An Overview of the ETL Process
The ETL process(Extract, Transform, Load) is an optimized solution that combines data from various data sources into one consistent data store that is loaded into a data warehouse or other target repository. The ETL process is the foundation for work streams like machine learning and data analytics. ETL cleans and organizes data to address business analytics requirements like monthly reporting. However, it can also handle advanced analytics to improve backend processes thereby enhancing user experience. The complete ETL process consists of extracting data from legacy systems, cleaning that data to improve data quality, and finally loading the formatted and processed data into a target database. Here is the ETL process in some detail. •Extract: During extraction, the raw data is exported from source locations to a staging area. This data can then be extracted from a range of sources in their native format – unstructured, semi-structured, or structured. The sources of data extract...