Build highly scalable and extensible SQL-based data pipeline using Managed Workflow for Apache Airflow and Amazon Redshift

Data is a vital element of today’s innovative organizations and its growing in volume and complexity faster than ever. Traditional data warehouses have rigid architectures that do not scale for modern big data analytics use cases. Amazon Redshift is the most widely used cloud data warehouse that uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes. Customers use Amazon Redshift to run scalable data pipelines in an ELT pattern and to orchestrate, they utilize Amazon Managed Workflow for Apache Airflow (MWAA), a highly scalable, fully managed and extensible orchestration solution based on open source Apache Airflow. In this session, learn how you can setup and execute end to end data pipelines using Amazon MWAA and Amazon Redshift to drive higher elasticity, reduce maintenance costs, and attain near real-time decision making.

Speaker: Praveen Kumar, Analytics Solutions Architect, AWS
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