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Question 21
A Power Platform developer needs to create a custom connector that authenticates using OAuth 2.0. Which authentication flow should be configured in the custom connector settings for a web application?
A) Basic authentication
B) API Key authentication
C) OAuth 2.0 with Authorization Code flow
D) Anonymous authentication
Answer: C
Explanation:
OAuth 2.0 with Authorization Code flow is the appropriate authentication method for web applications in custom connectors. This flow provides secure authentication by redirecting users to the authorization server, where they authenticate and grant permissions. The authorization server returns an authorization code that the application exchanges for an access token. This flow is most secure for web applications because the client secret remains on the server side and tokens can be refreshed without user intervention. Custom connectors support this flow natively through configuration settings.
Option A is incorrect because Basic authentication transmits credentials (username and password) with each request, typically encoded in Base64. While simpler to implement, Basic authentication is less secure than OAuth 2.0 and doesn’t provide token-based access control, refresh capabilities, or granular permission scoping. Basic authentication is appropriate for simple scenarios but not recommended when OAuth 2.0 is available and required by the API.
Option B is incorrect because API Key authentication uses a static key passed in headers or query parameters for authentication. API keys don’t expire automatically, can’t be scoped to specific permissions easily, and don’t support user-level authentication. While API keys are simpler than OAuth, they’re less secure and don’t provide the delegation and authorization capabilities that OAuth 2.0 offers for web applications accessing user data.
Option D is incorrect because anonymous authentication allows access without any credentials or authentication mechanism. This is only appropriate for completely public APIs that require no access control. Anonymous authentication provides no security and cannot identify users or control access to protected resources, making it unsuitable for most real-world scenarios requiring authentication.
Question 22
A developer is creating a canvas app that needs to display data from multiple SharePoint lists across different sites. What is the most efficient approach to access this data?
A) Create separate SharePoint connections for each list
B) Use Microsoft Dataverse as an intermediary data layer
C) Use Power Automate flows to copy data to a single location
D) Manually export and import data into the app
Answer: B
Explanation:
Using Microsoft Dataverse as an intermediary data layer is the most efficient approach for accessing data from multiple SharePoint lists across different sites. Dataverse provides a unified data platform with robust querying capabilities, relationships, business logic, and security. Data can be synchronized from SharePoint to Dataverse using Power Automate or built-in integration features, creating a consolidated view. Canvas apps can then connect to Dataverse with optimized delegation, filtering, and performance. This architecture provides better scalability, offline capabilities, and data integration compared to direct SharePoint connections.
Option A is incorrect because creating separate SharePoint connections for each list creates complexity, performance issues, and delegation limitations. Canvas apps have connector throttling limits and each SharePoint connection consumes resources. Multiple connections complicate data relationships and filtering across lists. Direct SharePoint connections also face delegation limitations that restrict the number of records that can be processed, making this approach inefficient for large datasets or complex scenarios.
Option C is incorrect because using Power Automate flows solely to copy data to a single location introduces latency, synchronization overhead, and potential data consistency issues. While flows can consolidate data, they add complexity in scheduling, error handling, and maintaining data freshness. This approach creates duplicate data storage and requires continuous flow execution, consuming flow runs and creating maintenance burden. More direct integration methods are preferable when available.
Option D is incorrect because manually exporting and importing data is completely impractical for production applications requiring current data. Manual processes don’t scale, can’t refresh data automatically, and require constant human intervention. This approach produces stale data, is error-prone, and defeats the purpose of building connected applications. Modern Power Platform solutions require automated, real-time data access, not manual data transfer.
Question 23
A Power Platform solution requires executing complex business logic that exceeds the capabilities of Power Automate. Which approach should a developer use to extend functionality?
A) Create Azure Functions and call them from Power Automate
B) Write all logic in canvas app formulas only
C) Use only built-in Power Automate actions repeatedly
D) Avoid complex logic entirely
Answer: A
Explanation:
Creating Azure Functions and calling them from Power Automate is the recommended approach for complex business logic that exceeds Power Automate capabilities. Azure Functions provide full programming language capabilities (C#, Python, JavaScript, etc.) for implementing sophisticated algorithms, integrations, or processing that would be impractical in Power Automate. Functions can be triggered via HTTP requests from Power Automate using the HTTP action or custom connectors. This hybrid approach leverages Power Automate for workflow orchestration while using Azure Functions for computational complexity, providing best-of-both-worlds architecture.
