UiPath-ABAv1 Exam Dumps : UiPath Certified Professional Automation Business Analyst Professional v1.0

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.

UiPath Automation Hub:

A platform designed to crowdsource automation ideas directly from employees.

Enables organizations to prioritize and manage these ideas to maximize ROI and align with strategic goals.

Key Benefits:

Employees can contribute automation opportunities, democratizing the identification process.

Automation Hub helps bridge the gap between business needs and technical execution.

Option Analysis:

Option A: Monitoring execution happens in Orchestrator, not Automation Hub.

Option B: While collaboration exists, the primary goal is sourcing ideas.

Option C: Automation workflows are not directly uploaded for review.

Correct Option (D): Highlights the crowdsourcing capability, a core feature of Automation Hub​​.

In the TemplateOne application provided by UiPath Process Mining, the Automation Dashboard includes the following three standard KPIs: Automation Rate, Total Manual Processing Time, and Total Manual Event Cost. These KPIs help in assessing the efficiency and cost-effectiveness of manual vs automated processes within an organization.