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Appian Lead Developer Sample Questions (Q27-Q32):

NEW QUESTION # 27
You need to export data using an out-of-the-box Appian smart service. Which two formats are available (or data generation?

• A. XML
• B. Excel
• C. CSV
• D. JSDN

Answer: B,C

Explanation:
The two formats that are available for data generation using an out-of-the-box Appian smart service are:
* A. CSV. This is a comma-separated values format that can be used to export data in a tabular form, such as records, reports, or grids. CSV files can be easily opened and manipulated by spreadsheet applications such as Excel or Google Sheets.
* C. Excel. This is a format that can be used to export data in a spreadsheet form, with multiple worksheets, formatting, formulas, charts, and other features. Excel files can be opened by Excel or other compatible applications.
The other options are incorrect for the following reasons:
* B. XML. This is a format that can be used to export data in a hierarchical form, using tags and attributes to define the structure and content of the data. XML files can be opened by text editors or XML parsers, but they are not supported by the out-of-the-box Appian smart service for data generation.
* D. JSON. This is a format that can be used to export data in a structured form, using objects and arrays to represent the data. JSON files can be opened by text editors or JSON parsers, but they are not supported by the out-of-the-box Appian smart service for data generation. Verified References: Appian Documentation, section "Write to Data Store Entity" and "Write to Multiple Data Store Entities".

NEW QUESTION # 28
Your Agile Scrum project requires you to manage two teams, with three developers per team. Both teams are to work on the same application in parallel. How should the work be divided between the teams, avoiding issues caused by cross-dependency?

• A. Group epics and stories by technical difficulty, and allocate one team the more challenging stories.
• B. Allocate stories to each team based on the cumulative years of experience of the team members.
• C. Group epics and stories by feature, and allocate work between each team by feature.
• D. Have each team choose the stories they would like to work on based on personal preference.

Answer: C

Explanation:
Comprehensive and Detailed In-Depth Explanation:In an Agile Scrum environment with two teams working on the same application in parallel, effective work division is critical to avoid cross-dependency, which can lead to delays, conflicts, and inefficiencies. Appian's Agile Development Best Practices emphasize team autonomy and minimizing dependencies to ensure smooth progress.
* Option B (Group epics and stories by feature, and allocate work between each team by feature):
This is the recommended approach. By dividing the application's functionality into distinct features (e.
g., Team 1 handles customer management, Team 2 handles campaign tracking), each team can work independently on a specific domain. This reduces cross-dependency because teams are not reliant on each other's deliverables within a sprint. Appian's guidance on multi-team projects suggests feature- based partitioning as a best practice, allowing teams to own their backlog items, design, and testing without frequent coordination. For example, Team 1 can develop and test customer-related interfaces while Team 2 works on campaign processes, merging their work during integration phases.
* Option A (Group epics and stories by technical difficulty, and allocate one team the more challenging stories):This creates an imbalance, potentially overloading one team and underutilizing the other, which can lead to morale issues and uneven progress. It also doesn't address cross-dependency, as challenging stories might still require input from both teams (e.g., shared data models), increasing coordination needs.
* Option C (Allocate stories to each team based on the cumulative years of experience of the team members):Experience-based allocation ignores the project's functional structure and can result in mismatched skills for specific features. It also risks dependencies if experienced team members are needed across teams, complicating parallel work.
* Option D (Have each team choose the stories they would like to work on based on personal preference):This lacks structure and could lead to overlap, duplication, or neglect of critical features. It increases the risk of cross-dependency as teams might select interdependent stories without coordination, undermining parallel development.
Feature-based division aligns with Scrum principles of self-organization and minimizes dependencies, making it the most effective strategy for this scenario.
References:Appian Documentation - Agile Development with Appian, Scrum Guide - Multi-Team Coordination, Appian Lead Developer Training - Team Management Strategies.

NEW QUESTION # 29
You are tasked to build a large-scale acquisition application for a prominent customer. The acquisition process tracks the time it takes to fulfill a purchase request with an award.
The customer has structured the contract so that there are multiple application development teams.
How should you design for multiple processes and forms, while minimizing repeated code?

• A. Create a common objects application.
• B. Create a Center of Excellence (CoE).
• C. Create a Scrum of Scrums sprint meeting for the team leads.
• D. Create duplicate processes and forms as needed.