Option B is incorrect because writing all complex logic in canvas app formulas creates performance issues, maintainability problems, and limited debugging capabilities. Canvas app formulas execute client-side with limitations on execution time, complexity, and available functions. Complex business logic in formulas makes apps slow, difficult to test, and hard to maintain. Business logic should typically reside in backend services or flows rather than client-side app formulas for better architecture.
Option C is incorrect because repeatedly using only built-in Power Automate actions for complex logic creates overly complicated, unmaintainable flows. While Power Automate offers many actions, some scenarios require capabilities beyond what connectors provide—like advanced mathematical computations, specialized algorithms, or complex data transformations. Trying to force complex logic into Power Automate alone results in convoluted flows that are difficult to debug and maintain.
Option D is incorrect because avoiding complex logic entirely when business requirements demand it is not a viable solution. Business processes often require sophisticated logic for calculations, validations, integrations, or decision-making. The goal is implementing complex logic using appropriate tools and architectures, not eliminating necessary functionality. Power Platform’s extensibility through Azure Functions and custom APIs specifically addresses scenarios requiring capabilities beyond standard connectors.
Question 24
A developer needs to implement field-level security in a Dataverse table to restrict access to sensitive salary information. What is the correct approach?
A) Use column-level security (field security profiles)
B) Create separate tables for each user group
C) Use JavaScript to hide columns in forms
D) Rely only on table-level security roles
Answer: A
Explanation:
Using column-level security through field security profiles is the correct approach for restricting access to sensitive columns like salary information in Dataverse. Field security profiles allow administrators to control read and update permissions for specific columns independent of table-level security. Users without appropriate field security profile membership cannot view or modify secured columns regardless of their table permissions. This provides granular security control for sensitive data while maintaining normal access to other table columns.
Option B is incorrect because creating separate tables for each user group introduces massive data redundancy, complexity, and maintenance overhead. This approach requires duplicating table structures, relationships, and business logic across multiple tables. Synchronizing data between tables becomes error-prone, and reporting across tables becomes difficult. Field-level security provides the needed granularity without architectural complexity, making separate tables an anti-pattern for this requirement.
Option C is incorrect because using JavaScript to hide columns in forms provides only cosmetic security, not actual data protection. Hidden columns can still be accessed through API calls, Power Automate, integrations, or by modifying JavaScript. Client-side security is never sufficient for protecting sensitive data because it can be bypassed. True security must be enforced server-side through Dataverse security mechanisms like field security profiles.
Option D is incorrect because relying only on table-level security roles provides all-or-nothing access to table data without column-level granularity. If users need access to some columns in a table but not others, table-level security alone cannot provide this distinction. Users granted table read permissions can view all columns unless field-level security is applied. Salary information requires more granular protection than table-level security provides.
Question 25
A canvas app needs to work offline and synchronize data when connectivity is restored. Which data source provides native offline capability?
A) SharePoint lists directly connected
B) Dataverse with offline profile configuration
C) Excel files in OneDrive
D) SQL Server direct connection
Answer: B
Explanation:
Dataverse with offline profile configuration provides native offline capability for canvas apps through the Power Apps mobile app. Offline profiles define which tables and records synchronize to mobile devices, allowing users to view and edit data without connectivity. Changes made offline are automatically synchronized to Dataverse when connectivity is restored, with conflict resolution mechanisms handling simultaneous edits. This built-in offline capability makes Dataverse the preferred data source for mobile scenarios requiring offline access.
Option A is incorrect because SharePoint lists directly connected to canvas apps do not provide offline capability. SharePoint connections require active internet connectivity to retrieve and update data. When offline, apps cannot access SharePoint data, and users cannot continue working. SharePoint lacks the synchronization infrastructure and conflict resolution necessary for offline scenarios, making it unsuitable for offline requirements without additional architecture.
Option C is incorrect because Excel files in OneDrive also require connectivity to access data and don’t provide built-in offline synchronization for canvas apps. While OneDrive has some offline file access for Office applications, this doesn’t extend to canvas apps querying Excel as a data source. Excel connections in canvas apps require online access to read and write data, and don’t offer the structured offline sync capabilities that Dataverse provides.
