Data Capture: What it is and how it works

In times of rapidly increasing data volumes, it is indispensable for companies to efficiently collect and evaluate information. This is the only way they can gain valuable insights into their business processes and make informed decisions.

As AI continues to evolve, data capture plays an important role in this context. Companies can use data capture systems to gather information about their customers, products, services and other aspects of their business and identify inefficient processes.

In this blog post, we show how the data capture process works, which data capture methods are available and which examples we know from practice. And: We explain how companies can benefit from data capture automation.

The most Important in a Nutshell

  • Data capture involves collecting information from various sources and storing it in a standardized format.
  • Common data capture systems include Optical Character Recognition, Intelligent Document Processing, barcodes and QR codes.
  • The main benefits of the method are better data quality, well-founded decision-making and easier compliance with regulations.
  • With Konfuzio, you can automate the capture, processing and analysis of data in unstructured documents such as invoices and orders. Let one of our experts advise you now on how you can automate important document management processes with Konfuzio!

Data Capture Definition

data capture definition

Data capture can be defined as the process of collecting data from various sources and converting it into a digital format. For example, this data can come from

  • documents such as scan, photo, TIF or native PDF,
  • Emails,
  • Web forms, 
  • Social media platforms 
  • and other digital sources. 

The goal of Data Capture is to capture information in a structured form in such a way that companies can process and analyze them as easily as possible.

Data Capture includes various technologies such as OCR (Optical Character Recognition), ICR (Intelligent Character Recognition), OMR (Optical Mark Recognition) and barcodes. These technologies enable data to be captured quickly and accurately and converted into a digital format.

In practice, companies use OCR, for example, to digitize invoices automatically. This so-called Invoice Capture captures all relevant information from a paper invoice and stores it in a database.

Companies can use data capture in various industries, such as healthcare, finance, retail, and logistics. Especially in industries where large amounts of data are captured and processed, data capturing helps to optimize business processes and make better decisions.

data capture process

How the Data Capture Process Works

The data capturing process describes the collection of data in a company or organization. It involves collecting information from various sources and storing it in a unified format. This happens in 4 steps:

  1. Set data

    First, companies must decide what data they want to capture online in a system using Data Capture. Here, it is important to collect only relevant information to make the process as efficient as possible.

  2. Identify data sources

    Next, companies must identify the data sources from which they want to obtain the information. These can be internal sources such as databases or external sources such as websites.

  3. Capture data

    Once all relevant information has been identified, companies capture it. They can do this manually or using data capturing automation. With manual capture, the data must be entered into the system by an employee. With automated capture, data capture software is used to automatically extract the data from the sources.

  4. Save data

    Once the data has been captured, companies need to store it in a consistent format. Here, it is important that the format is uniform for all data sources so that the data can be easily analyzed and processed later. This is where data capture management plays a crucial role. It ensures that all data is stored correctly, uniformly and correctly.

Full text search

The Full text search searches documents for specific words or phrases and displays relevant sections or documents. This feature speeds up information retrieval by efficiently querying extensive amounts of data and providing instant results.

Automatic document separation

The automatic document separation recognizes individual documents within large file batches and separates them accordingly. This optimizes document management, as users do not need to manually separate individual documents.

Categorization of documents

The Categorization of documents classifies texts into corresponding categories according to defined criteria. This structures the document pool and enables faster and targeted access.

Automatic routing in the enterprise

The Automatic routing forwards documents to the right departments or people based on their content. This increases the efficiency of work processes, as the necessary information arrives directly at the right place.

Document summary

The Document summary extracts the essential information, e.g. about NLP or NLU technologies, from longer texts and presents them in an abbreviated form. This allows users to quickly grasp the core content of a document without having to read the entire text.

Professional evaluation of the contents

Professional evaluation assesses the content of documents in terms of their relevance, accuracy and quality. Explainable expert systems In doing so, analyze texts and ensure that information meets established standards, e.g., in KYC processes, Freight processing, Order processing or the Audit.

9 popular Data Capture Systems

There are several data capture systems on the market, one of which is Konfuzioalso referred to as Data Capture Methods, each of which companies can use for different purposes. These 9 systems are particularly common:

Manual data acquisition

In this form of data capturing, companies enter data - from forms, for example - manually into a computer to digitize the data. However, this data capturing method is only suitable for a business that needs to capture and process a low, variable volume of data. This is because manual data capture depends on human labor and is therefore prone to errors.

OCR - Optical Character Recognition

OCR is a simple data capture example for capturing full texts. This is a technology that recognizes machine-generated characters and fonts. Companies can use OCR to automatically extract and process text from scanned documents and PDF files, for example. OCR is often used where large volumes of similar data are generated, e.g. in the healthcare, insurance and financial sectors. OCR is often supplemented by ICR, IDP or OMR solutions.

ICR - Intelligent Character Recognition

ICR can read handwritten characters of any font and transform them into meaningful data. For example, ICR prepares handwritten data from forms so that a business can easily process it. The technology is used primarily by banks and financial organizations. ICR is the next generation of OCR technology.

