CompTIA 220-1002 Exam Actual Questions
(Retired and replaced with 220-1201) (Page 7 )

• 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:

• Event | search "error"
• Event | where EventType == "error"
• search in (Event) "error"

• Dynamics 365 Remote Assist — used for remote collaboration and mixed-reality scenarios.
• Dynamics 365 Finance — supports financial and operational management.
• Dynamics 365 Business Central — designed primarily for small and medium-sized businesses’ finance and operations.
• Dynamics 365 for Phones — provides mobile access to Dynamics 365 apps, including Sales, through the mobile Unified Interface.

• 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.

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• Prompts and Suggestions: Retained for 28 days
• User Engagement Data: Kept for Two Years

• Why this is correct: In Azure Virtual Desktop, user access to a host pool is controlled through App Groups. The default app group for a host pool publishes the full desktop, so adding members to that app group grants them sign-in and access to the desktop (and any RemoteApps in that group). This is the standard way to give users access to AVD resources.

• Why the other options are not correct:

• Practical steps (high level):

• Answer: Internal load balancers (ILB) — option C.

• An ILB has a frontend IP address that must be a private IP within the subnet’s address space. You pick this IP when you create the ILB, and it can be Static or Dynamic.
• Other options don’t require a per-subnet IP:

• Le rôle n’a pas de clés propres. Des identifiants temporaires (via STS) sont émis lorsque quelqu’un ou quelque chose « assume » le rôle.
• La trust policy déclare qui peut assumer le rôle (par ex. une instance EC2, un utilisateur IAM, ou un service comme Lambda).
• Une fois attaché à une ressource (par exemple comme un instance profile sur une EC2), l’application peut appeler les services AWS avec les permissions du rôle.

• Respect du principe du moindre privilège: on accorde uniquement ce qui est nécessaire.
• Pas de stockages de clés sur les instances; les credentials se renouvellent automatiquement.

• Rôles pour EC2, rôles pour Lambda, accès cross-compte, etc.

• Who performed the action
• What action occurred
• When it occurred
• Where it originated
• Whether it succeeded or failed

• Investigating suspicious activity: Important, but investigation depends on having adequate audit data first.
• Storage allocation: Necessary for retention, but storage does not help if the records lack meaningful details.
• Actions after audit failure: Part of operational planning, not the primary assessment of the application’s audit capability.

• 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 target API uses HTTPS, so Mule must validate the server’s TLS certificate.
• The TLS configuration is set to None, meaning no custom truststore is configured.
• Mule therefore uses the JRE’s default truststore to determine whether the target certificate is trusted.
• If the issuing CA certificate is in that truststore, the TLS handshake can succeed.
• If it is absent—or the certificate is otherwise invalid—the request fails with a TLS/handshake error.

• The correct option is B: AWS Storage Gateway.

• Why: The scenario requires backing up on-prem data to AWS without changing existing backup workflows. AWS Storage Gateway provides a hybrid storage solution; specifically, the Tape Gateway emulates a physical tape library, allowing your existing backup software to write to virtual tapes that are stored in AWS (in S3 or S3 Glacier). This lets you back up 10 TB to the cloud while preserving current backup workflows and on-prem infrastructure.

• How it would work: Deploy a gateway appliance or VM on-site, connect your tape-based backup software to the virtual tape library, and start writing to virtual tapes. The data is then archived in AWS, freeing up local storage.

• Why the others aren’t suitable:

• Quick tip: If you weren’t using tape, File Gateway could be another option for file-based backups; Tape Gateway is the right pick for tape-based workflows.

• The first step in risk management is to understand objectives, constraints, and drivers from those who care about the project. This stakeholder engagement helps identify what could go wrong and what risks are most critical.
• Only after you’ve gathered input from stakeholders should you identify risks and document them in the risk register. Updating the risk register (option C) is important, but it comes after identifying and analyzing risks.
• Options B (ensure resources) and D (revise the risk management plan) are actions that may follow once risks are identified and understood; they’re not the initial step.

• 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.

• State is stored remotely in Terraform Cloud/Enterprise, not as a local file.
• Terraform runs (plan/apply) can be executed on remote infrastructure, with results visible in the remote workspace UI.
• Supports workspace-based organization, state locking, and concurrency control.
• Useful for team collaboration, centralized governance, and auditable logs.