Option D is incorrect because SQL Server direct connections require network connectivity and don’t provide offline capability. Canvas apps connecting to SQL Server need active connections to execute queries and updates. SQL Server has no built-in mobile offline synchronization mechanism for canvas apps. While SQL Server can be part of offline solutions through intermediary layers, direct SQL connections don’t support offline scenarios.
Question 26
A developer needs to call a custom API that requires a bearer token for authentication from a canvas app. What is the correct approach to securely handle the token?
A) Store the token in a global variable in the app
B) Create a custom connector with OAuth 2.0 authentication
C) Hard-code the token in the formula
D) Store the token in a collection
Answer: B
Explanation:
Creating a custom connector with OAuth 2.0 authentication is the secure approach for handling bearer tokens when calling custom APIs from canvas apps. Custom connectors manage authentication flows automatically, securely storing and refreshing tokens without exposing them in app formulas or variables. The connector handles token acquisition, renewal, and secure transmission to the API. This approach follows security best practices by keeping credentials out of the app layer and leveraging Power Platform’s built-in authentication infrastructure.
Option A is incorrect because storing bearer tokens in global variables exposes them to anyone who can export or inspect the app. Global variables are not encrypted and can be viewed by users with appropriate permissions. Storing security credentials in client-side variables violates security best practices and creates vulnerabilities. Tokens should be managed by secure backend services or connector infrastructure, not exposed in app variables.
Option C is incorrect because hard-coding tokens in formulas is extremely insecure and creates significant security vulnerabilities. Hard-coded tokens are visible to anyone who can edit or export the app, cannot be easily rotated when compromised, and may be inadvertently shared when apps are copied or shared. Hard-coded credentials violate fundamental security principles and can lead to unauthorized API access if tokens are exposed.
Option D is incorrect because storing tokens in collections has the same security vulnerabilities as global variables. Collections are client-side data structures that can be inspected and are not designed for secure credential storage. Like variables, collection data is not encrypted and can be accessed by users viewing the app. Security tokens require secure server-side management, not client-side storage in app collections.
Question 27
A Power Automate cloud flow needs to process 50,000 records from a Dataverse table. What is the most efficient pattern to avoid timeout and performance issues?
A) Use a single Apply to each loop processing all records
B) Implement batch processing with multiple child flows
C) Process all records in parallel branches
D) Use Do until loop without pagination
Answer: B
Explanation:
Implementing batch processing with multiple child flows is the most efficient pattern for processing large volumes of records in Power Automate. This approach divides the 50,000 records into manageable batches (e.g., 100-500 records per batch) and processes each batch in a separate child flow instance. Parent flow orchestrates batch creation and child flow invocation, often with controlled parallelism. This pattern avoids timeout limits, distributes processing load, provides better error handling per batch, and enables parallel processing while staying within Power Automate limits.
Option A is incorrect because using a single Apply to each loop processing all 50,000 records will exceed Power Automate timeout limits (typically 30 days for cloud flows, but practically much shorter for continuous execution). The flow will likely time out or encounter performance degradation. Apply to each loops have iteration limits and processing 50,000 records sequentially creates extremely long-running flows prone to failure. This approach doesn’t scale for high-volume processing.
Option C is incorrect because processing all records in parallel branches hits platform limits for concurrent actions and creates resource contention. Power Automate limits the number of concurrent actions and parallel branches in a single flow. Attempting to process 50,000 records in parallel would either fail due to limits or overwhelm Dataverse with simultaneous requests, triggering API throttling. Parallel processing must be controlled and batched, not unlimited.
Option D is incorrect because Do until loops without proper pagination and batch handling suffer the same timeout and performance issues as Apply to each loops. Do until loops executing sequentially through 50,000 records take excessive time and risk timeout. Without batching and child flows, Do until loops cannot efficiently process large datasets. Additionally, improper pagination can cause infinite loops or missing records.
Question 28
A developer needs to create a PCF (PowerApps Component Framework) control that displays real-time stock prices. Which method should be implemented to receive updated values from the parent form?
A) constructor method only
B) updateView method
C) init method only
D) destroy method
Answer: B
Explanation:
The updateView method should be implemented to receive updated values from the parent form in PCF controls. Power Platform calls updateView whenever bound properties change, passing a context object containing updated property values. This method is where the control should respond to data changes by updating its visual representation. For real-time stock prices, updateView receives new price values and refreshes the display accordingly. This method is essential for any PCF control that needs to react to data changes from the hosting application.
