Data capture

Definition

Input of data, not as a direct result of data entry but instead as a result of performing a different but related activity. Barcode reader equipped supermarket checkout counters, for example, capture inventory related data while recording a sale. See also data collection and data logging.

MEAN:

data capture A process for achieving the extraction of relevant data while the related transaction or operation is occurring. An example is a supermarket checkout equipped with point-of-sale terminals. The transaction is primarily concerned with the sale to the customer but while the purchased items are being entered onto the bill it is usual for the machine to record, and thus capture, data that will allow calculation of stock movement and other information.

If the equipment for data capture is online to a computer system, it is part of a data collection process and may be referred to as either data capture or data collection equipment. The term data capture is often used where a computer system monitors (and maybe controls) laboratory instruments, process parameters, etc.; in this context it is also known as data logging.

Data extraction

MEAN :

Data extraction is the act or process of retrieving (binary) data out of (usually unstructured or poorly structured) data sources for further data processing or data storage (data migration). The import into the intermediate extracting system is thus usually followed by data transformation and possibly the addition of metadata prior to export to another stage in the data workflow

Usually, the term data extraction is applied when (experimental) data is first imported into a computer from primary sources, like measuring or recording devices. Today's electronic devices will usually present a electrical connector (e.g. USB) through which 'raw data' can be streamed into a personal computer.

Typical unstructured data sources include web pages, emails, documents, PDFs, scanned text, mainframe reports, spool files etc. Extracting data from these unstructured sources has grown into a considerable technical challenge where as historically data extraction has had to deal with changes in physical hardware formats, the majority of current data extraction deals with extracting data from these unstructured data sources, and from different software formats. This growing process of data extraction from the web is referred to as Web scraping.

The act of adding structure to unstructured data takes a number of forms
• Using text pattern matching such as regular expressions to identify small or large-scale structure e.g. records in a report and their associated data from headers and footers;
• Using a table-based approach to identify common sections within a limited domain e.g. in emailed resumes, identifying skills, previous work experience, qualifications etc using a standard set of commonly used headings (these would differ from language to language), eg Education might be found under Education/Qualification/Courses;
• Using text analytics to attempt to understand the text and link it to other information