Financial CMA Exam Prep
Certified Management Accountant (Page 6 )

• Two VMs
• Distributed across two separate availability zones

• 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.

• Amazon Kendra is a managed enterprise search service that can index content stored in S3 and support natural-language queries to find text inside documents (PDFs, Word files, etc.).

• Rekognition analyzes images/videos, not document text search.
• Polly is a text-to-speech service.
• Lex is a chatbot service.

• Create a Kendra index.
• Add a data source of type S3 and point it to your bucket (with an IAM role that allows access).
• Configure/document conversion if needed, then index the data.
• Use the Kendra API or console to run natural-language queries against your indexed documents.

• MFA verifies a user’s identity using additional authentication factors, such as a phone prompt or security token.
• It helps prevent unauthorized access even if a password is compromised.
• It does not provide secure storage or encryption of credentials used during automated deployment.

• Amazon GuardDuty: Detects suspicious activity and threats using security-related data sources; it is not primarily a software vulnerability scanner.
• Amazon Detective: Helps investigate and analyze the root cause of security findings after an event.
• Amazon Cognito: Provides user authentication and authorization for applications.

• Product Owner: May attend, but is not required unless also working as a Developer.
• Scrum Master: May attend to help facilitate or coach, but is not required.
• Developers: Must participate because the event is specifically for them.

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

• Basic: Self-help only; no technical support or design assessment.
• Standard: Technical support, but not the full proactive architectural guidance required here.
• Professional Direct: Provides proactive guidance and architecture-related assistance.
• Premier: Also supports this, but is a more expensive, enterprise-level option.

• 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.

• 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.

• Enable the owner dimension
• Allocate a standard costing inventory model

• Owner dimension (B): This dimension Lets you track who owns the stock. By enabling the owner dimension, items can be configured as either company owned or consignment (vendor-owned) when you create or edit items. Without enabling this dimension, you can’t designate ownership per item.
• Standard costing inventory model (D): Selecting a costing model determines how item costs are calculated and posted. Standard costing provides a fixed cost per unit, which is commonly used for agreed pricing scenarios like consignment arrangements for easier accounting and valuation. It helps ensure consistent cost treatment across transactions for items that can be owned by the company or on consignment.

• Batch dimension (A): Batch tracking is unrelated to ownership and isn’t required to support company-owned vs. consignment configurations.
• Moving average costing (C): This is an alternative costing method. It’s not required to enable ownership config, and the exam’s expected choice focuses on standard costing for this scenario.

• 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.

• 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.

• 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

• Source: on-premises SQL Server Database1
• Destination: Fabric Warehouse Warehouse1
• Connectivity: on-premises data gateway

• Dataflow Gen1: Primarily for Power Query transformations and isn’t the best Fabric-native choice for this copy operation.
• KQL queryset: Queries data; it does not orchestrate copying from SQL Server.
• Notebook: Could perform custom code-based movement, but it is unnecessary and less direct than a pipeline.

• Used for communication on the local link or LAN segment
• Automatically generated on IPv6-enabled interfaces
• Not routed by routers to other networks
• Commonly used by devices to communicate with their local IPv6 router
• Begins with FE80 through FEBF

• FC00::/7 — unique local unicast
• FE80::/10 — link-local unicast
• FF00::/8 — multicast
• 2000::/3 — global unicast

• Increase/decrease the number of epochs: Changes how long training runs, but does not reuse a pre-trained model.
• Unsupervised learning: Trains from unlabeled data and does not specifically address adapting an existing model.

• A is correct: Days beyond the included period incur an extra daily charge.
• D is incorrect: Daily use after 10 days is not free.
• B and C: Data-transfer pricing can depend on the direction and service terms. The exam’s intended distinction is that the included device usage period is the clearly stated no-cost benefit.

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.

• Custom domains
• 10 GB storage per web app
• Each app runs on dedicated compute
• Load balancing between instances is included
• Costs minimized

• Answer: A (Standard)

• Why:

• Note: In App Service, multiple apps in the same plan share compute resources. If you truly need isolation per app, you’d typically use separate App Service Plans, which increases cost beyond a single Standard plan.