Option A is incorrect because the constructor method initializes the control class but doesn’t receive property updates from the parent form. The constructor runs once when the control instance is created and doesn’t have access to context or property values. While the constructor is necessary for class initialization, it cannot handle ongoing data updates that occur during the control’s lifetime. Data updates require the updateView method.
Option C is incorrect because the init method runs once during control initialization to set up the control, but it doesn’t receive ongoing property updates. Init receives the initial context and establishes event handlers and resources, but subsequent property changes don’t trigger init again. For controls displaying dynamic data like real-time stock prices, init alone is insufficient—updateView is required to handle continuous data updates.
Option D is incorrect because the destroy method is called when the control is being removed and is used for cleanup operations like removing event handlers and disposing resources. Destroy doesn’t receive property updates and runs at the end of the control lifecycle. It’s the opposite of what’s needed for receiving updated values—destroy handles teardown, not data updates.
Question 29
A model-driven app requires custom business logic to execute when a record is saved, regardless of how the save occurs (form, API, or import). Where should this logic be implemented?
A) JavaScript on the form OnSave event
B) Dataverse plug-in registered on the Update message
C) Power Automate cloud flow triggered by record modification
D) Canvas app formula
Answer: B
Explanation:
A Dataverse plug-in registered on the Update message is the correct location for business logic that must execute on every record save regardless of the save method. Plug-ins execute server-side as part of the Dataverse event pipeline and trigger consistently whether records are saved through forms, API calls, imports, integrations, or any other mechanism. Plug-ins can execute in pre-validation, pre-operation, or post-operation stages, providing control over execution timing and the ability to modify data or block operations based on business rules.
Option A is incorrect because JavaScript on the form OnSave event only executes when users save records through that specific form in the browser. JavaScript doesn’t run when records are updated via API calls, imports, Power Automate, integrations, or other forms. Client-side JavaScript cannot enforce business rules consistently across all save pathways. Server-side enforcement through plug-ins is required for universal business logic execution.
Option C is incorrect because Power Automate cloud flows trigger asynchronously after the save operation completes and may experience delays or failures. Flows cannot prevent invalid saves because they execute after the transaction commits. Flows also may not trigger for all save scenarios depending on configuration and have limitations in modifying the same record within the transaction context. For synchronous, guaranteed execution on all saves, plug-ins are required.
Option D is incorrect because canvas apps are completely separate applications and cannot enforce business logic on model-driven app forms or API operations. Canvas app formulas execute only within that specific canvas app and have no control over how records are saved in model-driven apps, through APIs, or via other mechanisms. Universal business logic requires server-side implementation, not client-side canvas app logic.
Question 30
A developer needs to create relationships between tables in a solution. The requirement states that when a parent record is deleted, all related child records should also be deleted. What type of relationship behavior should be configured?
A) Referential, Remove Link
B) Referential, Restrict Delete
C) Parental (Cascade All)
D) Custom with no cascading
Answer: C
Explanation:
Parental (Cascade All) relationship behavior should be configured to automatically delete child records when the parent record is deleted. This relationship type cascades delete operations from parent to child records, maintaining referential integrity by preventing orphaned child records. Cascade All also cascades other operations like assign, share, and unshare. This behavior is appropriate when child records have no independent existence and should be removed with their parent, ensuring data consistency.
Option A is incorrect because Referential, Remove Link behavior only removes the relationship reference when the parent is deleted but doesn’t delete the child records themselves. Child records remain in the system with their lookup field cleared, creating orphaned records. This behavior is appropriate when child records should continue existing independently after parent deletion, but the requirement specifically states child records should be deleted with the parent.
Option B is incorrect because Referential, Restrict Delete prevents parent record deletion when related child records exist. This behavior protects against accidental deletion by requiring users to manually delete or reassign child records before deleting the parent. While this ensures data safety, it contradicts the requirement for automatic child deletion. Restrict Delete is appropriate when child records must be preserved or explicitly handled.
Option D is incorrect because Custom with no cascading doesn’t provide automatic deletion behavior. Custom relationships allow granular control over specific cascade settings, but without cascading delete configured, child records won’t be automatically deleted when the parent is removed. The requirement explicitly needs automatic child deletion, which requires cascade delete behavior, making Custom without cascading inappropriate.
Question 31
A canvas app needs to display a filtered list of contacts based on the current user’s security role. What is the most efficient way to implement this?
