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Test Adobe AD0-E902 Prep - AD0-E902 Regualer Update

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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

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.

Topic 3

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 4

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.

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Adobe Workfront Fusion Professional Sample Questions (Q47-Q52):

NEW QUESTION # 47
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 > then run the Iterator to Parse each JSON packet
C. Define the data structure > Parse the JSON > then process arrays in the Iterator
D. Concatenate the JSON > Define the data structures > Parse the JSON > then run the Iterator

Answer: C

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 # 48
Given the array below, a user wants a comma-separated string of all stat names.

What is the correct expression?

Answer: C

Explanation:
* Understanding the Requirement:
* The input is an array containing objects, and the goal is to extract all the stat.name values into a comma-separated string.
* Example Input:
[
{
"base_stat": 48,
"effort": 1,
"stat": {
"name": "hp",
"url": "https://pokeapi.co/api/v2/stat/1/"
}
},
{
"base_stat": 48,
"effort": 0,
"stat": {
"name": "attack",
"url": "https://pokeapi.co/api/v2/stat/2/"
}
}
]
* Example Output:"hp, attack"
* Why Option B is Correct:
* The expressionjoin(map(2.data: stats[]; stats.stat.name); ", "):
* map: Iterates through each object in the array (2.data: stats[]) and extracts the stat.name field.
* join: Combines the extracted values into a single string, separated by a comma and space (", ").
* Breaking it down:
* map(2.data: stats[]; stats.stat.name) # Creates an array of names: ["hp", "attack"].
* join(...; ", ") # Converts the array into the string "hp, attack".
* Why the Other Options are Incorrect:
* Option A: join(2.data: stats[]; stat.name; ", ")
* This syntax is incorrect because it attempts to directly access stat.name within the join function without first mapping the values.
* Option C: join(map(2.data: stats[]; stat.name); ", ")
* The mapping references stat.name directly but does not account for the nested structure (stats.stat.name).
* Option D: join(flatten(2.data: stats[]); ", ")
* The flatten function is unnecessary here as the data is already structured. It would not properly extract the stat.name values.
* Steps to Implement in Workfront Fusion:
* Add aMapping/Transformation Module.
* Use the join(map(...)) function as described to transform the input array into a comma-separated string.
* Test the output to ensure it correctly generates the desired format.
* How This Solves the Problem:
* The map function ensures the proper extraction of nested stat.name values.
* The join function combines these values into the desired format efficiently.
References and Supporting Documentation:
* Adobe Workfront Fusion Functions Documentation
* Workfront Community: Using Map and Join Functions
The combination of map and join ensures that the stat names are extracted and formatted into a single comma-separated string, as required.

NEW QUESTION # 49
Which statement about the differences between instant and polling triggers is true?

A. A user must set up a webhook in Fusion to use Instant Triggers that make polling triggers easier to use and more reliable in scenarios
B. To keep track of records processed, instant triggers store received webhooks in a queue, whereas polling triggers remember which records have already been processed
C. Only polling triggers can be set to run on a schedule and should be used to avoid shutdown of third- party systems during working hours
D. A user should use instant triggers when available because instant triggers allow Fusion to process bundles of data faster than polling triggers

Answer: D

Explanation:
* Understanding Instant and Polling Triggers:
* Instant Triggers:
* Rely on webhooks to receive real-time data from a third-party system.
* The external system sends a notification (webhook) to Fusion whenever an event occurs, triggering the scenario immediately.
* Polling Triggers:
* Regularly check (poll) the third-party system for new or updated records at scheduled intervals.
* These are slower because they involve repeated API requests.
* Why Option B is Correct:
* Speed and Efficiency:
* Instant triggers process data faster because they act immediately upon receiving a webhook. Polling triggers, on the other hand, may take time depending on the polling frequency and can result in unnecessary delays.
* Reduced Load on Systems:
* Instant triggers generate fewer API calls than polling triggers, which continuously check for new records even if no changes have occurred.
* Best Practice: Use instant triggers whenever supported by the third-party system to ensure faster and more efficient scenario execution.
* Why the Other Options are Incorrect:
* Option A ("Instant triggers store received webhooks in a queue"):
* Webhooks do not store data in a queue; they simply notify Fusion of events in real-time.
Polling triggers also do not store records but remember the last processed record.
* Option C ("A user must set up a webhook in Fusion"):
* Instant triggers require setting up webhooks in the external system, not in Fusion. Fusion provides the webhook endpoint, but the user must configure the source system to send data.
* Option D ("Only polling triggers can be set to run on a schedule"):
* This is incorrect because instant triggers do not rely on schedules; they operate in real-time.
Polling triggers, however, run on schedules and are used when instant triggers are unavailable.
References and Supporting Documentation:
* Adobe Workfront Fusion Triggers Documentation
* Workfront Community: Differences Between Instant and Polling Triggers Instant triggers are the preferred option when available, as they provide real-time data processing with greater speed and efficiency than polling triggers.

NEW QUESTION # 50
REST APIs commonly implement CRUD operations, including Create, Read, Update, and Delete.
Which two actions is an object ID generally required to be provided as an input? Choose two.

A. Update
B. Delete
C. Create
D. Respond

Answer: A,B

Explanation:
* Object ID in CRUD Operations:REST APIs commonly use CRUD operations to interact with resources. TheObject IDserves as a unique identifier for the resource and is generally required for the following actions:
* A. Update:
* To update a specific resource, the API must know which resource to modify. The Object ID is used to identify the exact resource that should be updated.
* Example: A PUT or PATCH request typically requires the Object ID in the URL or body of the request.
* URL Example:
PUT /tasks/{id}
* B. Delete:
* Similarly, when deleting a specific resource, the Object ID is needed to ensure the correct resource is removed.
* Example: A DELETE request requires the Object ID in the URL to target the specific resource.
* URL Example:
DELETE /tasks/{id}
* Why Not Other Options?
* C. Respond: This is not a standard CRUD operation in REST APIs and does not involve an Object ID.
* D. Create: The Create operation (typically POST) does not require an Object ID because the resource does not yet exist. Instead, the API usually generates the Object ID after creation.
References:
* REST API Documentation Best Practices: CRUD Operations
* Experience League: Understanding CRUD in Workfront APIs

NEW QUESTION # 51
A custom API call to a web service is used inside of a high volume iteration. The module that calls the web service sometimes returns an error - 429: Too many requests.
Which two actions may be used to address this error? (Choose two.)

A. Use an ignore directive on the module generating the error
B. Add a sleep module just prior to the module generating the error
C. Add a module to test the service for errors
D. Use a break directive on the module generating the error

Answer: B,C

NEW QUESTION # 52
......

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