Extract Data From PDF Documents Online

Extract Data From PDF Documents Online

PDF is one of the most preferred file formats for exchanging important data between organizations. Organizations such as insurance and lending rely heavily on the PDF file format to organize consumer data and facts. This collected data has to pass through various layers of processing, with PDF files converted into various structured formats such as CSV, Excel files, or JSON before processing. In this 
blog, we will discuss different ways to extract text from PDF files and how to automate the complete workflow.

The Finest Manner to Extract Data From PDF to Excel

At work, you probably come across PDF files (almost) every day. Those files usually have data we want to use elsewhere, for instance, to perform computations in an Excel spreadsheet.

So accordingly, we are required to extract the data from the PDF file. Copy the data into Excel and begin computing; you only need to do this for one or two PDF files. When you have to go through hundreds of documents, it becomes time-consuming to copy and paste. So it's easy to explore smarter ways to extract data from PDF to Excel. That's what we're endeavouring to do in this article for you.
We will first discuss different ways to extract data from PDF to Excel, then we will discuss them thoroughly, and finally, how you and your business can excel (with pun intended) in the intelligent data processing. Presenting an automated solution that will help you become a better person!

Portable Document Format (PDF) is the ideal file format for sharing and exchanging business data. You can effortlessly view, preserve and print PDF files for a long duration. However, editing, scraping/parsing, or extracting data from PDF files is very cumbersome. For example, have you ever tried extracting text from a PDF, extracting a table from a PDF, or making a flat PDF searchable? 

Why Is It a Question of Extracting Data From PDF Files?

There are several reasons why extracting data from PDF can be difficult. There are many reasons for this, ranging from technical issues to actual workflow impediments. First of all, many PDF files are scanned images. These documents are easily readable by humans, but computers cannot understand scanned image text without first applying a method called Optical Character Recognition (OCR).
Once the document has gone through an OCR PDF scanner and contains text data (not just images), you can manually copy and paste some of the text. This method is cumbersome, error-prone, uneasy to implement, and not scalable. Opening each PDF document individually, finding the text you're looking for, selecting that text, and copying it to another software is too time-consuming.

Why Is It Essential to Extract Data From PDF Files?

Corporations exchange a ton of data and knowledge with each other through PDF files

• Invoices
• Purchase orders
• Packing lists
• Forms
• Bank statements
• Pay stubs &
• Contracts

Most of these records are developed digitally utilizing some software and conveyed via email as PDF files. So the issue occurs when the receiving company needs to finish these documents digitally. The only choices people and companies are left with are manually copying text from pdf files and pasting it to MS Word or Excel spreadsheet and carrying it from there. The procedure doesn't work when the pdf comes in the form of a scanned document. Even if it works, the method is not completely certain and is inclined to all sorts of errors. That's why corporations often have to outsource record processing or establish automated document data capture software within their premises.

What Types of Data Extracts Are There?

Now that you've seen the benefits of data extraction, how is it commonly applied? The first step in using data extraction to your advantage is recognizing areas that will benefit from the procedure. The following types of data are then typically extracted:

• Bank Statements: Bank statements are designed to be secure and difficult to identify and organize. The file names are usually random numbers, so when digitized they are all in one place. Also, since bank statements contain important information, document redundancy is necessary. Scanning and extracting data is important for the redundancy and protection of the data itself.
• Financial data: In addition to bank statements, financial data helps you organize your business. From selling and purchasing costs to competitor pricing, data helps companies track performance, improve inefficiencies, and make strategic plans to close business gaps.
• Customer Data: This data assists enterprises analyze and comprehend their consumers. This includes information such as your name, phone number, email address, identification number, purchase history, social media activity, and web searches. You can extract all this information and use it to build your database.
• Performance data: This data includes information about tasks or operations within your organization. This is, for example, all information about the company's logistics, such as customer feedback and shipping costs.

Different Forms to Extract Data From PDF to Excel Sheet

There are multiple distinct forms to extract data from PDF to Excel, but these are the most typical methods to do so:

• Copy and paste
• PDF converters
• PDF table extraction tools
• Direct import in Excel
• Outsourcing manual data entry
• Automated PDF data extraction

Copy and Paste

The most fundamental method of extracting data from a PDF file to Excel is simply copying and pasting data. Which consists of opening the file, selecting the appropriate text, and copying and pasting it into an Excel sheet. This approach may be the most suitable choice if you only have a rare PDF file. But once you have thousands of them, this will most probably result in data entry mistakes and take a lot of your time. 
Likewise, it is an incredibly tiresome procedure.

