Abstract

Data Analytics and Machine Learning work-streams rely on ETL for their basis. ETL cleanses and organizes data using a set of business rules to meet particular business intelligence requirements, such as monthly reporting. Still, it may also handle complex analytics to enhance back-end operations or enduser experiences. An organization's ETL is frequently used to Retrieve data from legacy systems, To improve data accuracy and reliability, clean the data. Update a target database with data.