ETL stands for Extract, Transform and Load, which is a process used to collect data from various sources, transform the data depending on business rules/needs and load the data into a destination database. The need to use ETL arises from the fact that in modern computing business data resides in multiple locations and in many incompatible formats. For example business data might be stored on the file system in various formats (Word docs, PDF, spreadsheets, plain text, etc), or can be stored as email files, or can be kept in a various database servers like MS SQL Server, Oracle and MySQL for example. Handling all this business information efficiently is a great challenge and ETL plays an important role in solving this problem. In a word: Creating  Sources and Targets  Repositories. Mapping Source and Target Repositories.

• Extract – The first step in the ETL process is extracting the data from various sources. Each of the source systems may store its data in completely different format from the rest. The sources are usually flat files or RDBMS, but almost any data storage can be used as a source for an ETL process. 
• Transform – Once the data has been extracted and converted in the expected format, it’s time for the next step in the ETL process, which is transforming the data according to set of business rules. The data transformation may include various operations including but not limited to filtering, sorting, aggregating, joining data, cleaning data, generating calculated data based on existing values, validating data, etc. 
• Load – The final ETL step involves loading the transformed data into the destination target, which might be a database or data warehouse.

References:

https://en.wikipedia.org/wiki/Extract,_transform,_load

http://www.sql-tutorial.net/ETL.asp

ETL definition