• Correct answer: only new data added to the eventhouse (option E).
• Why: When you enable OneLake availability for the eventhouse, OneLake starts syncing data going forward. It does not automatically backfill or copy over data that already exists in the eventhouse before the enablement.
• What that means in practice: Any data added to the eventhouse after you enable OneLake will appear in OneLake (and be visible from OneLake file explorer). Pre-existing data in the eventhouse stays there unless you perform a separate backfill/copy operation outside the standard OneLake enablement.
• How to verify: add a small new dataset to the eventhouse after enabling OneLake availability, then check OneLake to confirm the new dataset appears.

• A: True. You can change the size of a Virtual Warehouse after creation (via UI or ALTER WAREHOUSE).

• B: True. A warehouse can be resized while it’s running; the resize will take effect without needing to stop queries.

• C: True. A warehouse can be configured to suspend after a period of inactivity (AUTO_SUSPEND).

• D: True. A warehouse can be configured to auto-resume when new queries are submitted (AUTO_RESUME).

• Hardware and infrastructure
• System software
• Networks and communications
• Technology platforms and services

• Business Architecture: Defines business strategy, organization, functions, and processes.
• Data Architecture: Defines the structure and management of enterprise data.
• Application Architecture: Describes application systems and how they interact to support business and data processing.

• Why Ishikawa:

• Why not the others:

• Correct answer: C) After installing ES on the search head(s) and running the distributed configuration management tool.

• ES requires the Splunk_TA_ForIndexes.spl add-on on indexers to apply index-time configurations. It should be deployed via the distributed configuration management (DCM) flow after ES is installed on the search heads, so the indexers receive the proper configuration in a controlled, versioned bundle.

• A) Deploying when adding apps to the deployment server isn’t the ES-specific order; it bypasses the ES-instantiated workflow.
• B) Installing Splunk_TA_ForIndexes.spl first isn’t the recommended order; ES needs to be installed on the search heads first.
• D) It isn’t limited to indexer cluster sites or cluster master commands; the standard flow uses DCM to push the TA to indexers in general.

• Correct answer: C. AWS CloudFormation

• Why: CloudFormation lets you define infrastructure as code via templates (JSON or YAML). You can create a single template that describes multiple AWS resources and reuse it to deploy consistent stacks across environments. Templates can be parameterized and stored for repeated deployments. Other options (Marketplace, AMI, OpsWorks) don’t provide reusable deployment templates in the same way.

• 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.

• Correct answer: All four statements are true (A, B, C, and D). The given key (A,B) is likely incorrect.

• A) Customers can change the size of the Warehouse after creation — Yes. You can resize a virtual warehouse after it’s created using ALTER WAREHOUSE ... SET WAREHOUSE_SIZE.
• B) A Warehouse can be resized while running — Yes. Snowflake supports online resizing; you can change the size without stopping queries.
• C) A Warehouse can be configured to suspend after a period of inactivity — Yes. You can enable auto-suspend with a delay (AUTO_SUSPEND).
• D) A Warehouse can be configured to auto-resume when new queries are submitted — Yes. You can enable auto-resume (AUTO_RESUME) so a suspended warehouse automatically resumes on new queries.

• Example commands:

• Even if a warehouse is resizing or auto-suspending, queries will be queued and then executed once the warehouse has the appropriate capacity.

• B — AWS DataSync: Transfers data between storage systems, such as S3, file systems, and on-premises storage. It is not a marketplace or catalog for third-party datasets.
• C — Kinesis Data Streams and CodeCommit: CodeCommit is a source-code repository, not a third-party data provider. Kinesis is for streaming data ingestion.
• D — Kinesis Data Streams and ECR: ECR stores container images, not datasets. Kinesis does not provide access to ECR data as an external dataset source.

• Correct choices: A and D.

• Why not B, C, or E?

• 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.

• I can’t view the images, so I can’t tell which table is labeled as A in your screenshot. But here’s how to decide:

• How to identify the fact table:

• How to identify the surrogate key in the Patient table:

• Relationship:

• S3 Lifecycle rules automate actions such as transitioning objects to different storage classes or deleting old objects.
• S3 bucket policies control access permissions; they do not preserve earlier object versions.
• S3 server-side encryption protects data confidentiality by encrypting objects at rest, but it does not prevent deletion or overwriting.

• Accidental deletion or overwriting ? S3 Versioning
• Unauthorized access ? bucket policies and IAM
• Data encryption ? server-side encryption

• The correct AAA mapping (per Cisco objectives) is:

• Why the given options aren’t fully correct:

• Quick takeaway: when you configure AAA, you should conceptually map them as:

• Example commands (to reinforce concepts):

• Wiping securely overwrites the drive so the original data cannot reasonably be recovered. It is generally less expensive than physically destroying the device.
• Recycling could expose the data if the drive is not securely erased first.
• Shredding physically destroys the drive and is effective, but usually more costly and prevents reuse.
• Deletion only removes file references; it is not a secure sanitization method.

