Significance of ETL in data warehouse
ETL is a process in data warehousing that represents extract, transform, and load. This process involves extracting data from multiple sources, transforming and performing computations, cleansing for data quality, and loading the data into a target system. ETL is important for data warehouses to collect, read, process, transform, migrate, and analyze data from several disparate sources into one target database or warehouse. ETL eliminates silos in sources and integrates data for easy access and BI.
The ETL process typically consists of the following steps:
- Extract/ingest: Data is extracted from the source systems. This can be done using a variety of methods, such as database queries, file transfers, or APIs.
- Transform: The data is transformed into a format that is compatible with the target system. This may involve cleaning the data, converting data types, or merging data from multiple sources.
- Load: The data is loaded into the...
