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The ETL process is comprised of 3 steps that enable data integration from source to destination: data extraction, data transformation, and data loading. Most businesses manage data from a variety of data sources and use a number of data analysis tools to produce business intelligence.What are some benefits of using the ETL process?
The ETL process is fundamental for many industries because of its ability to ingest data quickly and reliably into data lakes for data science and analytics, while creating high-quality models. ETL solutions also can load and transform transactional data at scale to create an organized view from large data volumes.What is the purpose of ETL?
ETL is a process which is used to Extract data, Transform the data and loading of the data to the final source. ETL follows a process of loading the data from the source system to the Data Warehouse. Extraction is the first process where data from different sources like text file, XML file, Excel file, or various other sources are collected.What are some common use cases for ETL?
Data migrations and cloud data integrations are common use cases. ETL moves data in three distinct steps from one or more sources to another destination. This could be a database, data warehouse, data store or data lake. Here’s a quick summary: Extraction is the first phase of “extract, transform, load.”