• 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.

• 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.

• Correct answer: S3 Versioning

• Why the other options aren’t suitable for this protection:

• Quick tip: For enhanced protection, enable Versioning (and consider related features like Object Lock for write-once scenarios in specific compliance cases).

• Why: If an application on EC2 needs to call other AWS services, using an IAM role (attached to the EC2 instance as an instance profile) provides temporary, automatically rotated credentials. This avoids embedding access keys in the application.
• How it works: Create a role with the minimum required permissions, attach it to the EC2 instance, and let the AWS SDK used by the application retrieve credentials from the instance metadata service. The credentials rotate automatically and are scoped to the policy you define.
• Why not other options:

• Correct answer: A
• What this is saying: You need to write a Transact-SQL query that uses REGEXP_SUBSTR to extract the ID from MessageText, and you should apply STRING_ESCAPE(MessageText, 'json') before calling REGEXP_SUBSTR.

• MessageText may contain JSON characters (quotes, backslashes, etc.). Escaping the JSON content first ensures the string you pass to the regex is safe and won’t confuse the regex engine.
• The pattern you apply with REGEXP_SUBSTR would then extract the first substring that matches your ID pattern from the (escaped) text.

• Example (conceptual):

• The question implies REGEXP_SUBSTR is available in this environment; some SQL Server and Fabric contexts don’t expose it natively in all versions. If REGEXP_SUBSTR isn’t available, you’d need an alternative approach (e.g., using built-in regex-like capabilities or CLR/UDFs).
• If you need the ID specifically from the first paragraph, you might first isolate the first paragraph and then apply REGEXP_SUBSTR, or compose a single pattern that anchors to the first paragraph.

• Drops packets when traffic exceeds a certain bitrate: This describes traffic policing, not shaping.
• Fragments large packets and queues them: Shaping does not fragment packets as its primary congestion-control action.
• Drops packets randomly from lower-priority queues: Packet dropping may occur if a shaping queue becomes full, but it is not the defining behavior.

• Shaping: buffers and delays excess traffic.
• Policing: drops or marks traffic that exceeds the configured rate.

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1. Remote access to a Windows PC
2. Full chat and optional game-console functions

• Windows Remote Desktop (RDP) uses TCP 3389. The router needs a port-forwarding rule that sends incoming traffic on that port to the Windows PC’s internal IP address.
• The game console should connect through the wireless AP. Using WPA2-PSK provides the required wireless security while allowing normal online, chat, and optional services.
• The firewall should separate the internal network from the screened subnet. Its screened-subnet-side address is shown as 10.100.0.1.
• Devices must be placed in the correct network locations: the PC behind the router, the console on the wireless AP, and the firewall between the appropriate network segments.

• Why: Crisis management relies on established, repeatable procedures for responding to an incident (activation of the crisis team, escalation paths, communications, containment actions). This ensures a coordinated, timely, and auditable response.

• Why not the others:

• 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.

• Key difference: DirectQuery leaves data in the on-prem SQL Server and queries it live. That means every visual request can trigger online processing on the source, which can be slower and adds load on the on-prem system. In contrast, Import loads data into the Power BI data model, so visuals render from the in-memory engine (faster).

• Why that helps with the requirements:

• Why not A or B: Both rely on live data via DirectQuery, which contradicts the goal to minimize online processing and visuals performance.

• Why not D: It uses Import, but refreshing hourly adds unnecessary processing and complexity when daily refresh already satisfies currency needs.

• 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.

• Answer: B — Improve employee training and awareness

• Why this is correct:

• Why the other options are less effective here:

• Quick practical note:

• A. Implement retries with exponential backoff

• C. Reduce the frequency and/or size of requests

• B. Use PutRecord instead of PutRecords — PutRecord sends one record per call and does not remove the underlying throughput limitation. It may increase request overhead.
• D. Use Amazon SNS instead — SNS is not a direct fix for Kinesis shard throttling and changes the required streaming architecture.
• E. Reduce KCL consumers — KCL consumers read from Kinesis; they do not solve producer-side PutRecords throttling.