The trend of storing paper documents and records is obsolete. Enterprises are switching to scanned documents to digitally store their data. Scanned documents also face the issue of data retrieval as they are stored in image formats which lack indexing leading in loss of data as image file data is not readable standard software.
Data entry automation software is available to extract data from scanned documents. The challenge is not just to extract data but also to extract it accurately which becomes more challenging when the stored data is in tabular or graphical formats and is to be presented in excel format.
Difficulties in retrieving data from scanned documents?
• Data stored in scanned documents and images is not in text format which could be simply selected from a cursor.
• It’s harder when the data tables are spanned across multiple pages and images and that too in graphical format.
• Sometimes Optical Character Recognition is not able to capture the data the images or scan quality is not clear, even if it captures inaccuracy is possible.
• Nested data is hard to understand and capture correctly.
Although there are software solutions still they require human efforts for execution and large volumes of data it is time and effort consuming. Also employing humans would require cost and real-time data tracking will still be an issue. The most convenient option that seems to resolve all of this is automation.
Automated data extraction is being widely accepted in modern day as it is efficient in capturing from scanned documents. Automated data retrieval solutions are capable of reading data from images and scanned copies after which convert them into Excel or CSV file formats. Benefits of automated solution over traditional manual solution are-
• Faster, easier and more efficient
• Improved accuracy
• Saves time and investment
• Real-time data tracking made possible
• Customization is possible with help of software in the process
There are various software and solutions available in the market to carry out the task and they even are compatible with current business software. Technologies such as artificial intelligence and machine learning are also serving as a helping hand to improvise the standards.