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Tag: ETL Pipeline

Orchestrate an end-to-end ETL pipeline using Amazon S3, AWS Glue, and Amazon Redshift Serverless with Amazon MWAA | Amazon Web Services

Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is a managed orchestration service for Apache Airflow that you can use to set up and...

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Modernizing data science lifecycle management with AWS and Wipro | Amazon Web Services

This post was written in collaboration with Bhajandeep Singh and Ajay Vishwakarma from Wipro’s AWS AI/ML Practice. ...

Build efficient ETL pipelines with AWS Step Functions distributed map and redrive feature | Amazon Web Services

AWS Step Functions is a fully managed visual workflow service that enables you to build complex data processing pipelines involving a diverse set of...

Prepare and load Amazon S3 data into Teradata using AWS Glue through its native connector for Teradata Vantage | Amazon Web Services

In this post, we explore how to use the AWS Glue native connector for Teradata Vantage to streamline data integrations and unlock the full...

How GamesKraft uses Amazon Redshift data sharing to support growing analytics workloads | Amazon Web Services

This post is co-written by Anshuman Varshney, Technical Lead at Gameskraft. Gameskraft is one of India’s leading online gaming companies, offering gaming experiences across...

Unlock scalable analytics with AWS Glue and Google BigQuery | Amazon Web Services

Data integration is the foundation of robust data analytics. It encompasses the discovery, preparation, and composition of data from diverse sources. In the modern...

Orchestrate Amazon EMR Serverless jobs with AWS Step functions | Amazon Web Services

Amazon EMR Serverless provides a serverless runtime environment that simplifies the operation of analytics applications that use the latest open source frameworks, such as Apache Spark...

Top 20 Data Engineering Project Ideas [With Source Code]

Data engineering plays a pivotal role in the vast data ecosystem by collecting, transforming, and delivering data essential for analytics, reporting, and machine learning....

The Success Story of Microsoft’s Senior Data Scientist

Introduction In today’s digital era, the power of data is undeniable, and those who possess the skills to harness its potential are leading the charge...

Build an image search engine with Amazon Kendra and Amazon Rekognition

In this post, we discuss a machine learning (ML) solution for complex image searches using Amazon Kendra and Amazon Rekognition. Specifically, we use the...

Simplify and speed up Apache Spark applications on Amazon Redshift data with Amazon Redshift integration for Apache Spark

Customers use Amazon Redshift to run their business-critical analytics on petabytes of structured and semi-structured data. Apache Spark is a popular framework that you...

ETL vs ELT: Which One is Right for Your Data Pipeline?

Image by Author  ETL and ELT are data integration pipelines that transfer data from multiple sources to a single centralized source and perform some...

Difference Between ETL and ELT Pipelines

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...

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