Why is PDF data extraction important?
PDFs are everywhere. From invoices to reports, they’re a standard way to share information. But PDFs aren’t always easy to work with, especially when you need to pull data out of them.
Manually copying and pasting data from PDFs is slow and opens the door to errors. This is where data extraction comes in.
Data extraction is the process of turning the unstructured content of a PDF into something you can actually use. It transforms that data into a format that you can analyze, report on, and integrate with other systems.
In this article, we’ll look at different ways to approach the extraction of data from PDF documents, from manual methods to automated tools. We’ll also highlight why automation is key when you’re dealing with large volumes of data.
Understanding data extraction from PDFs: challenges and approaches
PDFs are great for visually presenting information, but extracting data from them can be tricky. Here’s why, along with a look at some common extraction methods.
The challenges of PDF data extraction
PDFs weren’t really designed to be data sources, so there are a few reasons that getting information out of them can be difficult:
- PDFs can contain text as images, which makes it hard to extract the text directly.
- PDFs can have complex layouts, tables, and formatting that make data extraction more challenging.
It’s also important to understand the difference between native and scanned PDFs. Native PDFs contain selectable text, whereas scanned PDFs are basically images. To extract text from a scanned PDF, you’ll need to use OCR (Optical Character Recognition) software.
Different approaches to PDF data extraction
There are two main ways to extract data from PDFs: manually or automatically.
- Manual data extraction: This involves copying and pasting data from PDFs into another application. This is fine for small jobs, but it’s not efficient or accurate when you’re working with a lot of documents.
- Automated data extraction: This involves using software to automatically extract data from PDFs. This is faster, more accurate, and more scalable than manual methods.
Manual PDF Data Extraction: When and How
Sometimes, the simplest way to extract data from a PDF is to do it yourself. Here are a few manual methods:
- Copying and Pasting with Microsoft Word: If you can open your PDF in Microsoft Word, you might be able to copy the data you need and paste it into Excel or another application.
- PDF Converters: You can convert your PDF into a different format, like Excel or CSV. There are many online converters and desktop software options that can do this.
- Table Extraction Tools: These tools specialize in extracting data arranged in tables within PDFs. You might need to tweak the results to make sure the extraction is accurate.
- Direct Import in Excel: Some Excel versions let you import data directly from PDFs. This works best with simple PDFs that have clearly defined tables.
Automated PDF Data Extraction: Tools and Techniques
If you’re dealing with a lot of PDFs and need to pull information from them regularly, you’ll probably want to automate the data extraction process. Here are a few tools and techniques that can help.
Intelligent Document Processing (IDP) Platforms
IDP platforms use artificial intelligence (AI) and machine learning to automate data extraction, no matter what type of document you’re working with. They’re designed to work with a range of file types and formats and offer features like OCR, pattern recognition, and data validation.
Key Features of Automated Data Extraction Tools
- OCR (Optical Character Recognition): This converts scanned images and PDFs into text your computer can read.
- Zonal OCR: Zonal OCR lets you select specific areas of a document for data extraction.
- Pattern Recognition: This finds and extracts data based on patterns you define.
- Template Creation: You can create templates for specific document types, so the software knows exactly where to look for the data you need.
- Data Validation: This feature makes sure the extracted data is accurate and consistent.
Examples of Automated PDF Data Extraction Tools
Here are a couple of examples of tools that can help you automatically extract data from PDFs:
Docparser
Docparser extracts data from different types of documents using OCR and pattern recognition. It supports multiple output formats and integrations and even offers pre-built templates for common documents like HR forms, shipping orders, and product lists.
Klippa DocHorizon
Klippa DocHorizon is a fully automated solution for extracting data from PDFs into Excel spreadsheets. It uses AI to automate the entire process and supports multiple document types, formats, and integrations.
How to automatically extract PDF data into Excel with Klippa DocHorizon
Klippa DocHorizon is an automated tool that can extract data from PDFs and convert it to Excel. Here’s how to use it:
- Set up Klippa DocHorizon. Create an account and log in.
- Connect to data sources. You can connect Klippa DocHorizon to external sources like Google Drive, Dropbox, or your email accounts. Then, configure the platform to watch those sources for new PDFs.
- Configure data extraction rules. This is where you tell the software what to pull from the PDF.
- Start by defining the data fields you want to grab, such as invoice number, date, and amount.
- Use the visual editor to map those fields to specific spots in the PDF.
- If you want to process invoices and similar documents, choose the “Financial model” preset.
- You can also create a custom preset for your specific needs.
- Test and validate. Before you process lots of PDFs, test the extraction process with a sample document and make sure the data comes out correctly. Verify that the first row contains headers. Test every step in the Klippa DocHorizon workflow.
- Export data to Excel. Finally, tell the platform to automatically send the extracted data to Excel in your preferred format (.xlsx, .csv, etc.).
Choosing the Right PDF Data Extraction Method
So, how do you pick the right way to extract data from PDFs? Here are some things to think about:
- How many documents do you have? If you only need to pull info from a few PDFs (dozens), manual extraction can work. But if you have hundreds or thousands, you’ll need to automate.
- How complicated are the PDFs? Basic tools can handle PDFs with a simple layout. But you’ll need something more advanced if your PDFs have tables, images, or different layouts from page to page.
- How accurate does the data need to be? Manual extraction opens the door to human error. Automated extraction is generally more accurate, especially if you have someone double-check the results.
- What’s your budget? Manual extraction is “free,” but it eats up time. Automated tools require a subscription or license.
- What’s your technical know-how? You only need basic computer skills to extract manually. But automated tools may require some tech skills to set up and configure.
Wrapping Up
Extracting data from PDFs is essential for making the most of the information locked inside those documents. When you can pull the data out of PDFs, businesses can automate time-consuming tasks, work more efficiently, and make better decisions about business strategy.
Whether you extract data manually or use an automated system depends on your particular needs and budget. If you only have a few PDFs and the documents are relatively simple, you can probably extract the data yourself. But if you have a large number of PDFs, the documents are complex, and you need a high level of accuracy, automation is the best choice.
With the right tools and techniques, you can turn PDFs from data dead ends into valuable assets. Intelligent Document Processing (IDP) platforms are one of the best ways to automate data extraction from PDFs.