run more than one core; it’s not limited to a single core.
• D: There isn’t a rule that there must be more slots than tasks; tasks can wait if slots aren’t available, and you can have equal or even fewer slots than concurrent tasks.