Data Extraction

19Aug
Slavisa M. 2 Comments

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".

@Subnetservice most of data extraction and ETL processes are done in an automated fashion. Our data extraction professionals and developers build workflows for extraction purpose, utilizing high-tech OCR tools to do the job.

A properly designed ETL system extracts data from source systems and enforces data type and data validity standards and ensures it conforms structurally to the requirements of the output.

Extract, transform, load (ETL) is a three-phase computing process where data is extracted from an input source, transformed (including cleaning), and loaded into an output data container. The data can be collated from one or more sources and it can also be output to one or more destinations. ETL processing is typically executed using software applications but it can also be done manually by system operators. ETL software typically automates the entire process and can be run manually or on recurring schedules either as single jobs or aggregated into a batch of jobs.

Data extraction involves extracting data from homogeneous or heterogeneous sources; data transformation processes data by data cleaning and transforming it into a proper storage format/structure for the purposes of querying and analysis; finally, data loading describes the insertion of data into the final target database such as an operational data store, a data mart, data lake or a data warehouse.

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.

    Aug 20, 2022 at 11:47 am Reply
  • 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...

    Aug 20, 2023 at 9:23 am Reply
    • 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...

      Aug 20, 2023 at 11:04 am Reply

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