QUESTION: 25

In a long-running context what is the status of a job waring for human valuation?

Stopping
Suspended
Running
Stopped

Answer(s): B

Explanation:

In a long-running context, a job can be suspended when it is waiting for human validation or intervention. This means that the job is paused until a human user performs an action, such as approving or rejecting a document, providing some input, or resolving an exception. A suspended job can be resumed by the user or by the orchestrator, depending on the configuration of the process. A suspended job is different from a stopping or stopped job, which means that the job is being terminated or has been terminated by the user or by the orchestrator. A suspended job is also different from a running job, which means that the job is executing normally without any interruption or delay.

Reference:

Long-Running Workflows - UiPath Documentation Portal, Managing Jobs - UiPath Documentation Portal, Long Running Workflow - UiPath Activities

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QUESTION: 26

A Solutions Architect is cresting the Solution Design diagram for a transactional process. The transactions represent invoice Numbers that should be processed sequent it two applications and they are received and formatted as a table in a CSV file. A transaction Should only be processed once in each application E.g It a System Exception occurs after invoice ABC was processed m Application 1 when retrying the transaction invoice ABC should only be processed in Application 2
The following metrics are known:
-Average Transaction Handling Time = 30 seconds
-Average Volume per day = 3500 transactions
Which of the following approaches is the most suitable for the process described above? A)

B)

C)

D)

Option A
Option B
Option C
Option D

Answer(s): B

Explanation:

Option B is the most suitable approach for the process described above, as it uses the Robotic Enterprise Framework (ReFramework) template with TransactionItem set as DataRow and TransactionData as DataTable. This template provides a robust and scalable structure for transactional processes, with built-in mechanisms for exception handling, logging, retrying, and reporting. By setting the TransactionItem as DataRow and the TransactionData as DataTable, the process can read the invoice numbers from the CSV file and process them one by one in a loop. The template also allows the use of queues to store the transaction data and status, which enables the process to resume from the last successful transaction in case of a system exception. This way, the process can ensure that each invoice number is processed only once in each application, and avoid duplicate or skipped transactions. The template also integrates with UiPath Orchestrator, which provides centralized management, monitoring, and scheduling of the process. The template also supports the use of long-running workflows, which can handle human intervention scenarios using UiPath Action Center. The template also complies with the UiPath Automation Solution Architect best practices and standards, such as naming conventions, modularity, reusability, and maintainability.

Reference:

UiPath Studio - Robotic Enterprise Framework Template
UiPath Studio - Working with Queues in the ReFramework UiPath Studio - Long Running Workflow Template with UiPath Tasks [UiPath Automation Solution Architect - Course Overview] [UiPath Automation Solution Architect - Best Practices and Standards]

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QUESTION: 27

How can UiPath Communications Mining and Document Understanding be combined to optimize data extraction and analysis in an automated business process?

Communications Mining can extract insights from unstructured messages and Document Understanding can obtain hey Information from attached files
Communications Mining can access confidential messages and files and feed the data collected to Document Understanding for analysis
Communications Mining can be Inked directly to the output form Document Understanding to generate summaries of every communication
Communications Mining should be used to reanalyze data extracted by Document Understanding as if it were unstructured messages tor creating analytics

Answer(s): A

Explanation:

UiPath Communications Mining is a platform that uses AI to monitor and automate business communications across different channels, such as email, chat, calls, and tickets. It can extract insights from unstructured messages, such as the reasons for contact, the data fields, and the sentiment. UiPath Document Understanding is a framework that uses AI to process and analyze documents of various formats, such as PDF, Word, Excel, and images. It can obtain key information from attached files, such as the document type, the fields, and the values. By combining Communications Mining and Document Understanding, businesses can optimize data extraction and analysis in an automated business process. For example, a customer service process that involves reading both messages and documents to complete a request can be automated by using Communications Mining to understand the customer's intent and data from the message, and Document Understanding to extract the relevant information from the document. This way, the process can be faster, more accurate, and more scalable.

Reference:

Communications Mining - Overview - UiPath Documentation Portal [Document Understanding - Overview - UiPath Documentation Portal] How and where Communications Mining can be deployed

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QUESTION: 28

What can be slated as tactual when it comes to Multi-node HA-ready production deployment?

A multi node HA ready production deployment involves one server node behind a toad balancer
A multi-node HA-ready production deployment involves a single-server node
A multi-node HA-ready production deployment involves 3 or more server nodes behind a toad balancer
A multi-node HA-ready production deployment has a knitted number of agent nodes

Answer(s): C

Explanation:

A multi-node HA-ready production deployment is the only configuration supported for production use by UiPath Automation Suite. It ensures that the cluster can handle increased workloads and demand, as well as provide resilience and availability in case of node failures or disasters. A multi- node HA-ready production deployment requires at least 3 server nodes behind a load balancer, which distributes the incoming requests among the nodes and manages the cluster state. The number of agent nodes, which run the UiPath products and shared components, is optional and depends on the actual usage and capacity. A specialized agent node with GPU support is recommended for running special tasks like Task Mining analysis and Document Understanding pipelines, which require high computational power.

Reference:

Automation Suite - Deployment architecture - UiPath, Automation Suite - Manual: Multi-node HA-ready production profile requirements and installation - UiPath.

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Free UiPath-ASAPv1 Exam Braindumps (page: 8)

QUESTION: 25

Explanation:

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QUESTION: 26

Explanation:

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QUESTION: 27

Explanation:

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QUESTION: 28

Explanation:

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