There is enough first-hand experience for almost every individual that PDF files are the best way to store bulky information. It’s definitely better than going around securing physical documents in files, and ensuring that they do not get lost somewhere in the archives. But even while managing data in a PDF format has eased our lives quite a bit, one cannot ignore the fact that it is still not very easy to use and manipulate data once it is converted into a PDF file. For a large percentage of users, manual retyping of data from files is the primary option to extract information from PDFs.
The bottom line is that just like Google allows us to scrape through the internet and find what we are exactly looking for, there should be a mechanism by which we can scrape through our own PDF files and extract something specific. In this article, we will be talking about PDF scrapers, how they really work, and what are the challenges users face while using traditional PDF scraping apps.
From what would have already become a little clear by now, PDF scraping refers to the process of pulling out specific parts of the data present in a PDF file automatically. When one has to use data from pre-existing records for operational purposes, manually retyping the same would not be a practical idea. This is simply because, in a professional setting, there will be huge chunks of such data that might be required at different stages.
Of course, digitized forms of the same information will always be more beneficial considering the extent of digitization in companies today. A PDF scraping software allows users to extract parts of the information stored in PDF files, and transport it to relevant databases. This finds application in sectors like banking, finance, insurance, hospitality, etc.
Information That Can Be Extracted with PDF Scrapers
● Simple Text
By specifying the data regions from which you need to pull out information, you can create your own templates for PDF scrapers. This way you can practically scrape through any text-based PDF easily and retrieve information which would be necessary for subsequent operations.
PDF Forms are commonly used by businesses to get customer feedback. Once these PDF files are obtained, the new users can selectively take out certain fields from these forms using a PDF scraper. This is a very beneficial method to obtain specific data about customer behavior and also aids in easy data analysis.
PDF scrapers allow users to pull out data from any region in the document whatsoever. Many times images are a part of PDF documents, and represent data and figures too. Any advanced PDF scraper will allow you to extract data from such images as well. Further, scanned images converted into PDF files can also be processed using good PDF scrapers. This way, documents that are originally handwritten can easily be converted into a digitally usable form.
Challenges With PDF Scraper
While there is no doubt that PDF scraping software is a breakthrough invention, it is worth pointing out that there is still a long way to go to make this an error-free operation. Challenges with existing PDF scrapers are quite significant. A very common problem is faced when users wish to scrape pdf to excel. Since the data, irrespective of its format, can easily be converted into a PDF, the reverse process is also independent of templates and formats. This means that extracting data in the exact tabulated format from a PDF, so that it can be used to prepare a new Excel sheet is very difficult for any application.
The next big challenge is that traditional PDF scrapers do not have any mechanism by which the final output can be proofread or rechecked. This means that once the rule-based conversion or extraction of data from the PDF is completed, even outputs full of errors will be presented before you. Moreover, it is certainly very difficult to pay heed to minute errors like these when you have to process data on a large scale.
Lastly, although PDF scrapers have the ability to pull out data selectively from your files, they may not be technically capable of preserving the formatting of the data as well. Ultimately, this would require human intervention to again format the information as per the original record, somewhat defeating the purpose of an automation tool.
KlearStack Solution For PDF Scraping
All these challenges that we have discussed so far have been pinch points for the developers at KlearStack for a long time. To find a tangible solution to these problems, we decided to create a state-of-the-art optical character recognition software that would change the way people screen scrape PDF. Our OCR software has been enriched with artificial intelligence capabilities, and therefore, is capable of providing error-free outputs on every use.
Further, with machine learning models being trained with diverse data sets, our optical character recognition software is capable of extracting information from any PDF file in the world. We have already provided our service to some of the leading enterprises across the globe, and are continuing our research to serve the industry in an even better way. Contact KlearStack today to book a free demo of our OCR tool.