Test Prep ACT Test Exam Prep
American College Testing: English, Math, Reading, Science, Writing (Page 4 )

• Shared capacity

• Fabric capacity — F SKUs

• Fabric trial capacity

• Existing Power BI Premium — P SKUs

• A — Tables
• B — Named file formats
• C — Schemas
• E — Databases

Why these are correct

• Tables: Can be cloned using CREATE TABLE ... CLONE. The clone initially uses zero-copy cloning, so storage is shared until changes are made.
• Named file formats: Can be cloned as database objects, preserving the file-format definition.
• Schemas: A schema and its eligible objects can be cloned.
• Databases: A database and its eligible schemas and objects can be cloned.

Why the others are incorrect

• Shares: A share is an account-level data-sharing object, not a normal cloneable database object.
• Users: Users are security principals and cannot be cloned with CLONE.

• Run the backup with WITH CHECKSUM
• Store the backup on an SMB network share

sql 
BACKUP DATABASE DB1 
TO DISK = '\\FileServer\SqlBackups\DB1_full.bak' 
WITH CHECKSUM;

• DMS does not create the SQL Server backups for you.
• You must provide a valid full database backup.
• You must continue taking transaction log backups while the source database remains online.
• The full backup and subsequent log backups must be available in the SMB share that DMS can access.
• WITH CHECKSUM enables backup checksum validation, helping detect backup corruption.

• Lower order numbers appear first.
• For example, a variable with order 100 appears before one with order 200.
• The Sequence field is not the control used for catalog variable display order.
• The Default Value sets a value, not placement.
• The Choice field defines selectable options, not the variable’s position.

• Namespace: The namespace associated with the code where the checkpoint was set.
• Time: When the checkpoint was captured or executed.

• Exception: Exceptions are viewed through debug logs or execution results, not as the primary Checkpoints tab information.
• Debug Statement: System.debug() output belongs in the Logs tab. A checkpoint captures program state, such as variables and their values, at a specific point in execution.

• Deterrent control: The signs warning that people may be filmed can discourage unauthorized or malicious activity. They do not directly stop the action; they influence behavior.
• Detective control: CCTV records or monitors activity so security personnel can identify events or investigate them afterward.

• Preventive: Stops an incident from occurring, such as access control.
• Corrective: Restores systems after an incident.
• Directive: Instructs people to behave in a certain way, such as a security policy.
• Compensating: An alternative control used when the preferred control is not feasible.

• QuickVisualize is used to create and render a Power BI report from a DataFrame.
• The typical pattern is:

python 
PBI_visualize = QuickVisualize( 
    get_dataset_config(df), 
    auth=device_auth 
) 


PBI_visualize

• get_dataset_config(df) prepares the dataset configuration.
• auth=device_auth supplies authentication for the Power BI connection.
• Evaluating PBI_visualize renders the report in the notebook.

• Box 1: No
• Box 2: Yes
• Box 3: Yes

• A — Capacity: The system must handle all current records and anticipated future records. A system that cannot cope with volume will quickly become ineffective.
• C — Accuracy: Academic records are critical, so the new system must be at least as accurate as the existing system and comparable systems. Poor accuracy could cause serious administrative and reputational problems.
• D — Integration: Linking with the university’s financial systems supports consistency and avoids duplicate data entry, especially for registration, deregistration and fee-related transactions.

• B — Parallel running: This is a useful implementation and risk-control technique, but it is not an essential feature of the system itself. It may also be expensive and time-consuming.
• E — Internet access for all information: This creates significant confidentiality and security risks. External access might be needed for selected services, but unrestricted access to all information is not essential and would be inappropriate for student records.

• Standardize which services users can deploy
• Apply governance and access controls
• Manage approved product versions
• Give users self-service access to authorized resources

• AWS Control Tower: Sets up and governs a multi-account AWS environment.
• AWS Cloud Map: Provides service discovery for applications.
• AWS Clean Rooms: Enables privacy-preserving collaboration on data analysis.

• A: CEO-sponsored formal policy — demonstrates executive support, but sponsorship at one point in time may not sustain commitment.
• B: Security awareness training — primarily improves employee behavior, not senior management commitment.
• C: Periodic alignment reviews — ongoing reviews show that security remains relevant, supports business priorities, and uses resources appropriately.
• D: Senior management signoff on the strategy — useful for governance and accountability, but signoff is generally a one-time event.

python 
result = poller.result()

• poller represents the ongoing invoice-analysis operation.
• poller.result() waits until processing finishes.
• It then returns the structured analysis output, such as extracted invoice fields, tables, or other content.

1. Create a temporary Onboarding OU.
2. Move the new account into it.
3. Move the restrictive SCPs from the organization root to the Production OU.
4. Allow the account to update AWS Config.
5. Move the account into Production after onboarding.

• An SCP attached at the organization root applies to every account and OU beneath it.
• An SCP attached to the Production OU applies only to accounts in that OU.
• Therefore, moving the restrictive SCP from the root to Production temporarily exempts the onboarding account without weakening the policies for existing production accounts.
• Once onboarding is complete, moving the account into Production subjects it to the normal restrictions.

• Redesign how work is performed
• Deliver services faster and more flexibly
• Scale resources as demand changes
• Improve customer experiences
• Support innovation and new business models

• A: Cloud transformation applies to organizations of all sizes, not only large enterprises.
• C: It affects the entire organization, including business operations, customer service, and strategy—not just IT.
• D: Cloud adoption often requires significant process and cultural change, rather than simply continuing business as usual with lower costs.

• Azure Machine Learning Studio is designed to build, test, train, and deploy machine-learning models, including predictive analytics.
• Azure Cosmos DB is a globally distributed NoSQL database. It can store data used by an AI solution, but it is not the primary service for developing and deploying predictive models.
• Therefore, the appropriate recommendation is Azure Machine Learning Studio, as shown in Question 15.

