Purpose and Applications
Content:
π Why use AWS for Data Pipelines?
AWS provides fully managed and scalable services like S3, Glue, and Athena, making it ideal for building cost-effective, reliable data pipelines. These services eliminate the need for provisioning infrastructure and support automation at scale.
With pay-as-you-go pricing, global availability, and strong integration capabilities, AWS is a go-to platform for modern data engineering.
π Applicable Use Cases
- π Data Cleaning and Transformation: Automatically clean and normalize raw CSV, JSON, or log files using AWS Glue.
- π Business Analytics: Enable business analysts to run SQL queries directly on S3 with Amazon Athena.
- π¦ ETL for Data Warehouses: Prepare structured data for loading into Redshift or other BI systems.
- π Scheduled Data Refresh: Run periodic jobs to update dashboards and reports using real-time or batch data.
π Future Scalability
- Easily integrate with other services such as:
- Amazon QuickSight for BI dashboards
- Amazon Redshift for data warehousing
- AWS Lambda for event-driven automation
- Support growing data volumes and additional data sources with minimal reconfiguration.
The architecture is modular and cloud-native, making it adaptable to future expansion and diverse analytics needs.