Data extraction can have multiple meaning. More commonly, the term refers to the retrieval of data from various data sources. Organizations often extract data for further processing or to move or migrate it to a data lake or data warehouse. The majority of extracted data comes from unstructured data sources and disparate data formats.The traditional method for data extraction in this context is ETL (extract, transform, load) although the ELT (extract, load, transform) is gaining traction as it provides more flexibility, accessibility, and scalability, as well as faster transformation and load times.
Another definition for this term involves the process of analyzing and crawling data to retrieve relevant information from data sources.
Snowflake and Data Extraction
Snowflake supports both ETL and ELT and works in tandem with a range of data integration tools. New tools and self-service pipelines are eliminating manual ETL coding and the need for outsourced data cleansing services.