Answer: A

Explanation:
Comprehensive and Detailed In-Depth Explanation:As an Appian Lead Developer, designing a large-scale acquisition application with multiple development teams requires a strategy to manage processes, forms, and code reuse effectively. The goal is to minimize repeated code (e.g., duplicate interfaces, process models) while ensuring scalability and maintainability across teams. Let's evaluate each option:
* A. Create a Center of Excellence (CoE):A Center of Excellence is an organizational structure or team focused on standardizing practices, training, and governance across projects. While beneficial for long- term consistency, it doesn't directly address the technical design of minimizing repeated code for processes and forms. It's a strategic initiative, not a design solution, and doesn't solve the immediate need for code reuse. Appian's documentation mentions CoEs for governance but not as a primary design approach, making this less relevant here.
* B. Create a common objects application:This is the best recommendation. In Appian, a "common objects application" (or shared application) is used to store reusable components like expression rules, interfaces, process models, constants, and data types (e.g., CDTs). For a large-scale acquisition application with multiple teams, centralizing shared objects (e.g., rule!CommonForm, pm!
CommonProcess) ensures consistency, reduces duplication, and simplifies maintenance. Teams can reference these objects in their applications, adhering to Appian's design best practices for scalability.
This approach minimizes repeated code while allowing team-specific customizations, aligning with Lead Developer standards for large projects.
* C. Create a Scrum of Scrums sprint meeting for the team leads:A Scrum of Scrums meeting is a coordination mechanism for Agile teams, focusing on aligning sprint goals and resolving cross-team dependencies. While useful for collaboration, it doesn't address the technical design of minimizing repeated code-it's a process, not a solution for codereuse. Appian's Agile methodologies support such meetings, but they don't directly reduce duplication in processes and forms, making this less applicable.
* D. Create duplicate processes and forms as needed:Duplicating processes and forms (e.g., copying interface!PurchaseForm for each team) leads to redundancy, increased maintenance effort, and potential inconsistencies (e.g., divergent logic). This contradicts the goal of minimizing repeated code and violates Appian's design principles for reusability and efficiency. Appian's documentation strongly discourages duplication, favoring shared objects instead, making this the least effective option.
Conclusion: Creating a common objects application (B) is the recommended design. It centralizes reusable processes, forms, and other components, minimizing code duplication across teams while ensuring consistency and scalability for the large-scale acquisition application. This leverages Appian's application architecture for shared resources, aligning with Lead Developer best practices for multi-team projects.
References:
* Appian Documentation: "Designing Large-Scale Applications" (Common Application for Reusable Objects).
* Appian Lead Developer Certification: Application Design Module (Minimizing Code Duplication).
* Appian Best Practices: "Managing Multi-Team Development" (Shared Objects Strategy).
To build a large scale acquisition application for a prominent customer, you should design for multiple processes and forms, while minimizing repeated code. One way to do this is to create a common objects application, which is a shared application that contains reusable components, such as rules, constants, interfaces, integrations, or data types, that can be used by multiple applications. This way, you can avoid duplication and inconsistency of code, and make it easier to maintain and update your applications. You can also use the common objects application to define common standards and best practices for your application development teams, such as naming conventions, coding styles, or documentation guidelines. Verified References: [Appian Best Practices], [Appian Design Guidance]

NEW QUESTION # 30
Your team has deployed an application to Production with an underperforming view. Unexpectedly, the production data is ten times that of what was tested, and you must remediate the issue. What is the best option you can take to mitigate their performance concerns?

• A. Create a table which is loaded every hour with the latest data.
• B. Create a materialized view or table.
• C. Introduce a data management policy to reduce the volume of data.
• D. Bypass Appian's query rule by calling the database directly with a SQL statement.

Answer: B

Explanation:
Comprehensive and Detailed In-Depth Explanation:As an Appian Lead Developer, addressing performance issues in production requires balancing Appian's best practices, scalability, and maintainability. The scenario involves an underperforming view due to a significant increase in data volume (ten times the tested amount), necessitating a solution that optimizes performance while adhering to Appian's architecture. Let's evaluate each option:
* A. Bypass Appian's query rule by calling the database directly with a SQL statement:This approach involves circumventing Appian's query rules (e.g., a!queryEntity) and directly executing SQL against the database. While this might offer a quick performance boost by avoiding Appian's abstraction layer, it violates Appian's core design principles. Appian Lead Developer documentation explicitly discourages direct database calls, as they bypass security (e.g., Appian's row-level security), auditing, and portability features. This introduces maintenance risks, dependencies on database-specific logic, and potential production instability-making it an unsustainable and non-recommended solution.
* B. Create a table which is loaded every hour with the latest data:This suggests implementing a staging table updated hourly (e.g., via an Appian process model or ETL process). While this could reduce query load by pre-aggregating data, it introduces latency (data is only fresh hourly), which may not meet real- time requirements typical in Appian applications (e.g., a customer-facing view). Additionally, maintaining an hourly refresh process adds complexity and overhead (e.g., scheduling, monitoring).
Appian's documentation favors more efficient, real-time solutions over periodic refreshes unless explicitly required, making this less optimal for immediate performance remediation.
* C. Create a materialized view or table:This is the best choice. A materialized view (or table, depending on the database) pre-computes and stores query results, significantly improving retrieval performance for large datasets. In Appian, you can integrate a materialized view with a Data Store Entity, allowing a!
queryEntity to fetch data efficiently without changing application logic. Appian Lead Developer training emphasizes leveraging database optimizations like materialized views to handle large data volumes, as they reduce query execution time while keeping data consistent with the source (via periodic or triggered refreshes, depending on the database). This aligns with Appian's performance optimization guidelines and addresses the tenfold data increase effectively.
* D. Introduce a data management policy to reduce the volume of data:This involves archiving or purging data to shrink the dataset (e.g., moving old records to an archive table). While a long-term data management policy is a good practice (and supported by Appian's Data Fabric principles), it doesn't immediately remediate the performance issue. Reducing data volume requires business approval, policy design, and implementation-delaying resolution. Appian documentation recommends combining such strategies with technical fixes (like C), but as a standalone solution, it's insufficient for urgent production concerns.
Conclusion: Creating a materialized view or table (C) is the best option. It directly mitigates performance by optimizing data retrieval, integrates seamlessly with Appian's Data Store, and scales for large datasets-all while adhering to Appian's recommended practices. The view can be refreshed as needed (e.g., via database triggers or schedules), balancing performance and data freshness. This approach requires collaboration with a DBA to implement but ensures a robust, Appian-supported solution.
References:
* Appian Documentation: "Performance Best Practices" (Optimizing Data Queries with Materialized Views).
* Appian Lead Developer Certification: Application Performance Module (Database Optimization Techniques).
* Appian Best Practices: "Working with Large Data Volumes in Appian" (Data Store and Query Performance).