IDP - Intelligent Document Processing

IDP combines AI technologies such as Natural Language Processing (NLP) and Optical Character Recognition (OCR). It is able to recognize common patterns in large amounts of data and sort them by type of content and check for accuracy. These data capture technologies are used primarily by companies that need to process documents such as invoices for collaboration with service providers.

OMR - Optical Mark Recognition

An OMR system can extract data from completed forms by scanning the marked fields and storing the information in a database. This data capture technique is used primarily in survey documents, ballots, and exams.

Barcodes and QR codes

The barcode technology can read information from barcodes and convert it into a digital format. A distinction must be made between 1D barcodes and 2D barcodes. 1D barcodes are used in stores, for example, to track inventory. They are also used in hospitals to verify patient data. 2D barcodes - also called quick response codes - are suitable for capturing web pages or documents, for example. In practice, this is the case for advertising and on product packaging, for example.

RFID - Radio Frequency Identification

RFID technology is a method of capturing data using radio waves. For this purpose, companies attach RFID tags to their products to store and transmit an information. In particular, companies in logistics and retail use this data capture application.

Web Scraping

Web scraping is a method of collecting data from web pages. As a rule, this involves bots and crawlers. Companies can use this type of data capturing to collect large amounts of data from the web and store it in relevant databases. In practice, for example, online stores can automate the monitoring of competitors' prices and optimize their own prices in this way. Or: companies can use web scraping to automatically receive news alerts when their name is mentioned in the press.

CDC - Change Data Capture

Change Data Capture (CDC) is a technique for capturing data changes in real time. CDC is particularly useful in scenarios where organizations need to track and quickly analyze changes made to their data. This is how Data Capture Change works: it captures the changes made to a database and stores them in a separate log file. This log file contains all the changes made to the data, as well as the time and date of the change. Organizations can use this log file to track and analyze the changes made to their data over time.

In practice, companies use Change Data Capture mainly in data warehousing and business intelligence applications.

CDC helps them identify trends and patterns in their data that they can use for better business decisions. In addition, companies can also use CDC to identify and correct errors and inconsistencies in data before they cause problems.

data capture benefits

Benefits of Data Capture 

Managing data collection is an important process for any company that works with data. It involves collecting, recording and processing data from various sources. Electronic Data Capture brings these advantages to the process:

Improved data quality

Professional smart data management ensures that captured data is accurate, complete and consistent. This helps companies make better decisions based on reliable data. By implementing relevant data capture requirements, companies can also ensure that the captured data meets their own specific needs.

Increased efficiency

Data Capture Solutions can automate the data capture process so that companies have to enter less data manually. This leads to greater efficiency as they save time and reduce the risk of errors. In this regard, Data Capture Systems providers also carry customized solutions that are tailored to a company's specific needs.

Better decision making

Data capturing provides companies with the information they need to make informed decisions. Because by analyzing the captured data, they can efficiently identify trends and patterns in their data and thus react quickly and correctly to changes. In practice, this means: more efficiency and more profitability.


Data capture management helps companies to comply with regulations such as GDPR, HIPAA and PCI-DSS. They can store their individual data capture requirements and thus ensure that data is captured and stored in a secure and legally compliant manner.

Conclusion: More efficient processes with data capture management

Data capture is an important process for companies to collect and analyze valuable information - and to draw the right conclusions for their daily business operations to achieve better business results. However, data capturing also comes with some challenges. Companies need to select the right data, identify the relevant sources for this data and collect and store the data in a structured manner. In this context, the question of the right data capture system also arises.

Konfuzio is a powerful Data Capture Solution. The German software provides companies with an advanced tool for the automatic capture, organization and analysis of unstructured data.

In order to be able to offer document processing - and therefore also data capture - efficiently, Konfuzio has developed its Deep Computer Vision based software with a training on over 100,000 documents. Machine and Deep Learning make it possible to extract and classify data and to pass it on to the downstream workflows in a qualified manner.

In practice, companies can use Konfuzio to manage large volumes of unstructured data, such as texts, e-mails, contracts and other documents, and to gain valuable insights from them.

Talk to one of our experts now and let them advise you on how you can use Konfuzio to add value to your company!


What is Data Capture?

Data capture is the collection and storage of data from various sources. This can be done manually or through automated methods. Companies use data capturing to gather information about their customers, products and business processes. They can then analyze the data to gain insights and make informed decisions.

What is Change Data Capture?

Change Data Capture (CDC) is a method to capture and process changes to data in real time. It captures only the changes and not the entire data set. This enables faster processing and better data quality.

What data capture systems are available?

There are various data capture systems, each serving a different purpose. Automated Data Capture is currently in particularly high demand. These include the data capture techniques OCR (Optical Character Recognition), ICR (Intelligent Character Recognition) and IDR (Intelligent Document Recognition). Which system is the right one depends on the requirements of the application.

Jan Schäfer Avatar

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