[Jan-2025] Verified Appian Exam Dumps with ACD300 Exam Study Guide
Best Quality Appian ACD300 Exam Questions LatestCram Realistic Practice Exams [2025]
NEW QUESTION # 12
You are just starting with a new team that has been working together on an application for months. They ask you toreview some of their views thathave been degrading inperformance. The viewsare highly complex with hundreds of lines of SOL What is the first step in troubleshooting the degradation?
- A. Go through the entire database structure to obtain on overview, ensure you understand the business needs, andthen normalize the tables to optimizeperformance.
- B. Browse through the tables, note any tables that contain a large volume of null values, and work with your team to plan for table restructure.
- C. Go through all of the tables one by one to identify which of the grouped by. ordered by. or joined keys are currently indexed
- D. Run an explain statement on the views, identify criticalareas of improvement that can be remediated and without business knowledge
Answer: D
Explanation:
Explanation
The first step in troubleshooting the degradation of the views is to run an explain statement on the views, identify critical areas of improvement that can be remediated without business knowledge. An explain statement is a tool that shows how a database executes a query or a view, and provides information about the cost, plan, and steps involved in the execution. By running an explain statement on the views, you can identify any inefficiencies or bottlenecks that are causing the degradation, such as missing indices, full table scans, nested loops, or hash joins. You can then apply some basic optimization techniques that do not require business knowledge, such as creating indices, limiting the number of columns or rows returned, using joins instead of subqueries, or using materialized views. Verified References: Appian Documentation, section
"Query Optimization".
NEW QUESTION # 13
You are asked to design a case management system for a client in addition to storing some basic metadata about a case, one of the client s requirements Is the ability for users to update a case The client would like any user in their organization of 500 people to be able to make these updates The users are all based in the company's headquarters, and there will be frequent cases where users are attempting to edit the same case. The client wants to ensure no information Is lost when these edits occur and does not want the solution to burden their process administrators with any additional effort.
Which data locking approach should you recommend?
- A. Use the database lo implement tow lewd pessimistic locking.
- B. Design a process report and query to determine who opened the edit form first
- C. Allow edits without locking the case GDI
- D. Add an Version annotation to the case COT to manage Vie locking
Answer: D
Explanation:
Explanation
The @Version annotation is a feature of Appian that allows for optimistic locking of CDTs. Optimistic locking assumes that concurrent updates to the same data are rare and does not lock the data until it is saved. If two users try to save changes to the same data, the user who saves first will succeed, while the user who saves second will get an error message and will have to resolve the conflict manually. This approach is suitable for the client's requirement, as itallows any user to update a case without locking it, ensures no information is lost when concurrent edits occur, and does not require any additional effort from the process administrators.
Verified References: [Appian Documentation], section "Optimistic Locking".
NEW QUESTION # 14
What are two advantages of having High Availability (HA) for Applan Cloud applications?
- A. In the event of a system failure, your Appian instance will fie restored and available to your users in less than 15 minutes.having lost no more than the last 1minute worth of data.
- B. An Applan Cloud HA instance is composed of multiple active nodes running in different availability zones in differentregions.
- C. A typical Appian Cloud HA instance is composed of two active nodes.
- D. Data andtransactions are continuouslyreplicated across the active nodes to achieve redundancy and avoid single points offailure.
Answer: A,D
Explanation:
Explanation
The two advantages of having High Availability (HA) for Appian Cloud applications are:
* B. Data and transactions are continuously replicated across the active nodes to achieve redundancy and avoid single points of failure. This is an advantage of having HA, as it ensures that there is always a backup copy of data and transactions in case one of the nodes fails or becomes unavailable. This also improves data integrity and consistency across the nodes, as any changes made to one node are automatically propagated to the other node.
* D. In the event of a system failure, your Appian instance will be restored and available to your users in less than 15 minutes, having lost no more than the last 1 minute worth of data. This is an advantage of having HA, as it guarantees a high level of service availability and reliability for your Appian instance.
