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Extract Transform Load (ETL)

What is the difference between extract transform and load?
Extract refers to the process of pulling data from a source such as an SQL or NoSQL database, an XML file or a cloud platform.
Transform refers to the process of converting the format or structure of a data set to match that of a target system.
Load refers to the process of placing a data set into a target system.
What is ETL extraction?
Data extraction refers to the method by which organizations get data from databases or SaaS platforms in order to replicate it to a data warehouse or data lake for Reporting, Analytics or Machine Learning purposes.
What is ETL used for?
ETL stands for extract, transform, and load and is a traditionally accepted way for organizations to combine data from multiple systems into a single database, data store, data warehouse, or data lake.
The five steps of the ETL process can be abbreviated to 'ECTLA': Extract, Clean, Transform, Load, and Analyze. 1.
Extract: Data sets are captured from unstructured sources and placed into a temporary staging location.

Extract, transform, and load (ETL) is the process of combining data from multiple sources into a large, central repository called a data warehouse. ETL uses a set of business rules to clean and organize raw data and prepare it for storage, data analytics, and machine learning (ML).

Extract Transform Load (ETL)

What is the difference between extract transform and load?

What is ETL extraction?

What is ETL used for?