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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 299
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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 343
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ELT vs ETL: Unveiling the Differences and Similarities

Analytics Vidhya

Introduction In today’s data-driven world, seamless data integration plays a crucial role in driving business decisions and innovation. Two prominent methodologies have emerged to facilitate this process: Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT).

ETL 269
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Good ETL Practices with Apache Airflow

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction to ETL ETL is a type of three-step data integration: Extraction, Transformation, Load are processing, used to combine data from multiple sources. It is commonly used to build Big Data.

ETL 381
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ETL Pipeline with Google DataFlow and Apache Beam

Analytics Vidhya

Introduction Processing large amounts of raw data from various sources requires appropriate tools and solutions for effective data integration. Building an ETL pipeline using Apache […]. The post ETL Pipeline with Google DataFlow and Apache Beam appeared first on Analytics Vidhya.

ETL 383
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Unlock the True Potential of Your Data with ETL and ELT Pipeline

Analytics Vidhya

Introduction This article will explain the difference between ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) when data transformation occurs. In ETL, data is extracted from multiple locations to meet the requirements of the target data file and then placed into the file.

ETL 293
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From Blob Storage to SQL Database Using Azure Data Factory

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Azure data factory (ADF) is a cloud-based ETL (Extract, Transform, Load) tool and data integration service which allows you to create a data-driven workflow. In this article, I’ll show […].

ETL 322