Unstructured Data Analysis with AI, RPA, and OCR | UiPath
Blog: UIPath.com
Tony Tzeng is Director of Product for UiPath Document Understanding at UiPath.
Cosmin Nicolae is a Product Manager at UiPath.
Unstructured data is everywhere, hiding in places like documents, audio files, videos, emails, images, and log files — the list goes on. In fact, unstructured data now accounts for roughly 80 to 90% of all data. Yet, despite its abundance and value, unstructured data remains one of the most wasted enterprise resources because companies lack the necessary tools to extract and analyze it.
This is changing, as demand is increasing for big data analytics and workflow automation — both of which require unstructured data. A growing number of businesses are leveraging a technology called optical character recognition (OCR), which makes it possible to convert print or handwritten text into machine-encoded text. As a standalone technology, OCR is somewhat limited (more on that below). Yet, through the trifecta of OCR, Robotic Process Automation (RPA) and artificial intelligence (AI), businesses can enable highly advanced levels of data processing and automation.
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