What are the UiPath Action Center action statuses?
Correct Answer: D
The valid Action Center statuses are: Unassigned: The action is not assigned to any user. Pending: The action is assigned and awaiting user response. Reference: UiPath Action Center
Question 2
Having the taxonomy in a file, shared and updated across multiple projects, what is the most convenient way to load it in a UiPath Studio project?
Correct Answer: C
Reference: UiPath Load Taxonomy Activity
Question 3
What can be done in the Reports section of the dataset navigation bar in UiPath Communication Mining?
Correct Answer: C
Reference: UiPath Communication Mining Reports
Question 4
Which log level in UiPath provides the most detailed information about the execution of activities?
Correct Answer: A
In UiPath, the Verbose log level offers the most detailed information about the execution of activities. It logs every possible detail about the automation operations, including variable changes, function calls, and external responses. This level is particularly useful for in-depth debugging and analysis. UiPath Documentation The hierarchy of log levels in ascending order of priority is as follows: Off: No logs are stored. Verbose: Logs all details about automation operations. Trace: Logs finer-grained informational events than the Debug level. Information: Logs informational messages that highlight the progress of the application. Warning: Logs potentially harmful situations. Error: Logs error events that might still allow the application to continue running. Fatal: Logs very severe error events that will presumably lead the application to abort. Therefore, setting the log level to Verbose ensures that all possible details about the execution are captured, aiding in thorough diagnostics.
Question 5
When processing a document type that comes in a high variety of layouts, what is the recommended data extraction methodology?
Correct Answer: B
Based on the classification of documents, there are two common types of data extraction methodologies: rule- based data extraction and model-based data extraction1. Rule-based data extraction targets structured documents, while model-based data extraction is used to process semi-structured and unstructured documents1. However, neither of these methods alone can handle the high variety of layouts that some document types may have. Therefore, a hybrid data extraction approach is recommended, which combines the strengths of both methods and allows for more flexibility and accuracy23. A hybrid data extraction approach can use one or more extractors, such as RegEx Based Extractor, Form Extractor, Intelligent Form Extractor, Machine Learning Extractor, or FlexiCapture Extractor, depending on the document type and the fields of interest3. The Data Extraction Scope activity in UiPath enables the configuration and execution of a hybrid data extraction methodology, by allowing the user to customize which fields are requested from each extractor, what is the minimum confidence threshold for a given data point extracted by each extractor, what is the taxonomy mapping, at field level, between the project taxonomy and the extractor's internal taxonomy (if any), and how to implement "fall-back" rules for data extraction2. References: 2: Data Extraction Overview 3: Data Extraction 1: Document Processing with Improved Data Extraction