A) Filter the data source in the gallery using formulas
B) Create a view in Dataverse with security filtering
C) Use Power Automate to filter and return data
D) Load all records and hide items with Visible property
Answer: B
Explanation:
Creating a view in Dataverse with security filtering is the most efficient approach because filtering happens server-side before data is transmitted to the app. Dataverse views support delegation, allowing efficient queries against large datasets while respecting user security context automatically. Views can include complex filtering logic based on user security roles through FetchXML or view filters. This approach minimizes data transfer, improves performance, and leverages Dataverse’s built-in security model rather than implementing security logic in the app layer.
Option A is incorrect because filtering data sources in gallery formulas may work for small datasets but doesn’t scale well and can hit delegation limitations. If the filtering formula is non-delegable, Power Apps only processes the first 500 or 2000 records (depending on delegation settings), potentially missing relevant records. Additionally, implementing security logic in app formulas is error-prone and creates maintenance challenges when security requirements change.
Option C is incorrect because using Power Automate to filter and return data introduces unnecessary latency and complexity. Flows execute asynchronously, adding response time compared to direct Dataverse queries. Flows also consume run quota and require additional error handling. While flows can be useful for complex orchestration, simple data filtering is more efficiently handled by Dataverse views with built-in delegation and security.
Option D is incorrect because loading all records and using the Visible property to hide items creates terrible performance and security issues. This approach transfers all records to the client, wasting bandwidth and exposing data that should be hidden. Hidden items can potentially be accessed through app inspection or export. True security requires server-side filtering, not client-side visibility toggling.
Question 32
A Power Platform solution needs to integrate with an external REST API that returns paginated results with a continuation token. How should a custom connector handle this pagination pattern?
A) Configure policy template for pagination in the custom connector
B) Manually call the API multiple times in Power Automate
C) Ignore pagination and accept incomplete results
D) Use only the first page of results
Answer: A
Explanation:
Configuring a policy template for pagination in the custom connector enables automatic handling of paginated results. Custom connectors support pagination policies that automatically follow continuation tokens or next page links, aggregating results across multiple API calls into a single response. This approach abstracts pagination complexity from flow authors, allowing actions to return complete datasets automatically. The connector definition includes pagination configuration specifying how to extract continuation tokens and construct subsequent requests.
Option B is incorrect because manually calling the API multiple times in Power Automate creates complex, error-prone flows with loops to manage continuation tokens. This approach requires flow authors to understand pagination logic, implement loop conditions, aggregate results, and handle errors for each page. Manual pagination increases flow complexity, creates maintenance burden, and is prone to infinite loops or missed data if not implemented perfectly.
Option C is incorrect because ignoring pagination and accepting incomplete results produces incorrect, unreliable solutions. When APIs return paginated results, the first page contains only a subset of total records. Ignoring pagination means missing most data, leading to incorrect business decisions and processing. Complete data retrieval requires following pagination through all available pages until no continuation token exists.
Option D is incorrect because using only the first page of results has the same problems as ignoring pagination entirely. The first page represents an arbitrary subset of available data, often just 10-100 records. Solutions requiring complete datasets cannot function correctly with partial data. Proper pagination handling is essential when APIs return paginated responses to ensure all relevant data is retrieved and processed.
Question 33
A developer needs to debug a plug-in that is registered in Dataverse. Which tool provides the best debugging experience for plug-in code?
A) Browser developer tools
B) Plug-in Registration Tool with profiling
C) Power Automate flow checker
D) Canvas app monitor
Answer: B
Explanation:
The Plug-in Registration Tool with profiling provides the best debugging experience for Dataverse plug-ins. The profiler captures plug-in execution context, including input parameters, execution time, exceptions, and entity images. Developers can replay captured profiles in Visual Studio, attaching a debugger to step through plug-in code locally while simulating the exact server-side execution context. This enables setting breakpoints, inspecting variables, and analyzing execution flow without deploying code to production, significantly improving debugging efficiency.
Option A is incorrect because browser developer tools are designed for debugging client-side JavaScript, HTML, and CSS, not server-side C# plug-in code executing in Dataverse. Plug-ins run on Microsoft servers as compiled .NET assemblies, completely outside the browser context. Browser tools cannot access, inspect, or debug server-side plug-in execution. Different debugging tools are required for server-side .NET code.
