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Adobe AD0-E902 Exam Syllabus Topics:

Topic	Details
Topic 1	Testing and Error Handling: This section of the exam measures the skills of Quality Assurance Engineers and evaluates the principles of testing and error handling in Fusion. Candidates must define test plans and test cases, identify directives for handling unreliable services, and configure custom error handling mechanisms. One specific skill tested is applying the correct error-handling directive to manage service disruptions.
Topic 2	Foundational Technical Concepts: This section of the exam measures the skills of Fusion Developers and covers core technical concepts related to data transformation, function nesting, and expression formation in Fusion. Candidates must understand how to modify field formats, use appropriate functions, and work with data manipulation techniques. One key skill evaluated is selecting the correct function to transform data between different formats.
Topic 3	Working with APIs: This section of the exam measures the skills of Integration Specialists and assesses knowledge of API interactions within Fusion. Candidates must handle rate-limiting errors, identify ways to integrate third-party APIs and determine the correct module types when built-in functionalities are unavailable. One critical skill evaluated is implementing a solution for API rate limits to ensure seamless integration.
Topic 4	Scenario Design and Architecture: This section of the exam measures the skills of Solution Architects and focuses on designing and structuring Fusion scenarios efficiently. Candidates must determine the correct steps to parse JSON, perform data lookups, and distinguish between different triggers. Understanding system limitations, module selection, and timezone handling is also essential. One key skill assessed is identifying the appropriate method for uploading documents while managing access controls.

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Adobe Workfront Fusion Professional Sample Questions (Q28-Q33):

NEW QUESTION # 28
A query returns a partial list of possible values.
Which flow control module should be used to ensure all the possible results are queried?

A. Router
B. Iterator
C. Repeater
D. Aggregator

Answer: C

Explanation:
* Understanding the Requirement:
* The query returns only a partial list of possible values.
* The task is to ensure that all results are processed by iterating through multiple queries or pages of data.
* Why Option B ("Repeater") is Correct:
* TheRepeatermodule is designed to repeat an operation a specified number of times or until a condition is met.
* It is commonly used for querying paginated data or when a system limits the number of records returned in a single request.
* In this case, the Repeater ensures all possible values are queried by making additional requests to retrieve subsequent pages or results.
* Why the Other Options are Incorrect:
* Option A ("Aggregator"):
* The Aggregator combines multiple data bundles into a single output. It does not handle iterative queries or pagination.
* Option C ("Iterator"):
* The Iterator splits an array into individual items for processing. It does not handle querying for additional data or looping through requests.
* Option D ("Router"):
* The Router splits the flow of a scenario into multiple paths based on conditions. It is unrelated to iterative querying.
* Steps to Configure the Repeater:
* Add theRepeatermodule to your scenario.
* Configure the number of repetitions or the condition to continue querying (e.g., based on the presence of additional data).
* Link the Repeater to the module responsible for retrieving the data, ensuring it processes all available results.
* How This Solves the Problem:
* The Repeater module ensures that all possible results are queried by iteratively sending requests until no more data is available.
References and Supporting Documentation:
* Adobe Workfront Fusion: Repeater Module Documentation
* Workfront Community: Using Flow Control Modules

NEW QUESTION # 29
Which action in Fusion enables resource sharing, such as connections, data stores, and keys?

