Who Needs Extract Value From Data?
Data extraction tends to be a very demanding work. It is the act or process of retrieving 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 an 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, social media, scanned text, mainframe reports, spool files, multimedia 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 data extraction" or "Web scraping".
Comments (02)
Mike Szelinski
I ran the workflow this morning and so far it looks good. I like the user interface that gives me all the information about the process, the origin and the destination. I also built my first pipeline.
Mike Szelinski
Oh, I did not see this at first glance. This is just amazing how workflow immediately identifies the errors in "date" formats. What a tool...
Slavisa M.
Hey Mike, I am glad you like it. The workflow doesn't take too much time, we've tested it yesterday and it should run smoothly. Yes, date formats are sometimes hard to deal with, but we make sure they get transformed properly. Thanks...
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