Automate your workflow with Nanonets
Request a demo Get Started

The Portable Document Format (PDF) is the go to file format for sharing & exchanging business data. You can view, save and print PDF files with ease.

But editing, scraping/parsing or extracting data from PDF files can be a big pain.

For example, have you ever tried to extract text from PDFs, extract tables from PDFs or make a flat PDF searchable?

PDF → Data
Extract data from PDF 
a frustrated Dwight from The Office
Giphy

Challenges in PDF data extraction

Data extraction from PDFs is crucial for reorganizing data according to your own requirements.

In other document formats, such as DOC, XLS or CSV, extracting a portion of information is pretty simple. Just edit the data or copy and paste.

But this is quite challenging to do in the case of PDFs.

Editing is impossible and copy-pasting just doesn’t maintain the original formatting & order - try extracting tables from a PDF!

When handling PDF data extraction in bulk, these issues can cause errors, delays or cost overruns that could seriously impact your bottomline!

Fortunately, there are solutions like Nanonets, that can extract data from PDF documents efficiently.

Let's look at the 5 most popular ways in which businesses extract data from PDFs.

5 ways to extract data from PDFs

Here are 5 different ways to extract data from PDF in an increasing order of efficiency and accuracy:


Need a smart solution for image to text, PDF to table, PDF to text, or PDF page extraction? Check out Nanonets' pre-trained data extraction AI for bank statements, invoices, customer orders, Purchase Orders, receipts, passports, driver's licenses & or any tabular data!

Automated data extraction using Nanonets

Copy and paste

copy & paste gif
Giphy

A copy-and-paste approach is the most practical option when dealing with a small number of simple PDF documents.

  • Open each PDF file
  • Select a portion of data or text on a particular page or set of pages
  • Copy the selected information
  • Paste the copied information on a DOC, XLS or CSV file
💡
This simple approach often results in data extraction that is erratic & error-prone. You will have to spend a considerable amount of time to reorganise the extracted information in a meaningful way.

Outsourcing manual data entry

outsourcing manual data entry
Giphy

Handling manual data extraction from PDFs in-house for a large number of documents might become unsustainable and prohibitively expensive in the long run.

Outsourcing manual data entry is an obvious alternative that is both cheap and quick.

Online services like Upwork, Freelancer, Hubstaff Talent, Fiverr, and other similar companies have an army of data entry professionals based out of middle-income countries in South Asia, South-East Asia, and Africa.

💡
While this approach can reduce data extraction costs and delays, quality control & data security are serious concerns! Data entry automation & automated data extraction solutions are therefore becoming more popular.
gif on outsourcing
Giphy

Want to capture data from PDF documents or convert PDF to Excel? Check out Nanonets' PDF scraper or PDF parser to scrape PDF data or parse PDFs at scale!

A super-happy Nanonets user

PDF converters

PDF converters are an obvious choice for those concerned about data quality & data security.

PDF converters allow data extraction to be managed in-house while being fast and efficient. PDF converters are available as software, web-based online solutions and even mobile apps.

PDFs are most commonly converted to Excel (XLS or XLSX) or converted to CSV formats as they present tables in a neat way; PDF to XML converters are also popular.

Simply upload the PDF document and convert it into a format of your choice.

Here are some top PDF convertor tools/software:

💡
PDF converters are not equipped to handle documents at scale. Bulk data extraction is just not possible and one has to repeat the data extraction process for each document, one at a time!

PDF data extractor or PDF table extraction tools

table extracted from a PDF document

Very often, PDF documents contain tables along with text, images and figures. In many cases, the data of interest usually lies in the tables.

PDF converters process the entire PDF document, without providing an option to limit the data extraction to a specific section in a PDF (such as specific cells, rows, columns or even tables).

PDF to table extraction tools or PDF data extractors do just that.

PDF table extraction tools/technologies such as Tabula & Excalibur allow you to select sections within a PDF by drawing a box around a table and then extracting the data into an Excel file (XLS or XLSX) or CSV.

💡
While PDF to table tools give reasonably efficient results, you might require development effort or in-house experts to leverage the underlying technologies powering these tools to fit your own use cases. Additionally such PDF data extraction tools only work with native PDF files and not scanned documents (which are more commonly used)!

If your PDFs deal with invoices, customer orders, receipts, claim forms, passports, or driver's licenses, check out Nanonets' PDF scraper or PDF data extractor to capture data from PDF documents.

Nanonets data extractor
Nanonets data extractor in action!

Automated PDF data extraction

Intelligent document processing solutions or AI-based OCR software like Nanonets provide the most holistic solution to the problem of extracting data from PDFs or extracting text from images.

They are dependable, efficient, extremely fast, competitively priced, secure & scalable. They can also handle scanned documents as well as native PDF files.

Such automated PDF data extractors employ a combination of AI, ML/DL, OCR, RPA, pattern recognition, text recognition and other techniques to process documents accurately at scale.

Automated PDF data extraction tools, like Nanonets, use machine learning to provide pre-trained extractors that can handle specific types of documents and unstructured data.

Here's a quick demo of Nanonets' pre-trained table extractor:

Nanonets' pre-trained Table Extractor model

Apart from using pre-trained extraction models, you can also build your own custom AI to extract data from different documents. Here's how:

  • Collect a batch of sample documents to serve as a training set
  • Train the automated software to extract the data according to your needs
  • Test and verify
  • Run the trained software on real documents
  • Process the extracted data

How to Train your own OCR Model with Nanonets


Nanonets has many interesting use cases that could optimize your business performance, save costs, and boost growth. Find out how Nanonets' use cases can apply to your product.


Update June 2023: this post was originally published in Oct 2020 and has since been updated numerous times.

Here's a slide summarizing the findings in this article. Here's an alternate version of this post.


If you're tired of the tedious task of manually extracting pages from PDFs, it's time to explore the power of Workflow Automation with Nanonets. Imagine a world where your PDF management becomes a breeze, thanks to our platform that lets you automate these tasks with ease. With seamless app integrations, you can connect your current tools and transform your document handling into an efficient, error-free process. Start building your custom workflows in minutes and free yourself from the monotonous clicks and drags of yesterday.

Learn More