A. Create a new organization
B. Create a new group
C. Create a new team

Answer: C

Explanation:
* Understanding the Requirement:
* The user wants to enableresource sharingin Fusion, includingconnections,data stores, andkeys.
* Resource sharing is necessary to allow multiple scenarios or users to access shared resources efficiently within the same Fusion environment.
* Why Option B ("Create a new team") is Correct:
* Teams in Fusion:
* Teams are a feature in Adobe Workfront Fusion designed to group users together within an organization.
* By creating ateam, you can enableshared accessto resources such as API connections, data stores, and authentication keys, streamlining collaboration and avoiding duplication.
* Resource Sharing with Teams:
* All members of the team can access shared resources (e.g., connections), allowing consistent and collaborative scenario development and execution.
* Example: If multiple users within a team need to use the same API connection, creating a team allows the connection to be configured once and shared among all team members.
* Why the Other Options are Incorrect:
* Option A ("Create a new group"):
* Groups in Fusion are used primarily for organizing scenarios or categorizing users but do not inherently allow sharing of resources like connections or keys. Groups lack the resource-sharing functionality of teams.
* Option C ("Create a new organization"):
* Organizations in Fusion represent the highest-level administrative entity. While creating an organization allows resource sharing among all users within the organization, it is not the recommended solution for managing resource sharing in smaller or more focused groups, such as project teams.
* Steps to Create a New Team and Share Resources:
* Log in to Adobe Workfront Fusion.
* Navigate to theAdmin PanelorTeam Managementsection.
* SelectCreate a New Teamand provide a name for the team.
* Assign users to the team by adding their Fusion accounts.
* Configure shared resources (e.g., connections, data stores, keys) to be accessible by the team.
* Save the settings, and all team members will now have access to the shared resources.
* How This Solves the Problem:
* Creating a team ensures that all resources, such as connections, data stores, and keys, are accessible to team members without requiring individual duplication or configuration. It simplifies collaboration and promotes consistency across scenarios.
References and Supporting Documentation:
* Adobe Workfront Fusion: Teams Overview
* Workfront Community: Managing Teams and Resource Sharing

NEW QUESTION # 30
A source system provides a list of users and their job roles and departments. The destination system requires the job role values be revised to match the job roles by different department. The end users currently use a spreadsheet to manage that mapping. Updates to this list are infrequent, and management requires more security than the current process offers.
Which method is appropriate for this use case?

A. Data store
B. Table aggregator
C. Switch
D. Spreadsheet

Answer: A

Explanation:
Step by Step Comprehensive Detailed Explanation:
* Scenario Summary:
* The source system provides a list of users, job roles, and departments.
* The destination system requires a mapping of job roles to different departments.
* Updates to this mapping are infrequent, and there is a concern for more security than a spreadsheet offers.
* Option Analysis:
* A. Switch: A switch function in Workfront Fusion is used to make decisions based on specific conditions but does not maintain persistent data like mappings over time. It is not suitable for storing mappings that require infrequent updates.
* B. Spreadsheet: Spreadsheets may be simple to use but are less secure and not ideal for integrating with Workfront Fusion workflows due to their lack of direct integration features or control over changes.
* C. Data store: Adata storein Workfront Fusion is specifically designed for storing persistent data, such as mappings or reference tables. It is secure, easy to manage, and integrates seamlessly with workflows, making it the best choice for this use case.
* D. Table aggregator: A table aggregator is used for combining or processing data within a workflow but is not suitable for storing persistent mappings outside of a running scenario.
* Why Data Store is Appropriate:
* Persistence: A data store is ideal for maintaining the job role and department mappings across scenarios.
* Security: It is managed within Workfront Fusion, offering better control and access restrictions compared to a spreadsheet.
* Ease of Integration: Data stores can be directly queried or updated in Fusion workflows, allowing seamless handling of mappings.
* Scalability: While updates are infrequent, the data store can handle changes easily and scale if the volume of mappings increases.
* Implementation in Workfront Fusion:
* Create adata storefor job roles and departments in Workfront Fusion.
* Set up fields for Job Role and Department in the data store.
* Use Workfront Fusion scenarios to retrieve and update mappings from this data store based on requirements.
References:This approach aligns with the Workfront Fusion documentation on data stores, which are designed for secure and efficient storage of persistent data used across scenarios. See Workfront Fusion resources for data store setup and use cases for further details.

NEW QUESTION # 31
A series of queries return several JSON packets that include a combination of nested arrays representing objects and their fields.
How should that information be arranged if each object needs to be processed through a portion of the scenario?