Option C is incorrect because Power Automate flow checker analyzes flow definitions for configuration issues, errors, and best practice violations, but has no capability to debug Dataverse plug-ins. Flows and plug-ins are different technologies serving different purposes. While flows can trigger plug-ins indirectly through data operations, flow checker doesn’t provide any insight into plug-in code execution, variables, or logic.
Option D is incorrect because Canvas app monitor tracks app performance, formula execution, and data calls within canvas apps, not server-side plug-in execution. App monitor shows client-side operations and API calls made by the app but cannot debug server-side .NET code running in Dataverse. Plug-in debugging requires server-side tools like the Plug-in Registration Tool, not client-side app monitoring.
Question 34
A solution includes multiple canvas apps that share common formulas and logic. What is the best approach to promote code reuse and maintainability?
A) Copy and paste formulas into each app
B) Create component libraries and reference them in apps
C) Write formulas in Word documents for reference
D) Recreate formulas manually in each app
Answer: B
Explanation:
Creating component libraries and referencing them in apps is the best approach for promoting code reuse and maintainability across multiple canvas apps. Component libraries are reusable containers for canvas components with their formulas, properties, and logic. Apps can import components from libraries, ensuring consistent behavior and appearance. When library components are updated, all consuming apps can be updated to use the new version. This centralized approach reduces duplication, improves consistency, and simplifies maintenance compared to copying code.
Option A is incorrect because copying and pasting formulas into each app creates maintenance nightmares. When logic needs updating, every app requires manual modification, increasing the risk of inconsistencies, errors, and missed updates. Duplicated code is difficult to maintain, test, and enhance. Copy-paste approaches violate the DRY (Don’t Repeat Yourself) principle and are considered anti-patterns in software development.
Option C is incorrect because writing formulas in Word documents for reference doesn’t provide actual code reuse—developers still manually implement formulas in each app. This approach creates documentation overhead without solving the reuse problem. Documentation can become outdated quickly and doesn’t ensure consistent implementation across apps. Word documents cannot enforce correct implementation or provide any automation benefits.
Option D is incorrect because manually recreating formulas in each app suffers the same problems as copy-paste approaches. Manual recreation is time-consuming, error-prone, and creates inconsistencies when implementations differ slightly across apps. Changes require modifying every app individually. Modern software development emphasizes reusable components and libraries rather than manual duplication of logic.
Question 35
A model-driven app form needs to display or hide a tab based on the value of an option set field. What is the correct way to implement this requirement?
A) Use form business rules only
B) Use JavaScript on form load and field change events
C) Modify the form XML directly
D) Create multiple forms for different scenarios
Answer: B
Explanation:
Using JavaScript on form load and field change events is the correct approach for dynamically showing or hiding tabs based on option set values. JavaScript provides programmatic access to form elements through the formContext API, allowing developers to get field values and manipulate tab visibility. Event handlers registered on field change events enable real-time tab visibility updates as users change option set values. Form load handles initial tab state based on existing values. This approach provides flexibility and responsiveness required for dynamic form behavior.
Option A is incorrect because form business rules cannot show or hide tabs—they can only control field visibility, requirement levels, default values, and locking. Business rules operate at the field level and don’t have access to tab-level form elements. While business rules are useful for simpler scenarios, they cannot implement tab visibility requirements. JavaScript is required for manipulating structural form elements like tabs and sections beyond simple field-level operations.
Option C is incorrect because directly modifying form XML is not supported for implementing dynamic behavior and creates maintenance problems. Form XML defines static form structure at design time, not runtime behavior. Changes to XML require republishing customizations and don’t provide dynamic response to user actions. Direct XML editing bypasses normal customization interfaces, making forms difficult to maintain and potentially breaking with platform updates.
Option D is incorrect because creating multiple forms for different scenarios creates unnecessary complexity and maintenance overhead. Users would need manual form switching or complex routing logic to see appropriate forms. Multiple forms duplicate structure, fields, and logic, making updates difficult. Dynamic form behavior through JavaScript provides better user experience and simpler maintenance than managing multiple static form variations.
Question 36
A Power Platform solution requires encrypting sensitive data stored in Dataverse. Which approach provides encryption at rest for specific columns?
