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UiPath Certified Professional Automation Business Analyst Professional v1.0 Sample Questions (Q136-Q141):

NEW QUESTION # 136
You are a Business Analyst tasked to analyze the feasibility of automating a process that takes as input a few hundred invoices per day. The invoices are received from a few dozen vendors. What is the best data extraction method for this process, keeping in mind the robustness of the process?
ACME Corporation
Beep freep/ Outsmart the competition
123 Road Runner Lane Desert City. AZ 85001 Phone: (800) 555-1234
TO:
Wile E Coyote
456 Canyon Chase Desert City. AZ 85002
INVOICE
INVOICE #20240731-001 DATE: 2024-07-31 DUE DATE: 2024-08-15
SHIP TO:
Wile E Coyote 456 Canyon Chase
Desert City, AZ 85002
QUANTITY DESCRIPTION UNIT PRICE TOTAL
2 ACME Rocket Skates $125 $250
1 ACME Giant Rubber Band (for tripping Road Runners) $45 $45
3 ACME Dynamite Kit $35 $105
1 ACME Anvil $75 $75
5 ACME Bird Seed $5 $25
SUBTOTAL SALES TAX (8 6%) SHIPPING & HANDLING TOTAL DUE $500
$43
$10
$553
Make all checks payable to ACME Corporation
If you have any questions concerning this invoice, contact Road Runner
THANK YOU FOR YOUR BUSINESS!

A. Model-based extractor
B. Rule-based extractor
C. Form-based extractor
D. RegEx-based extractor

Answer: A

Explanation:
Understanding the Scenario:
The process involves handling a few hundred invoices per day from several dozen vendors.
Each vendor likely uses different invoice templates, formats, and layouts, leading to high variability in input data.
The goal is to implement a robust and scalable data extraction method.
Why Model-Based Extractor is the Best Choice:
Model-based extractors leverage machine learning models trained on various document templates, making them ideal for diverse and semi-structured data like invoices.
The machine learning model can adapt to multiple formats and intelligently extract required data fields (e.g., invoice numbers, dates, line items, totals).
It ensures scalability as new vendor templates are introduced-additional training allows the model to learn new patterns effectively.
Comparison with Other Options:
Form-Based Extractor (Option A): Effective for extracting data from fixed, structured forms with minimal layout changes. It is not suitable for invoices with varying designs.
Rule-Based Extractor (Option C): Relies on static rules for data extraction. This approach fails to handle complex layouts or adapt to variations across dozens of vendor templates.
RegEx-Based Extractor (Option D): Uses regular expressions for specific patterns but is labor-intensive and error-prone for datasets with multiple formats and inconsistent structures.
Additional Benefits of Model-Based Extractor:
Can detect and extract data from images and scanned PDFs using OCR (Optical Character Recognition).
Reduces the time and effort required for manual intervention and template-specific configuration.
Relevance in UiPath Ecosystem:
UiPath's Document Understanding Framework includes AI-powered model-based extractors, designed to efficiently process a wide range of document types like invoices, purchase orders, and receipts.
By utilizing a model-based extractor, you ensure that the solution is robust, scalable, and capable of handling the high volume and variability of invoices effectively.

NEW QUESTION # 137
Within UiPath Process Mining, UiPath Automation Hub is used to turn ideas for automation that are discovered from UiPath Process Mining into real automated implementations. What is a best use case to send ideas for process automation from UiPath Process Mining to UiPath Automation Hub?

A. When you have identified a case ID with high automation rate (>80%) and you want to send the idea to UiPath Automation Hub
B. When you have identified an activity that takes a short-time to no time to be executed and you want to send the idea to UiPath Automation Hub
C. When you have identified an efficient activity that takes a short-time to be executed and you want to send the idea to UiPath Automation Hub
D. When you have identified a manual activity that takes a long-time to be executed and you want to send the idea to UiPath Automation Hub

Answer: D

Explanation:
The best use case for sending ideas for process automation from UiPath Process Mining to UiPath Automation Hub is when a manual activity has been identified that takes a significant amount of time to execute. This is because automating such activities can lead to considerable improvements in efficiency and productivity. UiPath Process Mining helps in identifying bottlenecks in processes, and when such a time-consuming manual activity is found, it is a prime candidate for automation. By sending this idea to the Automation Hub, it can be investigated and processed further to develop a real automated implementation1.

NEW QUESTION # 138
What event can affect selector reliability in automations?

A. An increase in the volume of transactions
B. Target applications changing their position on the screen
C. An update to the UiPath Robot running the automation
D. Automation target applications being updated

Answer: D

Explanation:
An event that can affect selector reliability in automations is the target applications being updated. Updates to applications can alter the UI elements and structures that selectors depend on, leading to failures in identifying these elements during automation execution.
Reference: UiPath Documentation on Selector Reliability at https://docs.uipath.com/.

NEW QUESTION # 139
Which of the following are possible queue item statuses in UiPath Orchestrator?

A. New, Assigned, Processed, and Archived
B. New, In Progress, Successful, and Failed
C. Queued, Started, Finished, and Aborted
D. Ready, Running, Completed, and Stopped

Answer: B

Explanation:
Within UiPath Orchestrator, the possible statuses for queue items include New, In Progress, Successful, and Failed. These statuses represent the lifecycle of a queue item from its creation (New), through its processing (In Progress), to its conclusion, which can either be successful completion (Successful) or encountering an error (Failed). This categorization helps in monitoring and managing the workflow execution more effectively()().
For more detailed insights and guidance, you can explore the UiPath Test Suite Overview on the UiPath Academy(UiPath Academy).
Top of Form

NEW QUESTION # 140
What is the difference between training an ML model using a CPU versus using a GPU in UiPath Cloud Platform?

A. Training a model using a GPU is around five times faster than using a CPU
B. You can train multiple models on the same GPU at the same time
C. Training a model using a GPU is around five times slower than using a CPU
D. Training a model using a GPU provides more accurate results

Answer: A

Explanation:
In the context of UiPath Cloud Platform, training a machine learning (ML) model using a GPU (Graphics Processing Unit) is significantly faster than using a CPU (Central Processing Unit). This is because GPUs are designed to handle parallel processing, which is highly beneficial for the matrix and vector computations required in ML model training. GPUs can perform more calculations simultaneously compared to CPUs, leading to faster training times, especially with large and complex datasets1.
The UiPath documentation specifically recommends using GPU training for large and production datasets, as CPU training is much slower and should be used sparingly, for small datasets for demo or testing purposes1. This aligns with the general understanding that for deep learning training, GPUs should be used due to their significant speed advantage over CPUs23.

NEW QUESTION # 141
......

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The Key to Success: Proper Planning and the Right UiPath UiPath-ABAv1 Exam Questions

Pass Guaranteed Quiz UiPath-ABAv1 - Updated UiPath Certified Professional Automation Business Analyst Professional v1.0 Reliable Test Braindumps

UiPath Certified Professional Automation Business Analyst Professional v1.0 Sample Questions (Q136-Q141):

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