The term “data extraction” might sound like a complicated procedure, but it couldn’t be further from the truth. As paper-based processes go digital, the transition isn’t perfect. Despite a wealth of new tools to digitally collect information, paper-based forms and processes still exist. This information must still be collected, analyzed, and processed. Here is where data extraction software can bridge the gap to complete the digital transformation of your business processes.
What is Data Extraction Software?
Data extraction software lets companies retrieve structured, semi-structured, and unstructured data from a variety of sources for collection, analysis, and processing. A data extraction software solution can be utilized to identify and recognize data located in paper forms, scrape information from websites, or even retrieve content from emails.
The way this software works is that it is trained to recognize characters, words, and phrases that are deemed important, based on the specific use case where the data extraction is being performed. Despite all the advances in machine learning and Artificial Intelligence, machines still can’t really think like a human. Instead, vast amounts of characters and phrases can be learned over time such that a high probability of assembling these characters into words or numbers is achieved – as a pretty good match.
There are Many Different Use Cases
As part of your evaluation of data extraction software and picking a vendor or partner to work with, you need to define your requirements. Are you building a data warehouse to store corporate financial records? Are you performing an audit for regulatory compliance record keeping? Or are you working to streamline manual data entry or a paper-based process?
Data aggregation strategies utilized for compliance requirements will focus on making sure all the data can be accessed and available, with a focus on achieving a high capture rate – often in the high 90 percentiles. These types of systems can err on efficiency. As long as everything is there to sustain an audit, it might not matter that it could take many days to find just the right information.
Data extraction software utilized to streamline a business process, however, must operate at a high level of performance. If not, the existing paper-based processes will suffice. Here is where choosing a specialty vendor that has experience in working with the types of paper documents relevant for your industry will be an important selection criterion.
The Importance of Industry Specialty
The way that hi-performance data extraction solutions operate is with an existing understanding of what data fields are relevant for each document and where these fields are located on each document. For example, a financial institution that needs to process hand-written, paper loan applications for assessing the creditworthiness of a prospective customer, there might only be certain fields that are most important to get “right” the first time, such as first name, last name, address, and social security number. Initial review and a preliminary approval could be performed with just these fields for an automobile loan in just 10 seconds, which might make the difference between getting (or not getting) the business.
Structured vs. Unstructured Data
The last evaluation factor is to understand whether your data is structured or not. Structured data is highly organized and readily searchable, typically residing in a database already. Unstructured data, however, cannot be processed or analyzed via conventional data tools and methods. It can come from a variety of sources and in different formats. An effective data extraction solution designed to improve the performance of a business process must be adept in extracting both structured and unstructured data, which until recently, was problematic and difficult to achieve.
Here is a resource to learn more about unstructured data.
The Role of Artificial Intelligence With Data Extraction Software
Artificial Intelligence, or AI, has become a critical enabling technology to help data extraction solutions perform with a high degree of efficiency. And, with the learning algorithms inherent in such a solution, to improve performance over time. This type of software can be implemented and then trained to know what types of data exist, where to look for it on a particular page, and what the typical content might be. This logic can even be applied to handwritten notes that accompany such a document. As more documents are classified and scanned, the location and content of the data that is typically associated with these documents becomes expected and understood with greater accuracy.
In conclusion, as you evaluate your data extraction solution requirements as part of how to improve an existing process or how to implement a new one, apply these decision criteria to help narrow your search and better understand what options exist. Then assemble a shortlist as part of the final evaluation process.