A) Enable Dataverse column encryption for specific columns
B) Use JavaScript to encrypt values on the client
C) Store encrypted values in text fields manually
D) Enable TLS for all connections
Answer: A
Explanation:
Enabling Dataverse column encryption for specific columns provides built-in encryption at rest for sensitive data. Column encryption uses customer-managed keys stored in Azure Key Vault to encrypt data transparently at the database level. Encrypted columns appear as normal text to authorized users but are stored encrypted on disk. This approach provides compliance with data protection requirements without modifying application code. Column encryption integrates with Dataverse security, ensuring only users with appropriate permissions can access decrypted values.
Option B is incorrect because using JavaScript to encrypt values on the client provides no real security and creates numerous problems. Client-side encryption keys must be accessible to the JavaScript code, meaning they’re exposed to users who can inspect code. Encrypted values stored as strings can’t be queried or filtered effectively by Dataverse. Client-side encryption doesn’t protect data in transit to the server or at rest in the database from privileged users or breaches.
Option C is incorrect because manually storing encrypted values in text fields requires custom encryption/decryption logic in all application layers, creates query limitations, and doesn’t integrate with Dataverse security. Custom encryption implementations are error-prone, may use weak algorithms, and create maintenance burden. Encrypted text fields can’t participate in Dataverse features like rollup fields, calculated fields, or effective filtering. Platform-provided column encryption is superior to custom implementations.
Option D is incorrect because TLS encrypts data in transit between clients and servers but doesn’t provide encryption at rest in the database. TLS protects against network eavesdropping but once data reaches the server, it’s stored unencrypted unless column encryption is enabled. Both transport encryption (TLS) and at-rest encryption (column encryption) serve different purposes and are often used together for comprehensive data protection.
Question 37
A canvas app needs to display data from a SQL Server database. The database contains over 100,000 records. What is the recommended approach to ensure good performance?
A) Connect directly to SQL Server with delegation-compatible queries
B) Use Power Automate to copy all records to collections
C) Export data to Excel and connect to the Excel file
D) Load all records into a collection on app start
Answer: A
Explanation:
Connecting directly to SQL Server with delegation-compatible queries is the recommended approach for large datasets. SQL Server connector supports delegation, allowing filtering, sorting, and searching to execute on the database server rather than retrieving all records to the client. Delegable queries can process millions of records efficiently because the database performs the work. Developers should use delegable functions and avoid non-delegable operations to maintain performance. This approach minimizes data transfer and leverages database query optimization.
Option B is incorrect because using Power Automate to copy records to collections is inefficient and hits multiple limitations. Collections are client-side data structures with practical size limits (typically recommended under 500 records). Copying 100,000 records through flows consumes significant flow runs, takes considerable time, and creates stale data snapshots. This approach introduces latency, complexity, and doesn’t scale for large datasets that need frequent updates.
Option C is incorrect because exporting data to Excel and connecting to Excel files creates static data that doesn’t reflect real-time database changes. Excel connections have poor performance with large datasets and limited delegation capability. This approach requires manual or automated export processes, creates duplicate data storage, and doesn’t support dynamic filtering on large datasets. Excel is unsuitable as an intermediary for operational database access.
Option D is incorrect because loading all 100,000 records into a collection on app start creates terrible performance with long app loading times, excessive memory usage, and potential app crashes. Collections have size limitations and loading large datasets to the client wastes bandwidth and resources. This approach defeats the purpose of server-side data processing and creates poor user experience with slow, unresponsive apps.
Question 38
A developer needs to implement version control and ALM (Application Lifecycle Management) for a Power Platform solution. What is the recommended approach?
A) Manually export and import solutions between environments
B) Use Azure DevOps with solution management and pipelines
C) Copy components between environments using copy-paste
D) Recreate solutions manually in each environment
Answer: B
Explanation:
Using Azure DevOps with solution management and pipelines is the recommended approach for Power Platform ALM and version control. Azure DevOps provides source control for solution files, automated build and deployment pipelines, work item tracking, and collaboration features. Power Platform Build Tools enable automated solution export, packing, and deployment through Azure Pipelines. This approach implements proper DevOps practices including version history, code reviews, automated testing, and controlled deployments across development, test, and production environments.
Option A is incorrect because manually exporting and importing solutions is error-prone, time-consuming, and doesn’t provide version control or audit trails. Manual processes lack automation, don’t track changes over time, and cannot easily roll back to previous versions. Manual ALM doesn’t scale for teams or complex solutions and increases risk of errors during deployment. Modern ALM requires automated processes with source control integration.
