PDF-Based Data Extraction Made Easy with ReportMiner

Businesses have used PDF format for exchanging data because of its convenience and reliability. However, manual extraction of data from PDFs is a challenging task. Some of the commonly exchanged PDF documents include purchase orders, invoices, financial statements, and valuation reports. In this blog, we discuss how businesses can liberate important business data from PDFs with automated PDF data extraction.

Challenges of PDF Data Extraction

Many businesses find data extraction from PDF documents challenging as they are in an unstructured format. Previously, businesses relied on the IT department to perform this task, increasing the burden on IT personnel, which led to delays in data exchange.

In most cases, the requirement is to extract data not from only one, but a batch of similarly structured files. In this case, manual extraction of data from PDFs is not only time-consuming but can also lead to errors. A data extraction tool can reduce manual effort required and save time by automating extraction from PDF documents.

Since an organization receives PDF documents in different formats such as scanned PDFs, text-based PDFs, and PDF forms, a desirable data extraction solution should be able to deal with all kinds of PDFs.

How ReportMiner makes PDF-based Data Extraction Painless?

Astera offers a data extraction solution for all PDF-based documents. ReportMiner’s automated data extraction features make it an easy to create and deploy end-to-end integration solution for any use case involving data extraction from PDF sources.

Featuring a user-friendly interface, the solution design is based on a visual, drag-and-drop environment and does not require any form of coding or scripting.

  • Text-based PDFs: ReportMiner can read directly through text-based PDFs and extract the required data based on the designed extraction template.
  • Scanned or Image-only PDFs: Some of the source documents that companies receive are image-only PDFs such as scanned invoices. ReportMiner’s OCR capability creates a text equivalent of images stored in PDF documents. That point onwards, the extraction process is identical to text-based.
  • PDF Forms: In some cases, businesses also deal with PDF Forms to collect important information such as customer details. ReportMiner enables extraction of data from these forms and makes critical business data available for further use.

Crucial business data is often trapped in PDF documents. ReportMiner enables businesses to liberate data from different types of PDFs with its extensive data extraction features. Streamlined PDF data extraction, combined with the ability to automate the process, helps businesses save time and gain access to mission-critical information promptly.

Download our whitepaper, ‘Liberating Data from PDF Documents’ to learn how ReportMiner can help businesses in extracting business data for further processing.

Streamlining Data Extraction

Most of the crucial business data is stored in unstructured formats, while machines require structured data for processing. Businesses need data extraction tools to bridge this gap.

Unstructured Data | Data Extraction

Data extraction has evolved with technology, from manual extraction to complete automation. Constant innovation and developments in this field are making data extraction easier, flexible, and scalable for users.

Automation of Data Extraction

Previously, organizations were heavily dependent on manual extraction of data. In some cases, the IT department was responsible for writing custom scripts to extract data points, and in other, employees manually read through every document to extract data. In both cases, the data required further massaging based on the needs of end users, delaying business decisions.

Today, the key goal of a data extraction tool is to automate the entire process for its users. Template-based data extraction is a popular route to automation, giving greater control to users. It involves converting incoming documents using extraction templates which can be re-used for documents with similar layouts. Moreover, modern tools provide a Graphical User Interface (GUI) for the creation of these extraction templates, enabling business users to extract documents on their own, without the need to script or code.

Other than this, technologies like Natural Language Processing (NLP) enable computers to understand free-form text and make it analyzable through speech tagging, deep learning, text analytics, and other methods. Tools that leverage Machine Learning (ML) use algorithms to understand text structures and word morphology.

Automating data extraction process accompanies several benefits for businesses. Some of them are listed below:

  • Saves Time and Effort

Reusability of extraction templates for similar documents saves time and effort.

  • Faster Decision Making

Data can be processed in real time. This makes meaningful data readily available for business analysis, ensuring faster decision-making.

  • Streamlined Document Processing

Data patterns are used for recognizing documents and can allow for automatic classification of documents.

Conclusion

Automation has reshaped the business landscape. In today’s dynamic environment, it is important for businesses to focus on the quality and accessibility of data to stay ahead of their competitors. Accurate data can be made available in real-time through the automation of data extraction process.

For more information about how the concept of data extraction has evolved to meet modern business needs download the whitepaper ‘State of the Art of Data Extraction’.