PDF to Excel
Convert PDF to Excel online
Drop your file here or
Upload from your device
Upload from Google Drive
Upload from DropBox
Upload from Web address (URL)
Max file size: 128 MB
Your files are safe !
We use the best encryption methods to protect your data.
All documents are automatically deleted from our servers after 30 minutes.
If you prefer, you can delete your file manually right after processing by clicking the bin icon.
How to convert an PDF to Excel document online:
- To start, drop your PDF file or upload it from your device or your cloud storage service.
- Our tool will automatically start to convert the file.
- Download the converted Excel file to your computer or save it directly to your cloud storage service.
Did you know?
Any document that does not have a predefined data model or is not organized in a predefined way contains unstructured data. This represents about 90% of all electronic documents generated, including PDF files, whether scanned (image PDF) or not (native PDF). Conversely, Excel files are structured by definition, as their information is organized in a table format. The objective of PDF to Excel conversion is to convert unstructured data into a structured document while maintaining the same visual and logical appearance.
The main issue is that PDF files can contain a wide variety of elements, including text, images, and graphics, making it difficult to extract and convert to an Excel spreadsheet. Even tables, the most obvious use case of PDF conversion to Excel, can be challenging to convert. For example, converting a table with merged cells, complex formatting, or partial outline can result in errors or data loss.
We can use many different tools and software applications to convert PDF files to Excel format; not all are equally effective. The conversion quality depends on the PDF file's complexity, the tables' formatting, and, most importantly, the specific tools and techniques used to perform the conversion.
The main issue is that PDF files can contain a wide variety of elements, including text, images, and graphics, making it difficult to extract and convert to an Excel spreadsheet. Even tables, the most obvious use case of PDF conversion to Excel, can be challenging to convert. For example, converting a table with merged cells, complex formatting, or partial outline can result in errors or data loss.
We can use many different tools and software applications to convert PDF files to Excel format; not all are equally effective. The conversion quality depends on the PDF file's complexity, the tables' formatting, and, most importantly, the specific tools and techniques used to perform the conversion.
Many AI-based technologies can help with converting PDF files to Excel.
Optical Character Recognition (OCR): an AI-powered OCR engine can recognize and extract text from scanned PDF files or PDFs within PDF files. AI technologies are beneficial for extracting text from complex layouts, such as tables, charts, graphics, and images, especially on low-quality scanned documents.
Machine Learning (ML): ML algorithms can be trained to recognize patterns and structures within PDF files, such as tables or forms, and convert them to Excel format.
Key-Value Pair (KVP): KVP extraction is a technique used in data extraction and natural language processing (NLP) that involves identifying and extracting specific types of data, such as names, addresses, or dates.
Document Layout Analysis (DLA): DLA identifies and categorizes regions on a document. It implies a geometric analysis of tables, pictures, equations, and barcodes and a logical layout analysis (paragraphs, lines, words, characters) of the document.
Optical Character Recognition (OCR): an AI-powered OCR engine can recognize and extract text from scanned PDF files or PDFs within PDF files. AI technologies are beneficial for extracting text from complex layouts, such as tables, charts, graphics, and images, especially on low-quality scanned documents.
Machine Learning (ML): ML algorithms can be trained to recognize patterns and structures within PDF files, such as tables or forms, and convert them to Excel format.
Key-Value Pair (KVP): KVP extraction is a technique used in data extraction and natural language processing (NLP) that involves identifying and extracting specific types of data, such as names, addresses, or dates.
Document Layout Analysis (DLA): DLA identifies and categorizes regions on a document. It implies a geometric analysis of tables, pictures, equations, and barcodes and a logical layout analysis (paragraphs, lines, words, characters) of the document.