Data Capture
The concept of data capture appears in many fields. For centuries, people have transferred information to paper and stored it in folders or boxes. With personal computers and printers becoming popular, it has become very easy to print the necessary information on paper. Especially in recent years, contracts, invoices, tickets, resumes and many other types of documents have been printed out with the help of scanners. However, with the personal computer, it has also become much easier to store information digitally. Its use has increased significantly in recent years. Dropbox and Google Drive cloud storage solutions have made it even more useful. Even though we are starting to move to digital information storage, there is still too much information on paper. This is why data capture has become critical.
What is Data Capture?
First of all, data capture allows to extract information from paper documents based on scanning or creating images of the documents. However, it is a technology for storing them in a structured form. At this point, a structured format is meant to help computers understand and communicate. Even to create a consistent and easy-to-understand format. Splits texts into chunks instead of large text files. It also marks important information with identifiers to mark it. For example, this is like marking up a text on paper to create a summary. This data is then transformed into a CSV, JSON, XLSX or XML. Below you can see an example of the JSON format of an invoice document:
[ {
“Buyer”: “ABC Ltd.”,
“Date”: “20-01-2023”,
“Amount”: “20,00”,
“Currency”: “TL”}]
How is it done?
There are stages to capturing data from paper documents. The first step is to convert the paper document into a digital document such as PDF or JPG. This usually happens with a scanning device or cell phone. As a result, as soon as the document is digital, you have an image of the document. But there is no information that the computer can read yet. So much so that for a computer it is just an image, not text.
OCR technology takes center stage to convert the image in the hand into text. OCR stands for optical character recognition. This technology converts an image of a document into an unstructured text file. In addition, the quality of the image, the lighting and the distance from the scan point to the document affect the result and accuracy of the conversion.
“Even if we have text after OCR conversion, it is not yet in a format that the computer can understand.”
The next step is to get a system that can read the text, identify important information. What is also needed is to use an intelligent parsing system that extracts the right information.
As a result, using specialized third parties for your data capture projects is much more efficient in terms of both time and money. In fact, Papirus AI is a company specialized in this field. You can choose Papirus AI to extract data from any document type without the need to define templates.