• In your configuration, you use a backend block like backend "remote" { ... }.
• You still run terraform init to configure/migrate to the remote backend.
• After setup, terraform plan/terraform apply may be executed remotely, and the outputs/logs appear in the Terraform Cloud/Enterprise UI rather than (only) in your local terminal.

• Other backends store state remotely but typically do not provide remote execution; with the remote backend you get remote runs and a collaborative UI, not just remote state storage.

• The correct setting to configure is the Enrollment Status Page (ESP) profile.
• Why: ESP tracks the enrollment progress and logs during Autopilot provisioning. You can enable log collection within the ESP policy so that, if ESP times out, the user can collect and share the logs with support.
• Optional enhancement: In the ESP policy (or the Autopilot diagnostics settings), you can enable:

• Automatic enrollment settings: control how devices auto-enroll, not log collection.
• Windows Autopilot deployment profile: controls deployment steps but not ESP log collection.
• Device configuration profile: applies settings but doesn’t provide ESP log collection mechanics.

• The two correct options are:

• The two incorrect options:

• Correct answer: C: Amazon Comprehend.

• Why: The library wants to classify books based on their text content. This is an NLP (natural language processing) task. Amazon Comprehend is AWS’s managed NLP service that can perform content classification (including creating custom classifiers) and extract meaningful information from text. The other services are not focused on text classification:

• Quick note: In practice, you’d store the books in S3, extract text if needed (e.g., from PDFs with Textract), and then use Comprehend to classify the documents into topics or genres.

• D. Provide public endpoints to store and retrieve data

• E. Manage the infrastructure layer and the operating system

• Classifying data
• Configuring access permissions, such as IAM policies
• Selecting or configuring available encryption options, depending on the requirement

• 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.

• 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

• 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. Configure prompt modifications to enforce tone, disclaimers, and refusal behavior at the system level.

• D. Configure Power Platform DLP policies to restrict unauthorized data connectors.

• B: Manual topic-by-topic disclaimer edits are specifically discouraged.
• C: Channel settings do not replace agent-level Responsible AI controls.
• E: Publishing before enabling safety filters violates the stated deployment sequence. Responsible AI filters should be enabled before publication, not afterward.

• What the scenario asks: You have a Power BI semantic model that pulls from multiple sources (Azure SQL Database and SharePoint Online), must support a single dataset for three reports, keep data current (daily refresh by 7 AM PT), and apply RLS to limit sales data by region. You need to choose a storage mode for the tables.

• Correct choice: Dual storage mode.

• Why Dual fits:

• Key concepts:

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.

• 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.

• 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.

• Topic: Conditional Access (CA) policy and MFA for Azure management.
• Policy name: Policy1, created with the template “Require multifactor authentication for Azure management.”
• What the template does: It enforces MFA when signing in to manage Azure resources (Azure management) for the users included in the policy.
• Who is included: The question lists Admin1, Admin2, Admin3, and Admin4 as the admins in the tenant. The template’s default scope for this scenario is to apply to those admin accounts (i.e., all four admins unless you explicitly limit the scope).

• CA policy for “Azure management” targets admin sign-ins.
• If the policy includes Admin1–Admin4, all of them must use MFA on their next sign-in (choice D).

• Step 1: From Power BI Desktop, select Get Data, choose Folder, enter the folder path, and click OK, then choose Transform data to open Power Query Editor.

• Step 2: In Power Query Editor, expand the Attributes column.

• Step 3: From the Power Query Editor, select the Content column and use Home > Combine Files (aka “Combine binaries”) to consolidate the files.

• The requirement: the support plan must allow opening new support requests (technical support incidents).
• Azure’s Basic plan does not include technical support incidents—only billing/subscription support and access to community support.
• Therefore, you must choose a paid plan to open new technical support requests: Developer, Standard, Professional Direct, or Premier.

• What the goal is: You want to add guest (external) users to your Azure AD tenant contoso.com, one entry per external user in a CSV.

• The proposed solution uses New-AzureADUser for each external user. Why this isn’t correct: New-AzureADUser creates a regular (internal) user in your directory. It does not create a guest/B2B user invite. So you’d end up with 500 ordinary accounts, not guest accounts with external access.