If one of the nodes fails or becomes unavailable, the other node will take over and continue to serve requests without any noticeable downtime or data loss for your users.
The other options are incorrect for the following reasons:
* A. An Appian Cloud HA instance is composed of multiple active nodes running in different availability zones in different regions. This is not an advantage of having HA, but rather a description of how HA works in Appian Cloud. An Appian Cloud HA instanceconsists of two active nodes running in different availability zones within the same region, not different regions.
* C. A typical Appian Cloud HA instance is composed of two active nodes. This is not an advantage of having HA, but rather a description of how HA works in Appian Cloud. A typical Appian Cloud HA instance consists of two active nodes running in different availability zones within the same region, but this does not necessarily provide any benefit over having one active node. Verified References: Appian Documentation, section "High Availability".
NEW QUESTION # 15
As part of your implementation workflow, users need to retrieve data stored in a third-party Oracle database on an interface. You need to design a way to query this information.
How should you set up this connection and query the data?
- A. Configure a Query DataBase node within the process model Then, type in the connection information, as well as a SQL query to execute and return the data in process variables.
- B. Configure an expression-backed record type, calling an API to retrieve the data from the third-party database. Then, use allqueryRecordType to retrieve the data.
- C. Configure a limed utility process that queries data from the thirdparty database daily, and stores It in the Applan business database, Then use alqueryEntity eating the Applan data source to retrieve the data.
- D. in the Administration Console configure the third-party database as a ''New Data Source,'' Then, use alqueryEntity to retrieve the data.
Answer: D
Explanation:
Explanation
To meet the application requirement of allowing users to navigate throughout the application while maintaining complete visibility in the application structure, and easily navigate to previous locations, you should include a breadcrumbs pattern on applicable interfaces to show the organizational hierarchy. A breadcrumbs pattern is a user interface component that displays the current location of the user within the application, and provides links to the previous levels of the hierarchy. For example, if the user is viewing a product details page, the breadcrumbs pattern could show something like "Home > Products > Product Details". This way, the user can see where they are in the application, and easily go back to any previous level by clicking on the corresponding link.
The other options are not as effective. Option A, using Tiles as Cards pattern on the home page to prominently display application choices, would provide a way for users to access different parts of the application from the home page, but it would not show the organizational hierarchy or allow users to navigate to previous locations.
Option B, implementing an Activity History pattern to track an organization's activity measures, would provide a way for users to see the recent actions performed by themselves or others in the application, but it would not show the organizational hierarchy or allow users to navigate to previous locations. Option C, implementing a drilldown report pattern to show detailed information about report data, would provide a way for users to explore different levels of data in a report, but it would not show the organizational hierarchy or allow users to navigate to previous locations.
NEW QUESTION # 16
You are reviewing the Engine Performance Logs in Production for a single application thathas been live for six months. This application experiences concurrent user activity and has a fairly sustained load during business hours. The client has reported performance issues with the application during business hours.
During your investigation, you notice a high Work Queue - Java Work Queue Size value in the logs You also notice unattended process activities, including timer events and sending notifications emails, are taking far longer to execute than normal.
The client Increased the number of CPU cores prior to the application going live What is the next recommendation?
- A. Optimize slow-performing user interfaces.
- B. Add more application servers.
- C. Add more engine replicas.
- D. Add execution and analytics shards
Answer: C
Explanation:
Explanation
Adding more engine replicas will increase the number of threads available to execute unattended process activities, such as timer events and sending notification emails. This will reduce the Java Work Queue Size and improve the performance of the application. Verified References: Appian Engine Performance Logs, Appian Engine Configuration
NEW QUESTION # 17
Your Appian project just went live with the following environment setup; DEV > TEST (SIT/DAT) > PROD Your client is considering adding a support team to manage production defects and minor enhancements, white the original development team focuses on Phase 2 Your client is asking you for a new environment strategy that will have the least impact on Phase 2 development work.
