A metadata-driven ETL framework using Azure Data Factory boosts scalability, flexibility, and security in integrating diverse ...

With Apache Spark Declarative Pipelines, engineers describe what their pipeline should do using SQL or Python, and Apache Spark handles the execution.

Our repository contains a comprehensive README.md, an architectural diagram, and proper GitHub/GitLab configurations to ensure the project is fully reproducible. ... (ECR) and AWS AppRunner to ...

The AI-driven ETL pipeline dynamically adjusts data extraction, transformation, and loading processes, resulting in significant improvements in data integration performance. Overview of the Paper ...

Pipeline executed, metadata is created and pushed; Semantic layer populated via cataloging and lineage; Like most areas, AI poses unique opportunities for an ETL-powered data fabric. Allowing the ...

For Amazon Web Services (AWS) and Snowflake a modern data streaming pipeline makes it easy for organizations to get data in near real-time from one platform to another.

Krishnamoorthy, who goes by G2, is under no illusions that companies will store all of their data in AWS databases or AWS file systems. He understands that data will exist in silos, in other ...

At AWS re: Invent, Amazon Web Services, Inc., an Amazon.com, Inc. company, today announced new integrations that enable customers to quickly and easily connect and analyze data without building ...

“We look forward to using Amazon Aurora PostgreSQL zero-ETL integration with Amazon Redshift, which will remove the burden of data pipeline management and maintenance for our engineering team.

Picnic redesigned its data pipeline architecture to address scalability issues with legacy message queues. The company uses connectors to build streaming pipelines from RabbitMQ and to Snowflake and ...