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Data Capturing vs Data Extraction

In today’s technological world, data is the most important resource for institutions and businesses. It is what makes all top tech companies what they are. As such, most IT experts are developing solutions that use data in some form or another. Therefore, the ability to process data is essential to IT specialists.

In general, there are several processes data usually undergo. Examples of these procedures are data capturing and data extraction. These two terms generally refer to different things. As such, this article will highlight the difference between the two terms.

Data Capturing

Data capturing is a process that allows a user to collect information from a physical or electronic document into a digital format that is readable to machines. In the past, data capture was slow. Now, AI has reinvented how this process occurs. A typical example of data capturing occurs in most convenience stores. Data from products are usually automatically collected to a billing and inventory system.

Data Capturing Process

In general, data capturing can begin with the completion of a physical or electronic form by a user. Afterward, the information is digitized to make it accessible. To make data capture easier, forms are mostly made with spaces for specific information. Doing this makes the process faster.

In addition, several other technologies can be used to capture data. Some of the most common tools used for data capture include:

  • Cameras;
  • Fingerprint scanners;
  • Face recognition equipment;
  • Writing pads;
  • Keyboards;
  • Optical character recognition (OCR) equipment.

Each of these tools is optimized to ensure smooth workflow, compatibility, and fast movement of data.

In most cases, OCR technologies are the most widely used data capturing tools. The popularity of this technology is primarily due to its adoption by retail and wholesale companies. In particular, this tool is popular because of its ease of use.

Data Extraction

Data extraction can use some of the technologies used in data capture. However, this process has a wide scope. You can use this process to gather data in different formats from various sources. Likewise, the collection of data is just one step in the process. As such, the data that is collected is also stored with the intention of further action on it. Afterward, you will need data processing technologies to make sense of what you store.

Data Extraction Process

Apart from extraction, another function of data extraction is data restructuring. Hence, you can rearrange or reformat unstructured data after collection before it is stored. Doing this makes future processing more efficient.

Typically, data extraction tools are made either as generic or specific tools. Therefore, an extraction technology may be suitable for some or all types of data. In either case, you can use these technologies to collect and store data from text documents, websites, PDF files, and other document types. Likewise, you have the option of storing data on physical or cloud storage. However, the extraction, transformation, and storage process of data extraction are defined by the parameters you use. As such, these parameters define the scope and limits of your extraction process.

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