A. Merge the JSON > Parse the JSON > then use the Iterator
B. Define the data structure > Parse the JSON > then process arrays in the Iterator
C. Define the data structure > then run the Iterator to Parse each JSON packet
D. Concatenate the JSON > Define the data structures > Parse the JSON > then run the Iterator

Answer: B

Explanation:
Step by Step Comprehensive Detailed Explanation:
* Understanding the Problem:
* Multiple JSON packets with nested arrays are being returned by queries.
* The goal is to process each object within these JSON arrays through the scenario.
* Option Analysis:
* A. Define the data structure > then run the Iterator to Parse each JSON packet:
* Incorrect. While defining a data structure is necessary, running the Iterator first would fail to process the JSON properly if it is not parsed.
* B. Concatenate the JSON > Define the data structures > Parse the JSON > then run the Iterator:
* Incorrect. Concatenation is unnecessary for this scenario since each JSON packet can be parsed and processed independently.
* C. Define the data structure > Parse the JSON > then process arrays in the Iterator:
* Correct. The correct approach involves defining a data structure to map the JSON, parsing it to extract the data into usable fields, and then using an Iterator module to process each object in the nested arrays.
* D. Merge the JSON > Parse the JSON > then use the Iterator:
* Incorrect. Merging JSON packets is not required unless you explicitly need to combine data from multiple packets into a single structure, which is not mentioned in this scenario.
* Why This Workflow Works:
* Defining the Data Structure: Helps Fusion understand and map the JSON fields for processing.
* Parsing the JSON: Extracts the data into fields and arrays that can be further processed.
* Using the Iterator: Breaks down the nested arrays into individual objects for sequential processing through the scenario.
* Implementation Steps:
* Use aDefine Data Structuremodule to define the JSON schema (fields, arrays, and objects).
* Add aParse JSONmodule to convert raw JSON packets into mapped data fields.
* Add anIteratormodule to process individual objects in the nested arrays.

NEW QUESTION # 32
A Fusion designer discovers that an iteration is processing thousands of bundles, though it should not need to.
What should the designer do to reduce the number of bundles?

A. Configure the trigger module to reduce the maximum number of results that Fusion will process during one execution cycle
B. Configure the trigger module to filter out unnecessary records
C. Configure the scenario settings to reduce the number of cycles per execution

Answer: B

Explanation:
Step by Step Comprehensive Detailed Explanation:
* Problem Summary:
* A trigger module is causing excessive iteration processing thousands of bundles unnecessarily.
* The goal is to optimize the scenario by reducing the number of processed bundles.
* Option Analysis:
* A. Configure the trigger module to reduce the maximum number of results:
* Reducing the maximum number of results processed per cycle limits the number of bundles processed at a time, but it does not solve the root issue of processing unnecessary records.
* B. Configure the trigger module to filter out unnecessary records:
* Filtering at the trigger level ensures that only the required records are fetched for processing, addressing the root cause of excessive bundle processing. This is the correct answer.
* C. Configure scenario settings to reduce cycles per execution:
* Limiting execution cycles reduces the overall runtime but does not directly address the number of bundles being processed unnecessarily.
* Why Filtering at the Trigger is Best:
* Efficiency: By setting up filters directly in the trigger, you ensure that only relevant data is retrieved.
* Performance: Reducing the number of unnecessary bundles improves processing speed and reduces resource usage.
* Accuracy: Filtering ensures only actionable data enters the workflow, maintaining scenario integrity.
* How to Implement:
* Open the trigger module settings.
* Add appropriate filters to exclude unnecessary records. For example:
* Add conditions to filter out old data or irrelevant statuses.
* Use fields like updatedDate, status, or any other criteria relevant to the workflow.
* Test the trigger module to verify that only relevant bundles are retrieved.
References:These answers are based on Workfront Fusion best practices for optimizing scenarios, as outlined in the Fusion documentation. Proper use of mapping panel functions and trigger filters ensures scenarios are efficient and scalable.

NEW QUESTION # 33
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