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Data Integration: Strategies for Efficient ETL Processes

Analytics Vidhya

This crucial process, called Extract, Transform, Load (ETL), involves extracting data from multiple origins, transforming it into a consistent format, and loading it into a target system for analysis.

ETL 302
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Building Your First ETL Pipeline with Bash

KDnuggets

Bash is a good choice for ETL due to its simplicity, flexibility, automation capabilities, and interoperability with other CLI tools. Get more info on putting together your first ETL script using Bash mainstay components.

ETL 288
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Why Do We Prefer ELT Rather than ETL in the Data Lake? What is the Difference between ETL & ELT

insideBIGDATA

In this article, Ashutosh Kumar discusses the emergence of modern data solutions that have led to the development of ELT and ETL with unique features and advantages. ELT is more popular due to its ability to handle large and unstructured datasets like in data lakes.

ETL 362
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Difference Between ETL and ELT Pipelines

Analytics Vidhya

Introduction The data integration techniques ETL (Extract, Transform, Load) and ELT pipelines (Extract, Load, Transform) are both used to transfer data from one system to another.

ETL 346
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Is manual ETL better than No-Code ETL: Are ETL tools dead?

Analytics Vidhya

Introduction ETL pipelines look different today than they used to. The post Is manual ETL better than No-Code ETL: Are ETL tools dead? ArticleVideo Book This article was published as a part of the Data Science Blogathon. appeared first on Analytics Vidhya.

ETL 341
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Open Source Python ETL

Hacker News

Amphi is a micro ETL designed for extracting, preparing and cleaning data from various sources and formats. Develop data pipelines and generate native Python code you can deploy anywhere.

ETL 179
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Best Practices for Building ETLs for ML

KDnuggets

This article talks about several best practices for writing ETLs for building training datasets. It delves into several software engineering techniques and patterns applied to ML.

ETL 332