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

The correct order of steps in the Document Understanding processing flow for a generic document is as follows:

1.Digitize: The first step involves digitizing the document to turn it into machine-readable content.

2.Classify: Next, the document is classified to determine the types of documents found within the digitized file.

3.Data Extraction: After classification, the relevant data is extracted from the document.

4.Data Export: Finally, the extracted data is exported for consumption1.

This sequence ensures that the document is first made readable for the system, then categorized, followed by data extraction, and concluding with the export of the data.

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.

The main goal of conducting a feasibility study during the business analysis phase for RPA is to evaluate the technical feasibility of the automation solution. This involves assessing whether the processes in question can be automated using RPA technology, and if so, how effectively. It includes examining the nature of each step and activity performed by the operation user, validating whether the process is rule-based or requires additional decisions or analysis, and determining the complexity, volume of transactions, technology landscape, development efforts, data size, and information flow. The feasibility study ensures that the process is suitable for automation and helps in identifying any manual interventions that might be needed during the process1.