ETL is a method employed in data warehouses to transfer data from the source systems to a data warehouse and then transform the data into an usable format. The ETL procedure is composed of three major phases:
Extract: In this phase, it is the extraction of data from various systems. It could involve the reading of information from flat files, databases APIs, databases, or other sources. Data extraction may be scheduled to take place on a regular basis or even in real-time when data is updated.
Transform: Data Transformation is the procedure of cleansing up, structuring and enriching extracted data. This includes things like data validation deduplication, format transformation and implementing business-related regulations. The transformation process ensures that the data is reliable and useful to be analyzed.
Load: The last stage is loading converted data in the warehouse. The loading of data can take place in batches (loading huge amounts of data on a regular basis) and in real-time (immediate changes). The data loaded is organized into dimension tables as well as fact tables. This makes it ready to be used in analytical queries.