Etl 강좌

ETL is an acronym for extract, transform, load. This describes a computer programming process that automatically extracts, transforms, and loads multiple forms of computer data from a variety of data sources, and then transmits them to a data storage facility or data warehouse repository.

ETL was introduced half a century ago in computing circles to help computer techs better integrate and load data into large computer mainframes for computation purposes and data analysis. The ETL process was originally designed to support business intelligence needs. It is still used today, generally for smaller repositories of data, and other forms of data integration software are being used for larger volumes of data.‎

Learning about ETL can help you further your data storage knowledge, which is such a huge part of today's interconnected networks. Knowing ETL will help you understand why companies use the process to sort through their data, decide what to keep, and what to eliminate.

Learning ETL can help you manage data projects more efficiently. This is especially true for anyone eager to learn about scalable data analytics processes and optimal business intelligence warehousing.‎

The typical careers for someone who has learned ETL include data warehousing, data storage, network functionality, computer networking, systems architecture, and other similar roles within companies or agencies. Realistically, you could work in just about any data-intensive industry and find employment as an ETL developer. Many industries are moving toward big data repositories, and having the knowledge of ETL processes can be a tremendous asset for someone aspiring to find ETL work.‎

When you take online courses about ETL, you can learn the basics of data warehousing for business intelligence. But that's just the start. Within the wide variety of online courses about ETL, you can branch-off to pursue your interests in data warehousing, data storage, SQL database learning, visual modeling, and much more. Learning about these interconnected specialties can help you stay ahead of the big data revolution.‎