PDF (Portable Document Format) is a file format that is used to present and exchange documents reliably, independent of software, hardware, or operating system. PDF was invented by Adobe and is now an open standard maintained by ISO. Nowadays PDF files are compatible and generated by a majority of software applications. PDF documents can contain all types of media in them like links, input form fields, video and can be signed electronically.
It depends on the type of pdf file which can be either searchable or image-based.
That depends on the volume, type (image/searchable), and the amount of text/data you need to process from each pdf file;
Single/Multipage low volume:
To be honest, if we are talking about a few pdf files per day, it’s not a huge challenge to manually extract data and key in that data in your line-of-business system. So it won’t make any sense to introduce automation, as it is going to be overkill.
Single/Multipage high volume:
In this case, the data entry operator has to individually open each pdf file, locate the data fields from the correct pages, then copy/paste data in case of searchable pdf. It would get harder for the operator to manually type in the text in the destination system when the pdf is not searchable. Formatting the dates, numbers during the data entry process would further make it more time-consuming and error-prone.
So using a modern data capture cloud-based software like DocAcquire to automate the data entry process would yield a huge ROI to any business.
If you simply want to convert a pdf file to any other standard format then you can use the following tools;
If your requirement is to extract only key (specific) data fields from pdf files. An example would be Invoice Date, Invoice Number, Tax, Total from a Supplier Invoice. If you are also looking to store extracted data in a structured format like Excel, Microsoft SQL Server, Microsoft Sharepoint, or in your business system.
If the above is the case, you are looking for an “automated data capture software” which is based on Optical Character Recognition (OCR) and Machine Learning.
The majority of modern automated data capture platforms are built on a workflow system. A typical document extraction workflow goes through the following stages;
Import:
A variety of file types like pdf files and scanned images can be uploaded to data capture software. These documents can come from an array of sources;
DocAcquire has a strong integrations engine that enables to import of documents from a wide variety of sources.
Classify:
Every document is classified based on its layout and content. Once classified, the document is ready for the next stage of data extraction. The system marks the document as Unclassified if it can’t recognize the document layout and content. In such a case, the document needs to be trained.
Extract:
Once the document is classified, based on the initial training the required data/fields are extracted. Once the data extraction is done, the document is sent for the next stage of the workflow for verification.
Verify:
This is the stage where a human operator comes in and verifies the extracted data, fixes any potential errors, and marks the document Ready for the next stage for Export. This is normally a less time-consuming process as the majority of the heavy lifting is already done by the data extraction software. The involvement of a human to verify the extracted data guarantees the maximum accuracy of data after data extraction.
Export:
At this stage, a document extraction is already done and data is verified by a human operator, the data is then exported to the selected destination.
There are many ways you can extract data from a PDF file. But the approach entirely depends on your use case or requirement.
If you are after the full text on all the pages of PDF. That is way simple and straightforward.
Here are a few reasons why you want to use this approach;
If you want to extract specific data points from a PDF document then that a different ball game – The complexity increases – especially when the documents get very unstructured like contracts, letters, etc.
What is Transactional data? When a company does business with some other organization which involves the exchange of products or services, and during this process data that is captured is called transactional data.
For example, when a product is sold, the company that sells it raise an invoice. The invoice contains the required financial data about which product(s) were sold, how many, and for how much the value. Some other transactional documents include Purchase Orders, Proof Of Delivery, Bill of Lading, etc.
Having documents that have fixed rules in the placement of individual data points (like, invoice number, invoice data, totals, etc.) is less complicated compared to other documents where a particular data point (like invoice number) is not fixed to one location, and it gets more complex when the PDF is scanned which is of poor quality, skewed and the data point can exist on any random page of a PDF document. It gets more tricky when that data point needs to be extracted from dense and unstructured text.
DocAcquire is a modern cloud-based data capture software that can extract data from a variety of file formats like pdf, png, jpeg, and tiff. By default, DocAcquire uses the OCR engine called AWS Textract to read the text from documents.
DocAcquire Key features for pdf data extraction
DocAcquire’s – Cognitive Invoice is a platform built on deep learning which makes invoice data extraction a breeze. Here is a quick sneak peek of the platform, you can see how easier is it to get up and running – there’s no need to build and maintain templates.
I hope you found this blog helpful and if you have any specific questions please Contact Us and we would be more than happy to answer any of your questions.
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