ETL (Extract, Transform, Load) are three processes that are combined together to allow for the transformation of data from a source to a destination. It is a popular data integration technique that is used to load data from multiple sources into a destination system, such as a data warehouse.
In the Extract phase, data is extracted from its original source such as from databases, flat files, JSON files, XML files, and other sources. This phase serves to isolate and extract the desired data from its source and to organize it into a common format.
In the Transform phase, data is modified, cleaned, and organized into the desired format required for the destination system. This phase also includes other steps to ensure that the data is of a consistent quality, such as the setting of rules to standardize spellings, and to filter out unwanted data.
In the Load phase, the transformed data is loaded into the destination system, such as in a database table or a data warehouse.
ETL is a critical process for businesses which depend on data integration. It allows data to be standardized and consolidated from multiple sources and into one system, allowing for improved productivity and flexible analysis of data. It is also used to support tasks such as data migration and data warehousing.