Which option involves the lowest additional server cost and the least code retrofit effort?
- A. Phase 2 development work stream: DEV > TEST (SIT/UAT) >PROD Production support work stream DEV > TEST2 (SIT/UAT) > PROO
- B. Phase 2 development work stream: OEV > TEST (Srr/DAT) > PROO Production support work stream. DEV2 > TEST (SIT/UAT) > PROD
- C. Phase 2 development work steam: DEV > TEST (SIT) > STAGE (UAT) > PROO Production support work stream DEV > TEST2 (SIT/UAT)>PROO
- D. Phase 2 development work Stream: DEV > TEST (SIT) > STAGE (UAT) > PROO Production support work stream DEV2 > STAGE (S1T/UAT) > PROD
Answer: D
Explanation:
Explanation
The option B involves the lowest additional server cost and the least code retrofit effort, as it only requires one additional environment (DEV2) for the production support work stream. The production support work stream can use the existing STAGE environment for testing and user acceptance testing, as it is shared with the phase
2 development work stream. This way, there is no need to create a separate TEST2 environment or to retrofit any code from TEST to STAGE or from STAGE to PROD. Verified References: [Appian Certified Lead Developer study guide], page 16, section "Environment Strategy".
NEW QUESTION # 18
You are the lead developer for an Appian project, in a backlog refinement meeting You are presented with the following user story.
As a restaurant customer. I need to be able to place my food order online to avoid waiting in line for take out.' Which two functional acceptance criteria would you consider 'good'?
- A. The user will click Save, and the order information will be saved in the ORDER table and have audit history
- B. The system mutt handle up to 500 unique orders per day
- C. The user will receive an email notification when their order is completed.
- D. The user cannot submit the form without filling out all required fields.
Answer: C,D
Explanation:
Explanation
Functional acceptance criteria are the conditions that a user story must satisfy to be accepted by the user or stakeholder. They should be specific, measurable, achievable, relevant, and testable. In this case, two functional acceptance criteria that would be considered 'good' are:
* The user will receive an email notification when their order is completed. This is a specific, measurable, achievable, relevant, and testable criterion that describes a feature that the user needs to be informed of their order status.
* The user cannot submit the form without filling out all required fields. This is a specific, measurable, achievable, relevant, and testable criterion that describes afeature that the user needs to provide valid and complete information for their order.
The other options are not as good. Option A, the user will click Save, and the order information will be saved in the ORDER table and have audit history, is not a functional acceptance criterion, but rather a technical implementation detail that is not relevant or visible to the user. Option C, the system must handle up to 500 unique orders per day, is not a functional acceptance criterion, but rather a non-functional requirement that describes a performance or quality attribute of the system.
NEW QUESTION # 19
You add an index on the searched field of a MySQL table with many rows (>100k).
The field would benefit greatly from the Index in which three scenarios?
- A. The Add contains Dig integers, above and below 0.
- B. The field contains a textual shot Business code.
- C. The field contains long unstructured text such as a hash
- D. The field contains many datetimes, covering a large range
- E. The field contains a structured JSON.
Answer: A,B,D
Explanation:
Explanation
The field would benefit greatly from the index in the following scenarios:
* A. The field contains a textual short Business code. This is a scenario where an index can improve the performance of queries that search for exact matches or ranges of values in the field. A textual short Business code is likely to have high cardinality, meaning that it has many distinct values and low duplication. This makes the index more selective and efficient, as it can quickly narrow down the results based on the search criteria.
* C. The field contains many datetimes, covering a large range. This is a scenario where an index can improve the performance of queries that search for exact matches or ranges of values in the field. A datetime field is likely to have high cardinality, meaning that it has many distinct values and low duplication. This makes the index more selective and efficient, as it can quickly narrow down the results based on the search criteria.
