Principal Architect Intelligent Automation, USA.
Received on 12 October 2022; revised on 14 December 2022; accepted on 17 December 2022
This research paper focuses on Cognitive Robotic Process Automation (RPA), with an emphasis on how it has revolutionized the processing of unstructured data. While traditional RPA systems excel at handling structured data, the growing volume and complexity of unstructured data have necessitated more advanced solutions. Cognitive RPA integrates artificial intelligence (AI) and machine learning (ML) to enable RPA to effectively interpret and process text, images, and emails, thus extending its capabilities to unstructured data environments.
Thus, the research objectives of this paper are as follows: First, the identification of the application of cognitive RPA to the different fields of business; second, to evaluate the capability of cognitive RPA on unstructured data; and last, to determine the technologies that enable interaction on the automation. Recall the problem stated within the problem section. The problem solution is associated with the presence of RPA’s inability to handle unstructured data and how cognitive automation can help.
Last but not least, cognitive RPA is a way to transform those operations for better performance, refine business processes, and better decision-making. Given the automating tendencies, this paper will first define cognitive RPA and how it is ideal for transforming the data processing sector.
Cognitive RPA; Unstructured Data; AI; ML; NLP; OCR
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Abhaykumar Dalsaniya. Cognitive Robotic Process Automation (RPA) for Processing Unstructured Data. International Journal of Science and Research Archive, 2022, 07(02), 639–643. Article DOI: https://doi.org/10.30574/ijsra.2022.7.2.0269
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