• The users currently have Office 365 Enterprise E3 licenses assigned directly.
• Assigning Microsoft 365 Enterprise E5 through a group does not automatically remove their directly assigned E3 licenses.
• From the Licenses blade, you can select the E3 product and remove it from all assigned users in one operation. This requires less effort than editing 2,500 users individually.

• Identity Governance manages access reviews, entitlement management, and related governance—not bulk license removal.
• Set-AzureAdUser does not remove product licenses.
• Set-WindowsProductKey applies Windows product keys and is unrelated to Microsoft 365 licensing.

• Reporting relationships
• Organizational structures
• Leadership styles
• Team maturity
• Individual and group behavior
• Communication and motivation

• Acquire Project Team: Focuses on obtaining the people needed for the project.
• Develop Project Team: Focuses on improving team skills, relationships, and performance.
• Manage Project Team: Focuses on tracking performance, resolving issues, and managing changes within the team.

• Recovery Services vault — stores Site Recovery configuration and recovery metadata.
• Hyper-V site — represents the on-premises Hyper-V environment.
• Azure virtual network — the target network where the replicated VM will run after failover. Since Azure VMs already use the same virtual network, that VNet can be selected as the target.
• Storage account or managed-disk target, depending on the ASR configuration and portal version.
• Provider/agent on the Hyper-V server — enables replication from Hyper-V to Azure.

• A. IDS attack signatures: An IDS primarily detects suspicious network activity; it is not the best tool for scanning uploaded files.
• C. Load balancer: Improves availability and distributes traffic but does not inspect files for malware.
• D. WAF: Protects web applications against attacks such as SQL injection and command injection. It may inspect HTTP requests, but malware scanning of uploaded PDFs is the key requirement here.

• Lead investigator: Coordinates the investigation and directs the response.
• Information security representative: Provides security expertise and helps assess the incident.
• Technical representative: Preserves system evidence, takes forensic backups, and supports technical analysis.
• Legal representative: Advises on legal, regulatory, privacy, and evidence-handling requirements.

• Accept: Acknowledging the risk and choosing not to take additional action.
• Transfer: Shifting the risk or financial consequences to another party, such as an insurer.
• Mitigate: Reducing the likelihood or impact through controls, such as patching or access restrictions.
• Avoid: Eliminating the activity that creates the risk.

• Form layout
• Related lists
• Dictionary settings
• UI policies
• Client scripts
• Views and field visibility

• Personalization usually affects only the individual user.
• System configuration can affect other users, depending on its scope and conditions.

bash 
OTEL_SERVICE_NAME=foundry-agent

bash 
OTEL_SERVICE_NAME=langchain-service

python 
import os 


os.environ["OTEL_SERVICE_NAME"] = "langchain-service" 


from azure.ai.openai... # import your tracing components 
from azure.monitor.opentelemetry import configure_azure_monitor 


configure_azure_monitor( 
    connection_string=os.environ["APPLICATIONINSIGHTS_CONNECTION_STRING"] 
)

• Agent application: OTEL_SERVICE_NAME=foundry-agent
• LangChain application: OTEL_SERVICE_NAME=langchain-service

• SQL injection: Manipulates database queries through application input.
• XML external entities (XXE): Abuses XML parsers to access files, internal systems, or other resources.
• Cross-Site Request Forgery (CSRF): Tricks an already authenticated user’s browser into sending an unwanted request. It generally does not steal session cookies.

• Storage usage of files stored in Microsoft Teams: SharePoint site usage report

• Number of active users per team: Microsoft Teams usage report

1. SharePoint site usage report
2. Microsoft Teams usage report

1. Open File Explorer.
2. Go to View ? Show ? File name extensions

1. Disable Hide extensions for known file types.
2. Rename the complete filename from Document.txt to Document.xml.
3. Confirm the extension-change warning.

• Virtual introductions: Team members share their role, experience, location, and working preferences.
• Online icebreakers: Short, informal activities such as “two truths and a lie.”
• Virtual coffee chats: Pair team members for informal, non-project conversations.
• Collaborative problem-solving: The team works together on an online puzzle or scenario.
• Retrospectives: The team discusses what went well, what did not, and how to improve.
• Working-agreement sessions: The team agrees on response times, meeting etiquette, communication channels, and handoffs.
• Recognition sessions: Members acknowledge one another’s contributions.
• Remote workshops: Teams jointly create plans, diagrams, or schedules using collaboration tools.

• Existing Eventhouse data: remains available only in the KQL database.
• Data ingested after enabling the feature: is copied to OneLake and can be accessed through OneLake file explorer.
• New databases: are irrelevant; the setting applies to the selected KQL database.

• Complex inputs: Queueable jobs can accept objects such as Map<Id, Project__c> and List<Account> through the class constructor.
• Long-running callouts: Implement Database.AllowsCallouts in the Queueable class.
• Confirmation/status: System.enqueueJob() returns an AsyncApexJob ID, which can be used to query job status and determine whether execution completed successfully.

apex 
public class ProjectQueueable 
    implements Queueable, Database.AllowsCallouts { 


    private Map<Id, Project__c> projects; 
    private List<Account> accounts; 


    public ProjectQueueable( 
        Map<Id, Project__c> projects, 
        List<Account> accounts 
    ) { 
        this.projects = projects; 
        this.accounts = accounts; 
    } 


    public void execute(QueueableContext context) { 
        // Perform the callout 
    } 
}

• @future(callout=true) supports callouts, but future methods accept only primitive values or collections of primitives—not complex sObjects or maps of sObjects.
• Database.AllowsCallouts
 Hyderabad, India