* D. The field contains big integers, above and below 0. This is a scenario where an index can improve the performance of queries that search for exact matches or ranges of values in the field. A big integer field is likely to have high cardinality, meaning that it has many distinct values and low duplication. This makes the index more selective and efficient, as it can quickly narrow down the results based on the search criteria.
The other options are incorrect for the following reasons:
* B. The field contains long unstructured text such as a hash. This is a scenario where an index might not improve the performance of queries that search for exact matches or ranges of values in the field. A long unstructured text field is likely to have low cardinality, meaning that it has few distinct values and high duplication. This makes the index less selective and efficient, as it cannot quickly narrow down the results based on the search criteria. Moreover, indexing a long unstructured text field could increase thestorage space and maintenance cost for the database, which could affect the overall performance.
* E. The field contains a structured JSON. This is a scenario where an index might not improve the performance of queries that search for exact matches or ranges of values in the field. A structured JSON field is not a native data type in MySQL, and it requires special functions or operators to access or manipulate its elements. Indexing a structured JSON field could increase the complexity and overhead for the database, which could affect the overall performance. Verified References: Appian Documentation, section "Query Optimization".
NEW QUESTION # 20
You are selling up a new cloud environment. The customer already has a system of record for Its employees and doesn't want to re-create them in Appian. so you are going to Implement LDAP authentication.
What are the next steps to configure LDAP authentication?
To answer, move the appropriate steps from the Option list to the Answer List area, and arrange them in the correct order. You may or may not use all the steps.
Answer:
Explanation:
* Navigate to the Admin console > Authentication > LDAP. This is the first step, as it allows you to access the settings and options for LDAP authentication in Appian.
* Work with the customer LDAP point of contact to obtain the LDAP authentication xsd. Import the xsd file in the Admin console. This is the second step, as it allows you to define the schema and structure of the LDAP data that will be used for authentication in Appian. You will need to work with the customer LDAP point of contact to obtain the xsd file that matches their LDAP server configuration and data model. You will then need to import the xsd file in the Admin console using the Import Schema button.
* Enable LDAP and enter the LDAP parameters, such as the URL of the LDAP server and plaintext credentials. This is the third step, as it allows you to enable and configure the LDAP authentication in Appian. You will need to check the Enable LDAP checkbox and enter the required parameters, such as the URL of the LDAP server, the plaintext credentials for connecting to the LDAP server, and the base DN for searching for users in the LDAP server.
* Test the LDAP integration and see if it succeeds. This is the fourth and final step, as it allows you to verify and validate that the LDAP authentication is working properly in Appian. You will need
* to use the Test Connection button to test if Appian can connect to the LDAP server successfully.
You will also need to use the Test User Lookup button to test if Appian can find and authenticate a user from the LDAP server using their username and password.
NEW QUESTION # 21
You have 5 applications on your Appian platform in production. Users are now beginning to use multiple applications across the platform, and the client wants to ensure a consistent user experience across all applications You notice that some applications use rich text some use section layouts, and others use box layouts. The result is that each application has a different color and size for the header.
What would you recommend to ensure consistency across the platform?
- A. In the common application, create one rule for each application, and update each application to reference its respective rule
- B. Create constants for text size and color, and update each section lo reference these values.
- C. In each individual application, create a rule that can be used lot tot section headers, and update each application lo reference its respective rule
- D. In the common application, create a rule that can be used across the platform for section headers, and update each application to reference this new rule
Answer: D
Explanation:
Explanation
The best way to ensure consistency across the platform is to create a rule that can be used across the platform for section headers. This rule can be created in the common application, and then each application can be updated to reference this rule. This will ensure that all of the applications use the same color and size for the header, which will provide a consistent user experience.
The other options are not as effective. Option A, creating constants for text size and color, and updating each section to reference these values, would require updating each section in each application. This would be a lot of work, and it would be easy to make mistakes. Option C, creating one rule for each application, would also require updating each application. This would be less work than option A, but it would still be a lot of work, and it would be easy to make mistakes. Option D, creating a rule in each individual application, would not ensure consistency across the platform. Each application would have its own rule, and the rules could be different. This would not provide a consistent user experience.
