The article provides a comprehensive guide on converting information from scanned PDFs to Excel through various techniques, highlighting the challenges and solutions in this process. With the exponential growth of data, PDFs have become a prevalent format for storing text-related data, yet extracting information from them into Excel remains a complex task due to the lack of inherent table structures in PDFs. The guide explores methods such as Optical Character Recognition (OCR) and Deep Learning for automating the extraction process, emphasizing the importance of identifying electronically generated versus scanned PDFs. It reviews tools like Nanonets, EasePDF, and Adobe Acrobat, discussing their advantages and limitations in automating PDF to Excel conversion, and outlines business benefits such as improved efficiency and data integration. The article also addresses common issues like algorithm selection and post-processing challenges while offering insights into building robust deep learning pipelines for this conversion task.