A very popular process known as ETL helps in building a target data source to house data that is consumable by applications. Generally, the data is in a raw format, and to make it consumable, the data should go through the following three distinct phases:

• Extract: During this phase, data is extracted from multiple places. There could be multiple sources and they all need to be connected to in order to retrieve the data. Extract phases typically use data connectors consisting of connection information related to the target data source. They might also have temporary storage to bring the data from the data source and store it for faster retrieval. This phase is responsible for the ingestion of data.
• Transform: The data that is available after the extract phase might not be consumable directly by applications. This could be for a variety of reasons. The data might have irregularities, or there might be missing data or erroneous data. There might be data that is not needed at all.

The format of the data might not be conducive for consumption by target applications. In all such cases, transformation has to be applied to the data such that it can be consumed by applications.

• Load: After transformation, data should be loaded to the target data source in a format and schema that enables faster, easier, and performance-centric availability to applications. This again typically consists of data connectors for destination data sources and loading data into them.