Best Practices:
* When designing a platform, it is important to consider the user experience. A consistent user experience will make it easier for users to learn and use the platform.
* When creating rules, it is important to use them consistently across the platform. This will ensure that the platform has a consistent look and feel.
* When updating the platform, it is important to test the changes to ensure that they do not break the user experience.
NEW QUESTION # 22
Your application contains a process model that Is scheduled to run daily at a certain time, which kicks off a user input task to a specified user on the 1ST time zone for morning data collection The time zone is set to the (default) pm!timezone.
In this situation, what does the pm!tinezone reflect?
- A. The default time zone for the environment as specified in the Administration Console
- B. The line zone of the user who most recently published the process model
- C. The time zone of the user who is completing the input task.
- D. The time zone of the server where Applan is intuited
Answer: A
Explanation:
Explanation
In this situation, pm!timezone reflects the default time zone for the environment as specified in the Administration Console. pm!timezone is a process variable that returns the time zone of the process. If the time zone is not explicitly set in the process model, then pm!timezone returns the default time zone for the environment, which can be configured in the Administration Console. In this case, the time zone is set to the (default) pm!timezone, which means that the process model does not have a specific time zone, and therefore uses the default time zone for the environment.
The other options are not correct. Option A, the time zone of the server where Appian is installed, is not what pm!timezone reflects, as the server time zone may not be the same as the default time zone for the environment. Option B, the time zone of the user who most recently published the process model, is not what pm!timezone reflects, as the user's time zone may not be the same as the default time zone for the environment. Option D, the time zone of the user who is completing the input task, is not what pm!timezone reflects, as the user's time zone may not be the same as the default time zone for the environment.
NEW QUESTION # 23
For each scenario outlined, match the best tool to use to meet expectations. Each tool will be used once Note: To change your responses, you may deselected your response by clicking the blank space at the top of the selection list.
Answer:
Explanation:
NEW QUESTION # 24
You are running an inspection as a part of the first deployment process from TEST to PROD. You receive a notice that one of your objects will not deploy because it is dependent on an object from an application owned by a separate team.
What should be your next step?
- A. Push a functionally viable package to PROD without the dependencies, and plan the rest o! the deployment accordingly with the other team's constraints
- B. Create your own object with the same code base, replace (he dependent object in the application. and deploy to PROO.
- C. Check the dependencies of the necessary object Deploy w PROO if there are few dependencies and it is low risk
- D. Halt the production deployment and contact the other team tor guidance on promoting the object to PROD
Answer: D
Explanation:
Explanation
Deploying an object that is dependent on another object from a different application can cause errors and inconsistencies in the production environment. The best practice is to halt the production deployment and contact the other team for guidance on how to promote the object to PROD. The other team may have a different deployment schedule, or they may have some dependencies or customizations that need to be considered. By communicating with the other team, you can ensure that the object is deployed in a safe and coordinated manner, and avoid any potential conflicts or issues. Verified References: [Appian Deployment Guide], [Appian Best Practices]
NEW QUESTION # 25
You are planning a strategy around data volume testing for an Appian application that queries and writes to MySQL database.
You have administrator access to the Appian application and to the database.
What are two key considerations when designing a data volume testing strategy?
- A. The amount of data that needs to be populated should be determined by the project sponsor and the stakeholders based on their estimation
- B. Data from previous tests needs to remain in the testing environment prior to loading prepopulated data
- C. large datasets must be loaded via Applan processes
- D. Testing with the correct amount of data should be in the definition of done as part of each sprint.
- E. Data model changes must wait until towards the end of the protect.
