Portable Document Format or PDFs are the most commonly used documents in today’s digitized business world. PDFs have become the universal standard for document sharing, thanks to their ease of use and flexibility.
Organizations extensively use PDFs to exchange important documents like invoices, purchase orders, contracts, forms, and more. However, a caveat of using PDFs is that it makes data extraction difficult.
Why? Because PDFs contain semi-structured or unstructured data that doesn’t have a pre-defined schema. Hence, extractingdatafrom a document via the copy-paste function doesn’t maintain the original formatting.
Why is Data Extraction from PDF Documents Important?
Data extraction allows businesses to consolidate the information trapped in PDFs to a centralized data repository for analytics and reporting.
Using the insights gathered by processing data extracted from PDF documents, businesses can optimizetheir efficiency and performance.
All in all, organizations get more control over their data.
How to Extract Data fromPDF Documents?
There are three ways to extract PDF data: manual data entry, outsourcing, and data extraction automation.
Manual Data Entry
Manual data entry is the most straightforwardway to extract data from PDFs. It simply involves opening the document, copying the desired data fields, and pasting it on an editable file like Word or Excel.
But it only works for a small volume of PDF documents — essentially, retyping information, character by character,is a costly, error-prone, and time-consuming method for extracting data at scale.
Outsourcing is a cheaper and faster alternative to resolve in-house manual data entry tasks. It involves hiring third-party agencies with data entry professionals to perform manual data entry.
These data entry agencies employ data entry professionals trained to retype data from PDF files to editable files. However, it’s still an error-prone and time-consuming approach to data extraction at scale.
Moreover, important business data is exposed to those outside the organization, leading to confidentiality and regulatory issues.
Data Extraction Automation
Automated PDF data extraction toolsoffer the most efficient way to extractdata from PDFs. These tools, also called data scraping tools, are used by enterprises to handle large-scale PDF data extraction.
The PDF data extraction automationsolutions leverage a combination of artificial intelligence (AI), machine learning, text/pattern recognition, and other techniques to extract data with great precision.
They are extremely fast, reliable, and secure, allowing enterprises to seamlessly capture data from PDF files. Data extraction automation facilitates business analytics leading to data-driven decision making.
Which PDF Data Extraction Method is the Best?
It depends on the usecase. Manual data extraction is a feasible choice if you only want to extract data from a few PDF files. But for routine document processing, you need an automated solution.
Data extraction automation is the best option — and the only practical way —to perform PDF data extraction at scale. Powered by AI, data scraping toolsallow access to the wealth of data buried inside unstructured files.
The modern data scraping tools allow users to create reusable templates for PDF data extraction, perform validation to ensure data accuracy, and design and schedule workflows to fully automate the process.
About the Author
Ammar Ali is a technology writer, editor, and researcher for Astera Software. He’s passionate about data science and strives to educate readers about modern data management solutions and business intelligence tools. He works closely with development teams to design innovative strategic solutions for solving business problems.