ETL Process Explained
ETL is the abbreviation for “extract, transform, load” and it enables organizations to collect and
copy data from various sources into a single, centralized system. Different types of data are
collected and refined by an ETL process. This data is then delivered to a data warehouse.
Moreover, it enables the migration of data among multiple sources, destinations and analytical
tools. An ETL process not only aids in executing strategies for data management but also
provides business intelligence.
An adequately designed ETL system is important for strategies that involve data integration
and is usually used in data warehousing. An ETL process ensures the extraction of data from
source systems along with enforcing standards for consistency as well as data quality. This
process makes it possible for separate data sources to be used together and for various types of
data to function together seamlessly and consecutively delivers data in a presentable form
enabling application developers to build applications and end users to make decisions.
The process of data extraction extracts data from sources that are either homogenous or
heterogeneous. Data is processed in the data transformation step with the aid of data cleaning.
Additionally, the data is moulded into a structure or storage format that enables querying as
well as analysis. Last but not the least is the step of data loading which involves the insertion of
data into the corresponding database (a data warehouse, an operational data store, data mart
etc.). ELT systems involve data integration from various applications which are developed and
supported by different vendors.
To digress, the websites that we access also have data. This data is stored on the servers of web
hosting companies and delivered from there via the Internet, upon user request, to ensure that
websites are accessible. Web hosting services can be of various types and the most efficient
web hosting services are usually referred to as th