• The correct approach: Use New-AzureADMSInvitation for each external user. This invites the external user to your directory and creates a guest user (a B2B collaboration user) in your tenant. The invited user then accepts the invitation and gains access as a guest.

• Azure AD vs directory/tenant: Azure AD is the cloud identity service. A directory (also called a tenant) is your specific instance of that service (contoso.com in your scenario). The terms are often used interchangeably in exams.
• Guest user vs internal user: A guest user is external to your organization; an internal user is created directly in your directory as a normal employee/user account.
• B2B invitation: The process of inviting external users so they can collaborate in your resources; New-AzureADMSInvitation is designed for this.

• Answer: No (B)

• SaaS (Software as a Service) delivers applications over the internet; you don’t manage the underlying infrastructure or OS.
• Deploying Azure virtual machines requires provisioning and managing virtual machines, OS, updates, and networking—this is classic IaaS (Infrastructure as a Service).
• PaaS is for managed runtime environments (apps hosted on a platform), not for VM deployment.

• A) configure matching hold and delay timers

• B) configure matching key-strings

• C) configure matching priority values

• D) configure unique virtual IP addresses

• 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.

• On-Demand: You pay by the hour with no long-term commitment. This is ideal for workloads that are infrequent or have highly variable usage. Since this job runs only 24 hours once per year, you pay only for those 24 hours, with no wasted upfront or long-term payments.
• Reserved Instances: Require a 1- or 3-year commitment and pay for capacity whether you use it or not. For a workload that runs just 24 hours a year, you’d be paying for most of the term unused, making it far less cost-efficient.
• Spot Instances: Can be interrupted whenever AWS needs capacity, which is unacceptable for an uninterruptible workload.
• Dedicated Instances: Generally more expensive and aimed at licensing or compliance requirements; not needed for this use case.

• 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:

• 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.

• 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.

• 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.

• Ethical red-teaming is adversarial testing aimed at uncovering weaknesses and potential exploits in an AI system before deployment.
• A (improving accuracy) is not the primary?? of red-teaming.
• B (simulate model risk scenarios) is related but narrower; red-teaming centers on finding vulnerabilities and risk exposure, not just simulating risks.
• D (ensure compliance) is not the main goal of red-teaming.

• The 99.99% availability SLA for VMs is achieved when you run VMs across two or more Availability Zones.
• Two VMs in a single Availability Zone do not meet the 99.99% target (their SLA is lower, e.g., around 99.95% or less depending on configuration).

• Deploy at least two VMs across two different Availability Zones (one VM in each zone, or both in two zones with a load balancer).
• This provides the required zone redundancy and the 99.99% SLA.

• B — Increase provisioned concurrency for Lambda

• D — Refactor the Lambda functions

• E — Use Amazon RDS Proxy

• A. Custom and standard objects have standard fields. True. Both object types include standard fields (for example, CreatedDate, LastModifiedDate, Owner). Custom objects also have the Name field, which is a standard field on all objects.
• B. Standard objects are included with Salesforce. True. Standard objects (like Account, Contact, etc.) come with Salesforce out of the box.
• C. A new standard object can be created. False. You can create custom objects, but you cannot create new standard objects.
• D. Only standard objects support master-detail relationships. False. Master-detail relationships can be used with both standard and custom objects.

• '15' is a string. With + and a string, JavaScript does string concatenation: '15' + 10 -> '1510'.
• The result '1510' is then used in a multiplication: '1510' 2. The operator triggers numeric conversion, so '1510' becomes the number 1510.
• 1510 * 2 = 3020.

• If the code were let x = (15 + 10) * 2, the result would be 50 since 15 + 10 is numeric addition.

python 
import azure.cognitiveservices.speech as speechsdk 


speech_config = speechsdk.SpeechConfig( 
    subscription="YOUR_KEY", 
    region="YOUR_REGION" 
)

Important Azure Speech SDK classes

• SpeechConfig

• AudioConfig

python 
  audio_config = speechsdk.audio.AudioConfig( 
      use_default_microphone=True 
  )

• SpeechRecognizer

python 
  recognizer = speechsdk.SpeechRecognizer( 
      speech_config=speech_config, 
      audio_config=audio_config 
  )

• SpeechSynthesizer

• AudioOutputConfig

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