Data Capture is Not Data Entry
For a long time, Data Entry has existed in some form or another. Certificates, such as marriage and death certificates, were once transcribed by Data Entry clerks using pen and paper. As the computer age arrived, this work became easier as it went hand in hand to offices full of individuals typing away on keyboards.
As time passed and data got transferred or entered into a database, Data Entry became known as transcribing information from one source to another with outsourcing. With this, one may ask how does Data Entry differ from Data Capture?
Businesses need to know various essential data. They obtain the data from targeted groups. When one needs to get input from customers, employees or perform staff evaluations, surveying is a typical method for obtaining the required information. One thing to think about when considering doing a survey is what would be the most appropriate design. One should know what the goal is when obtaining the needed data from the source. It is essential to know the various techniques to be able to achieve the goal.
The words imaging, scanning, indexing, and capturing get commonly used in document management. Many of these approaches overlap, so determining which one is best for the business ultimately comes down to the data structure and what one wants and has to do with it.
The distinctions between data entry and data capture services and how to choose which is best for your company’s objectives are discussed more in the following contents.
What is Data Entry
The input and storage of text and numbers from a document into an electronic system is known as data entry. Depending on the type of document, this gets done via automated computer software or manual entry. Forms and surveys can serve various purposes, and they might inquire for short or extended responses. It is more difficult and tricky to use automated processing methods when data sources incorporate handwriting. Manual Data Entry is required when handwritten data gets used. Additionally, it requires more time and is more expensive than utilizing automated software.
What is Data Capture
Data capture is analogous to data entry, except it only gets utilized on data sources with basic answer types. Automated data capture processes multiple-choice, yes-no, and bubble-circle questions. Because not all automated software can interpret handwriting, printed responses do not get included in data capture.
After gathering the data, it can get exported to a spreadsheet or other indexing solution, where it can be saved, shared, and so on. Because of the automated nature of data capturing services, they produce short turnaround times and tend to be less expensive.
Here are some technologies integrated with data capture:
Optical Character Recognition, or OCR, supplies Data Capture software that removes the need for Manual Data Entry. Moreover, the OCR software is an accurate, highly intelligent, and scalable data capture and document processing system. It also converts the information obtained on paper or digital, image-based documents of every form and complexity into business-ready data.
This adaptable solution may be installed on any desktop or as a client-server program, and businesses may use it throughout a department or a whole company. Its intelligent nature enables it to handle a wide range of document processing scenarios and support a wide range of form types, resulting in a system that can meet a wide range of workflows and regulatory requirements.
Machine learning is the application and development of computer systems that can learn and adapt without specific instructions. To put it another way, it is a system that can read the data and expand from it to find more effective ways of doing a task. This strategy is advantageous in large-scale businesses when it comes to data capture. Moreover, Machine Learning allows the system to set and forget the automated data extraction program, allowing it to learn from each document processed, each user command, and each new set of data.
Because of Machine Learning, enhanced data capture systems that need minimal user interruption can produce correct data and function efficiently, making them highly adaptable to various industries.
Simple operations like data retrieval and transmission from one system to another can get computerized using Robotic Process Automation or RPA. Following the initial success of RPA projects, companies are increasingly looking to automate other, more complicated business processes.
According to solution providers and their clients, to complete tasks of greater complexity, data inputs to a given process must be decoded and comprehended.
Data Entry VS Data Capture: What’s the Difference?
While data capture can entail data entry, it does not rely solely on humans entering information. Instead, it uses technology to grab data from current existing sources and even manipulates the data to meet the output requirements of the company using data capture.
Though Data Entry and Data Capture both have the same goal: to obtain information, they still have a distinct feature making them different. Data Entry gets done via automated computer software or manual entry. Additionally, it can inquire for short or long responses. On the other hand, Data Capture works on data sources with basic answer types such as yes or no, or multiple-choice question types.