Option C is incorrect because copying components between environments using copy-paste is not a real ALM approach and creates inconsistencies and errors. Many Power Platform components cannot be copy-pasted, and this approach doesn’t maintain dependencies, solutions, or proper packaging. Copy-paste completely lacks version control, deployment automation, and change tracking. This represents ad-hoc development without proper lifecycle management.
Option D is incorrect because manually recreating solutions in each environment is extremely inefficient, error-prone, and creates configuration drift between environments. Manual recreation doesn’t guarantee consistency, wastes development time, and makes tracking changes impossible. This approach violates ALM principles requiring identical artifacts deployed across environments. Proper solution packaging and automated deployment ensure consistency and traceability that manual recreation cannot provide.
Question 39
A Power Automate cloud flow needs to handle errors gracefully and retry failed operations automatically. What is the best approach to implement error handling?
A) Use Configure run after settings and Scope actions for error handling
B) Ignore errors and let the flow fail
C) Manually rerun the flow after each failure
D) Delete actions that might fail
Answer: A
Explanation:
Using Configure run after settings and Scope actions for error handling is the best approach for graceful error handling in Power Automate. Scope actions group related operations, allowing catch blocks through run after configuration set to “has failed” or “has timed out.” This creates try-catch patterns where error handling actions execute only when operations fail. Actions can include notifications, logging to tables, retry logic, or compensating transactions. Built-in retry policies on individual actions provide automatic retry for transient failures. This comprehensive approach creates robust, production-ready flows.
Option B is incorrect because ignoring errors and letting flows fail creates unreliable automation that doesn’t handle exceptions gracefully. Failed flows may leave processes incomplete, data inconsistent, or users uninformed about issues. Production flows must anticipate and handle expected errors, provide meaningful notifications, and implement retry logic for transient failures. Flows without error handling are fragile and unsuitable for critical business processes.
Option C is incorrect because manually rerunning flows after failures defeats the purpose of automation and doesn’t scale. Manual intervention requires monitoring flows constantly, responding to failures promptly, and understanding context for reruns. This approach creates operational burden and can’t handle high-volume scenarios. Automated error handling and retry logic should minimize manual intervention, making flows self-healing when possible.
Option D is incorrect because deleting actions that might fail eliminates necessary functionality rather than handling errors appropriately. All external integrations, API calls, and data operations can potentially fail due to transient issues, network problems, or service unavailability. Removing functionality to avoid errors is not a solution. Proper error handling allows flows to implement full requirements while gracefully managing exceptions when they occur.
Question 40
A canvas app requires displaying a hierarchical organization chart with drill-down capabilities. What is the most effective way to implement this visualization?
A) Use nested galleries with complex formulas
B) Implement a PCF control specifically designed for hierarchical data
C) Create separate screens for each level manually
D) Use standard text labels arranged manually
Answer: B
Explanation:
Implementing a PCF (PowerApps Component Framework) control specifically designed for hierarchical data is the most effective approach for organization charts. PCF controls can leverage specialized JavaScript libraries (like OrgChart.js or D3.js) that provide rich hierarchical visualizations with built-in drill-down, zoom, pan, and interactive features. PCF controls offer superior performance, customization, and user experience compared to attempting complex visualizations with native canvas app controls. Many open-source and commercial PCF organization chart controls exist that can be imported and configured.
Option A is incorrect because nested galleries with complex formulas create significant performance problems, limited interactivity, and maintenance challenges. Galleries aren’t designed for hierarchical tree structures, requiring convoluted formulas to simulate parent-child relationships. Deep nesting causes slow rendering and excessive formula evaluation. While technically possible for small hierarchies, this approach doesn’t scale and provides poor user experience compared to purpose-built visualization components.
Option C is incorrect because creating separate screens for each organizational level creates rigid, non-scalable solutions that don’t provide smooth drill-down experiences. This approach requires screen navigation for each level, creating disjointed user experience without smooth transitions. Changes to organizational structure require modifying multiple screens. This manual approach lacks the dynamic, data-driven visualization that organization charts require for effective navigation and exploration.
Option D is incorrect because using standard text labels arranged manually is completely impractical for organization charts with more than a few people. Manual positioning doesn’t adapt to data changes, can’t handle dynamic hierarchies, and provides no interactivity. This approach requires repositioning every label when the organization changes and becomes impossible to maintain with realistic organization sizes. Modern organization charts require dynamic, data-driven visualizations with automatic layout algorithms.
