How to Extract Data From PDFs?

In today's workplace, PDF has become the go-to file format for sharing and exchanging business data. Viewing, sharing, and printing PDF files is easy. This format is commonly used for various documents like contracts, invoices, and bank statements. Due to the importance of data processing and analysis, extracting data from PDFs has become crucial. Particularly in the financial sector, businesses and organizations need to extract data from financial documents such as invoices, bank statements, and tax forms, making it an essential part of business operations. To facilitate further data processing, the extracted data from PDFs often undergoes various processing layers, requiring the conversion of PDF files into structured formats such as CSV, Excel files, or JSON. 

 

 

Editing, parsing, or extracting data from PDF files can pose significant challenges. For example, have you tried to extract text from PDFs, extract tables from PDFs, extract images from PDFs, or make scanned PDFs searchable? In this article, we will discuss how to extract data from PDFs with 4 methods, and all the different aspects of data extraction from PDF files.

How to Extract Data From PDFs?

Method 1. Manual Data Entry

If you only have a few simple PDF documents to deal with, manually entering data using the copy-and-paste approach is the easiest and most practical way to extract information. The process is straightforward: open each PDF file, select the data or text on a specific page, copy it, and then paste it into a DOC, XLS, or CSV file.

 

While this data extraction method is easy and simple, it can be time-consuming and prone to errors.

 

• Pros:

- No need for additional data extraction software or tools.

- Suitable for small amounts of data.

 

• Cons:

- Time-consuming and labor-intensive.

- Prone to errors.

- Not suitable for large amounts of data or complex data extraction.

 

• Suitable Use Cases:

- Small amounts of data.

- Simple data extraction requirements.

- Limited budget for data extraction.

 

Alternatively, you can outsource manual data entry to one of the many data entry providers available on platforms like Upwork, Freelancer, Fiverr, and other online services. The overall workflow remains similar to the manual approach described above opening each document, selecting the relevant text, and inputting the data into a database or spreadsheet.

 

Method 2. PDF Converters

Using a PDF converter is another helpful method for extracting data from PDFs, allowing you to convert it into various formats. Common conversions include converting PDFs to Excel (XLS or XLSX), converting PDFs to CSV, or converting PDFs to JSON. Several software options, like Adobe and PDF Reader Pro, offer PDF conversion features. Additionally, you can make use of free online PDF tools such as ComPDFKit by uploading your PDF document and easily converting it into the desired format.

 

 

• Pros:

- Support diverse formats, providing flexibility in choosing the most suitable format for workflows.

- Intuitive interfaces make PDF conversion accessible even for non-professionals, streamlining the data extraction process.

 

• Cons:

- Limited customization for specific data extraction needs.

- Complex PDFs may face compatibility issues, impacting data accuracy. Users need to consider file structure and content.

- Not suitable for bulk data extraction.

 

• Suitable Use Cases:

- Simple data extraction Needs

- Limited budget for data extraction.

 

Method 3. PDF Data Extraction tools

PDF data extractors, also known as PDF table extraction tools, are software designed for extracting content from PDF documents. These documents often contain text, tables, images, and figures. PDF data extractors parse the PDF files, extract the content accurately, and convert it into digital formats such as Excel or CSV. 

 

Unlike general PDF converters that process the entire document, these tools allow selective extraction, enabling users to choose specific sections like cells, rows, columns, or tables. Technologies such as Tabula & Excalibur provide the flexibility to draw a box around a table and extract data into Excel (XLS or XLSX) or CSV. It's important to note that these tools are compatible only with native PDF files and not scanned documents, which are more commonly used.

 

• Pros:

- Accurately processes complex text, tables, and graphics for highly precise data output.

- Automates handling large PDF volumes, enhancing efficiency, and reducing manual efforts.

 

• Cons:

- Limited to native PDF files and doesn't support scanned documents.

- Requires a high level of technological knowledge.

- Limited ability to extract unstructured data.

 

• Suitable Use Cases:

- Structured PDF documents.

- Large-scale data processing.

 

Method 4. AI-powered PDF Data Extraction

Intelligent document processing solutions, such as AI-powered PDF data extraction with OCR tools like ComPDFKit, offer comprehensive solutions for extracting data from PDF documents, including scanned files. The extracted data can be output in various formats, such as JSON, XML, Excel, and CSV.

 

Alongside text information, these solutions support parsing and extracting tables, images, location, layout, and style information. Developers can utilize this extracted information for more convenient secondary development, applicable in content processing, re-publishing, data analysis, and automated content processing.

 

• Pros:

- Supports both native and scanned PDF documents.

- Capable of extracting data from semi-structured and unstructured documents.

- High accuracy and precision with Document AI technology.

- Can handle multiple languages.

 

• Cons:

- Requires a high level of technological knowledge.

- Demands significant data training and development to ensure accuracy.

 

• Suitable Use Cases:

- Financial documents, such as bank statements and invoices.

- Legal documents, such as contracts.

- Educational documents, like papers.

- Government documents, such as tax forms and permits.

- Healthcare documents, including medical records and insurance claims.

- Human resources documents, such as resumes and employee onboarding forms.

 

Solutions for PDF Data Extraction by ComPDFKit

1. PDF Data Extraction SDK

ComPDFKit provides PDF data extraction SDK for Windows, Android, iOS, and Mac platforms, supporting various languages like C++, Java, Python, and PHP. Developers can seamlessly integrate the SDK into programs or systems like EPR, CEM, or RPA. It allows direct output of extracted data in various forms or saving it in corresponding formats for subsequent development.

