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extract-transform-load

Extract, Transform, Load (ETL) is a crucial process in data engineering that facilitates the movement of data from various sources to a target system, typically a data warehouse. The ETL process consists of three main steps:

Extract: Data is collected from diverse sources such as databases, files, or APIs. This step ensures that the data is ready for transformation.
Transform: The extracted data is cleaned, enriched, and formatted to meet the requirements of the target system. This may involve data quality checks and modifications.
Load: Finally, the transformed data is loaded into the target system for analysis and reporting.

ETL is essential for organizations to manage and utilize large volumes of data effectively.

A Friendly Introduction to ETL (Extract, Transform, Load) Process in Data Engineering with Python

Python in Plain English

What is ETL (Extract, Transform, and Load) ETL stands for Extract, Transform, and Load. It’s a three-step process in data engineering that helps move data from its source to a target system. Let’s bre...

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Transforms Created On: Feb 09, 2021 | Last Updated: Aug 11, 2021 | Last Verified: Not Verified Data does not always come in its final processed form that is required for training machine learning algo...

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A transformer model. User is able to modify the attributes as needed. The architecture is based on the paper “Attention Is All You Need”. Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Ll...

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