Optical Character Recognition (OCR) technologies have been a gamechanger in data extraction. At Parsel, we use OCR to analyse and identify the data in your PDFs and extract it without the need for manual guidance - just one of the many benefits of OCR data extraction.
As a concept, OCR has been around since the early 1900's, but it wasn't until the information age that it became a fully realised technology that tangibly improved the way we process data.
At Parsel, we use OCR to identify the unstructured data in your PDFs and eliminate the need for manual guidance - as discussed in our previous blog on serverless architecture. And while there are many reasons to use OCR technology for data extraction, the core benefit is clear - convenience.
However, there's still a lot of confusion about what OCR actually is and what it's used for. So, here's a few pointers from the Parsel team.
What does OCR stand for?
OCR stands for Optical Character Recognition. That's it. That's the tweet.
What is OCR technology used for?
To understand what OCR technology is used for, it helps to understand what OCR technology actually does. So, to be clear: OCR identifies characters - letters or numbers - from a source file, so they can be reproduced and assembled in the form of a new editable and structured file.
When you consider how many electronic documents - PDF, Word, Excel files etc - are produced around every day, the use cases for OCR data extraction are virtually limitless. From the Admin Assistant trying to extract purchase order information to CEOs trying to get a better understanding of their company reports. OCR plays a vital part in automating the extraction of that data.
When Parsel extracts data, OCR algorithms automatically identify unstructured data in your PDFs, before applying additional table recognition to extract and reproduce the data in its new structured and editable form. It's why Parsel's table extraction doesn't require any manual guidance.
Why automate data extraction?
It all comes back to one thing - convenience.
Previously, companies would need to employ people - sometimes entire departments - to manually extract and enter data into business systems. The drawbacks of this are obvious - it's costly, time-consuming and prone to human error.
That's why automated data extraction tools, like Parsel, exist. To make data extraction a quicker, cheaper and simpler process.
Try Parsel's best-in-class OCR data extraction
1. Upload your PDF document
Use our handy drag and drop function to upload your PDF document to Parsel (you'll need to create a free account first.)
2. Let our OCR extract your data
Now, just sit back and let Parsel's OCR table extraction do the work for you.
3. Download your data file
After a few minutes, Parsel will output your extracted data in multiple file formats, including Excel, JSON and more.
Join the many businesses that use Parsel
Unlike other apps, we've taken the hassle out of data extraction. We don't ask you to select a page range or target areas in your PDF - Parsel does all that for you. Our technology analyses, identifies and extracts your data all on its own; it's simple, fast and efficient.
And with superior accuracy born from rigorous extraction of complex financial datasets, there's far fewer issues recognising table column and row headers - meaning less time for you spent making manual corrections.
To start converting your company reports to Excel today, sign up for free here.