Answer: D,E
Explanation:
Explanation
When designing a data volume testing strategy for an Appian application that queries and writes to MySQL database, you should consider two key considerations:
* Testing with the correct amount of data should be in the definition of done as part of each sprint. Data volume testing is a type of testing that verifies how well an application performs when handling large amounts of data. Data volume testing is important to ensure that the application meets the performance and quality requirements of the users and stakeholders. By including data volume testing in the definition of done as part of each sprint, you can ensure that each feature or functionality of your application is tested with realistic data volumes before being delivered to production. This way, you can identify and resolve any potential issues or bottlenecks early in the development cycle, and avoid any surprises or delays later on.
* Data model changes must wait until towards the end of the project. Data model changes are changes that affect the structure or schema of your database, such as adding, modifying, or deleting tables, columns, indexes, or constraints. Data model changes are risky and costly to make, especially when dealing with large amounts of data. Data model changes can affect the performance, functionality, or integrity of your
* application and database. Therefore, data model changes must wait until towards the end of the project, when you have finalized your requirements and design decisions, and have minimized your data volume testing efforts. By waiting until towards the end of the project to make data model changes, you can reduce the impact and complexity of those changes, and avoid any unnecessary rework or regression.
The other options are not as effective. Option A, data from previous tests needs to remain in the testing environment prior to loading prepopulated data, is not a key consideration for designing a data volume testing strategy, but rather a best practice for preparing your testing environment. Option B, large datasets must be loaded via Appian processes, is not a key consideration for designing a data volume testing strategy, but rather a technical implementation detail that may or may not be suitable for your application. Option C, the amount of data that needs to be populated should be determined by the project sponsor and the stakeholders based on their estimation, is not a key consideration for designing a data volume testing strategy, but rather an input or assumption that you need to validate before conducting your data volume testing.
NEW QUESTION # 26
You are deciding the appropriate process model data management strategy.
For each requirement. match the appropriate strategies to implement. Each strategy will be used once.
Note: To change your responses, you may deselect your response by clicking the blank space at the top of the selection list.
Answer:
Explanation:
Explanation
Requirement: Archive processes 2 days after completion or cancellation. Correct match: A. Processes that need to be available for 2 days after completion or cancellation, after which are no longer required nor accessible Exact explanation of correct match taken from Appian Documentation: This strategy is called
"Archive after 2 days" and it is one of the options for process model data management in Appian. This strategy means that processes that complete or cancel will remain available for 2 days, after which they will be archived and no longer accessible. This strategy can help reduce the size of the process database and improve the performance of process reporting.
Requirement: Use system default (currently auto-archive processes 7 days after completion or cancellation).
Correct match: C. Processes that remain available for 7 days after completion or cancellation, after which are archived when accessed Exact explanation of correct match taken from Appian Documentation: This strategy is called "Use system default" and it is one of the options for process model data management in Appian. This strategy means that processes that complete or cancel will remain available for 7 days, after which they will be archived when accessed. This strategy can help balance the availability and performance of process data, as it allows processes to be archived on demand rather than on a fixed schedule.
Requirement: Delete processes 2 days after completion or cancellation. Correct match: B. Processes that need to be available for 2 days after completion or cancellation, after which remain accessible Exact explanation of correct match taken from Appian Documentation: This strategy is called "Delete after 2 days" and it is one of the options for process model data management in Appian. This strategy means that processes that complete or cancel will remain available for 2 days, after which they will be deleted and no longer accessible. This strategy can help reduce the size of the process database and improve the performance of process reporting, but it also means that process data will be permanently lost.
Requirement: Do not automatically clean-up processes. Correct match: D. Processes that need to remain available without the need to unarchive Exact explanation of correct match taken from Appian Documentation: This strategy is called "Do not automatically clean-up" and it is one of the options for process model data management in Appian. This strategy means that processes that complete or cancel will remain available indefinitely without being archived or deleted. This strategy can help ensure the availability and integrity of process data, but it also means that the process database will grow over time and affect the performance of process reporting.
NEW QUESTION # 27
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