NEW QUESTION # 31
You are required to create an integration from your Appian Cloud instance to an application hosted within a customer's self-managed environment.
The customer's IT team has provided you with a REST API endpoint to test with: https://internal.network/api
/api/ping.
Which recommendation should you make to progress this integration?

• A. Expose the API as a SOAP-based web service.
• B. Deploy the API/service into Appian Cloud.
• C. Add Appian Cloud's IP address ranges to the customer network's allowed IP listing.
• D. Set up a VPN tunnel.

Answer: D

Explanation:
Comprehensive and Detailed In-Depth Explanation:As an Appian Lead Developer, integrating an Appian Cloud instance with a customer's self-managed (on-premises) environment requires addressing network connectivity, security, and Appian's cloud architecture constraints. The provided endpoint (https://internal.
network/api/api/ping) is a REST API on an internal network, inaccessible directly from Appian Cloud due to firewall restrictions and lack of public exposure. Let's evaluate each option:
* A. Expose the API as a SOAP-based web service:Converting the REST API to SOAP isn't a practical recommendation. The customer has provided a REST endpoint, and Appian fully supports REST integrations via Connected Systems and Integration objects. Changing the API to SOAP adds unnecessary complexity, development effort, and risks for the customer, with no benefit to Appian's integration capabilities. Appian's documentation emphasizes using the API's native format (REST here), making this irrelevant.
* B. Deploy the API/service into Appian Cloud:Deploying the customer's API into Appian Cloud is infeasible. Appian Cloud is a managed PaaS environment, not designed to host customer applications or APIs. The API resides in the customer's self-managed environment, and moving it would require significant architectural changes, violating security and operational boundaries. Appian's integration strategy focuses on connecting to external systems, not hosting them, ruling this out.
* C. Add Appian Cloud's IP address ranges to the customer network's allowed IP listing:This approach involves whitelisting Appian Cloud's IP ranges (available in Appian documentation) in the customer's firewall to allow direct HTTP/HTTPS requests. However, Appian Cloud's IPs are dynamic and shared across tenants, making this unreliable for long-term integrations-changes in IP ranges could break connectivity. Appian's best practices discourage relying on IP whitelisting for cloud-to-on-premises integrations due to this limitation, favoring secure tunnels instead.
* D. Set up a VPN tunnel:This is the correct recommendation. A Virtual Private Network (VPN) tunnel establishes a secure, encrypted connection between Appian Cloud and the customer's self-managed network, allowing Appian to access the internal REST API (https://internal.network/api/api/ping).
Appian supports VPNs for cloud-to-on-premises integrations, and this approach ensures reliability, security, and compliance with network policies. The customer's IT team can configure the VPN, and Appian's documentation recommends this for such scenarios, especially when dealing with internal endpoints.
Conclusion: Setting up a VPN tunnel (D) is the best recommendation. It enables secure, reliable connectivity from Appian Cloud to the customer's internal API, aligning with Appian's integration best practices for cloud- to-on-premises scenarios.
References:
* Appian Documentation: "Integrating Appian Cloud with On-Premises Systems" (VPN and Network Configuration).
* Appian Lead Developer Certification: Integration Module (Cloud-to-On-Premises Connectivity).
* Appian Best Practices: "Securing Integrations with Legacy Systems" (VPN Recommendations).

NEW QUESTION # 32
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