Copy and Paste With Microsoft Word

Copy-pasting data performs well in most circumstances, but occasionally it doesn’t provide you with the expected results. For instance, it’s nearly inconceivable to nicely copy and paste an entire table, including its configuration and data, from PDF to Excel. In such a case, you have to open the PDF file in Word, and then copy/paste it to an Excel sheet. To make 

You need Microsoft Word 2013 or a later version to use this procedure. Then you need to comply with the steps:

1. Open PDF files in Microsoft Word
2. Emulate the content from the Word file and paste it into an Excel spreadsheet.

While this approach delivers considerable outcomes, it won’t manage complex elements, such as more complicated tables with cell spacing. Apart from this, it’s not feasible to extract data in the majority as you have to open every PDF file one by one. 

PDF Converters

 If you frequently need to extract data from PDF files to Excel, a PDF converter is a good choice. PDF Converter can convert PDF files to Excel files in seconds. The process is pretty easy. Select the PDF file you want to convert, upload the file to the PDF converter and click the Convert button. The file can be converted to an Excel file or any other desired format. Some PDF converters also let you edit the text and images directly in the PDF file and then export them to an Excel spreadsheet. 

There are many PDF converters out there, but here are some of the best PDF converters:

• Adobe Acrobat
• Cometdocs
• Able2Extract
• PDFelement
• SimplyPDF

The PDF converter can extract data efficiently and quickly, but it cannot extract enormous amounts of data. PDF files are required to be uploaded individually. Also, the PDF converter only works with native PDF documents. This also means that if you save a scanned paper document as a PDF, you cannot extract data from it.

PDF Table Extraction Tools

There can be periods when you only like to extract data from a particular table. A PDF converter can be your major option, but it fails to extract the data accurately. Fortunately, different mechanisms can be of excellent help: table extraction tools. You can discover the five finest table extraction mechanisms downward:

• Tabula
• PdfTables 
• Docparser
• Camelot 
• Excalibur

Most of these tools let you draw a frame around the table and extract the data to Excel or other formats. Note that the table extractor tool works only with native PDF files. Most of these tools only allow you to upload one file at a time and you have to select the spreadsheet you want to convert. Additionally, in-house knowledge may be required to fine-tune the table extractor to work for your particular use case. In short, using tools to extract PDF spreadsheets is still labour-intensive and not an ideal solution.

Direct Import in Excel

Importing a PDF straight into Excel and extracting data from it can likewise be a suitable choice. Let's take a look at the following steps for a better understanding:

1. Open the Excel spreadsheet
2. From display Choose the tab Data > Get data > From file > From PDF
3. Select the PDF file and select Import
4. Then you will notice a Navigator forum with the tables and pages in your PDF, along with a preview option
5. Select a table and click Load. The table is imported into an Excel sheet.

This technique is fully efficient with specific data. Complicated data or tables with multiple pages will result in annoying errors in the formatting.

Outsourcing Manual Data Entry

Maintaining manual data extraction from PDFs for large numbers of documents in-house can be prohibitive and out of reach in the long run. Outsourcing manual data entry is a cheap, fast, and obvious option. We can see that Online services such as Upwork, Freelancer, Hubstaff Talent, and Fiverr have large numbers of data entry professionals from middle-income countries in South Asia, Southeast Asia, and Africa.

Automated PDF Data Extraction

Intelligent document processing solutions like Nanonets and AI-based OCR software offer the most comprehensive solution to the problem of extracting data from PDFs and extracting text from images. They are reliable, efficient, blazingly fast, cheap, secure, and scalable. Scanned documents and native PDF files can also be processed. Such automated PDF data extractors use a combination of AI, ML/DL, OCR, RPA, pattern recognition, text recognition, and other techniques to accurately extract large amounts of data. Automated PDF statistics extraction equipment like Nanonets uses machine learning to offer pre-educated extractors which can deal with unique sorts of documents.

Extract Data From PDF to Excel Using an Automated Solution

The most accurate and fastest way to extract data from PDF files in Excel is to use an automated data extraction solution. Automated data extraction solutions use text recognition technology called optical character recognition (OCR) to accurately extract data from documents. An accurate instance of such an automatic explanation is Klippa Doc Horizon. It can process large amounts of native and non-native PDFs in seconds. It can also be easily integrated into existing software using Klippa's OCR API. Here's an overview of how this technology works:

1. Upload the PDF document to the API – First, you need to publish the PDF file to the API. You can do this through our mobile or a net application.
2. Pre-processing the PDF file – In the second stage, the document’s components enhance to improve recognition accuracy.
3. Transforming the PDF to text – Then, the software will alter the PDF document into a text document. The PDF data is extracted directly, but still unstructured at this point.
4. Converting to Excel – In the last stage, the Klippa parser converts the text file into structured data in this circumstance, you can readily start using the data from the PDF file in Excel.

By following these measures, Klippa DocHorizon can extract data from basically any PDF file and will be able to save time, decrease mistakes and reduce costs.

Conclusion

In this blog, we conferred the most famous approaches to extracting data from PDF to Excel. We explained their pros and cons and resembled them to several functionalities. In the end, it became apparent that none of them was the ideal alternative.

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