 

2. ComPDFKit PDF Extract API

ComPDFKit offers a PDF extract API following the RESTful API standard, enabling developers to access the data extraction interface quickly. It provides a faster and more flexible way to utilize services from any platform with high scalability and reliability. ComPDFKit API simplifies document upload, processing, and file download workflows, including data extraction functions. Sign up now to enjoy 1000 free API calls per month.

 

3. ComPDFKit Processor for PDF Data Extraction

ComPDFKit Processor for Linux is an SDK designed for converting PDF files on the Linux platform. It equips developers with a robust set of APIs, including data extraction functions, enabling quick integration of PDF functionalities into any Linux application. With a focus on high security, it ensures the protection of your data while extracting content from PDFs securely.

 

The Case for Extracting Data from PDFs

 

 

In today's digital age, where vast amounts of information are stored in PDF documents, extracting valuable data becomes essential for streamlined operations, analysis, and decision-making. Several compelling cases underscore the importance of extracting data from PDFs:

 

1. Financial Efficiency:

• Scenario: Businesses often receive financial statements, invoices, and bank statements in PDF format.
• Case: Extracting financial data from PDFs allows for efficient processing, budgeting, and analysis. It enables timely financial reporting, aiding in strategic decision-making.

 

2. Legal Compliance:

• Scenario: Legal contracts and agreements are frequently exchanged in PDF format.
• Case: Extracting relevant information from legal documents ensures compliance, facilitates contract management, and supports legal teams in navigating and understanding critical terms.

 

3. Educational Documentation:

• Scenario: Educational institutions handle various documents, including research papers and examination results, often in PDF form.
• Case: Extracting data from academic documents streamlines record-keeping, enhances accessibility, and supports educational analysis, contributing to improved learning outcomes.

 

4. Government Processes:

• Scenario: Government agencies deal with numerous forms, permits, and reports in PDF format.
• Case: Extracting data from government documents enhances administrative efficiency, enables data-driven policymaking, and improves public service delivery.

 

5. Healthcare Management:

• Scenario: Medical records, insurance claims, and research studies are commonly stored as PDFs in healthcare.
• Case: Extracting data from healthcare documents enhances patient care coordination, supports medical research, and ensures accurate billing and insurance processing.

 

6. Human Resources Optimization:

• Scenario: Resumes, employee onboarding forms, and HR documents are often shared in PDF format.
• Case: Extracting data from HR documents aids in talent acquisition, facilitates personnel management, and contributes to strategic workforce planning.

 

In each of these scenarios, extracting data from PDFs not only improves efficiency but also unlocks the potential for data analysis, compliance, and informed decision-making across various industries and sectors. Whether in finance, law, education, government, healthcare, or human resources, the ability to extract valuable insights from PDFs is a critical component of modern information management.

 

What Data is Included in a PDF Document?

The types of data extraction in PDF documents encompass various categories, including text, tables, images, page data, formulas, code, and more.

 

•  Text Data: Text data is the most common type in PDFs, including words, numbers, lines, paragraphs, and symbols. It can be formatted with fonts, colors, and sizes. ComPDFKit's PDF extract API ensures quick and accurate extraction of text data.

•  Table Data: Tables organize and display data in rows and columns, typically containing text, numbers, rows, cells, and headers.

•  Image Data: Image data comprises photos, diagrams, logos, and other visual content, either embedded in the PDF or linked to an external file.

•  Page Data: Page data provides information about the physical layout, including page titles, lists, header/footer details, and page numbers.

•  Others: PDFs may also include formulae, code, annotations, and additional data types.

 

The diversity of these data types enables versatile information extraction from PDF documents, meeting the needs of a wide range of application scenarios. Utilize ComPDFKit for efficient and accurate data extraction from PDFs.

 

Challenges in PDF Data Extraction

Extracting data from PDFs presents several challenges that need to be addressed:

 

• Non-Structured PDFs: PDF files are commonly created without a structured format, leading to difficulties in accurate content extraction. Unstructured data, coupled with variations in formatting like font sizes, styles, colors, as well as the presence of tables, images, and charts, makes consistent and accurate data extraction challenging.
• Scanned Documents: Poor-quality document scans further complicate content extraction. Some PDFs consist of scanned document images, necessitating the use of Optical Character Recognition (OCR) technology to convert images to text for data extraction. OCR accuracy can vary based on scan quality and language.
• Complex Layouts: PDFs with intricate layouts pose additional challenges. Complex layouts often require advanced techniques, such as OCR technology, to accurately extract data. The accuracy of OCR depends on the quality of the scan and the language used.
• Large Volumes of Data: Handling large volumes of data within PDFs can be time-consuming and challenging for manual extraction processes. Efficient and reliable software is essential to streamline the extraction process and ensure accuracy.

 

To overcome these challenges, utilizing dependable software is crucial. ComPDFKit offers PDF extraction solutions, enabling easy and flawless content extraction from PDF files.

 

Conclusion

In this article, we've outlined four methods for PDF data extraction. Manual data entry is suitable for smaller volumes, PDF converters offer flexibility, and PDF extractor tools excel in structured data. For versatile and precise extraction, AI-powered solutions like ComPDFKit with OCR technology stand out. Each method has its strengths, and the choice depends on the task at hand. 

 

ComPDFKit provides a comprehensive solution with its SDK, API, and Processor, ensuring efficient and accurate PDF data extraction across various scenarios. Contact us now to unlock the potential within your PDF documents and streamline your information management.