Automating ETL Tasks Using AWS Glue

ETL - Data Cataloging, Data Validation and Data Processing

1. Why We Need This Use Case

AWS Glue is a serverless data integration service that makes it easy to discover, prepare, and combine data for analytics, machine learning, and application development. Using AWS Glue to automate ETL (Extract, Transform, Load) tasks simplifies the process of integrating data from various sources, transforming the data into a usable format, and loading it into an analytics platform, thereby enhancing data-driven decision-making and operational efficiency.

2. When We Need This Use Case

• Data Warehousing: To consolidate various data sources into a central repository for analytics and business intelligence.

• Data Lakes: For organizing data in a data lake architecture, enabling scalable analytics solutions.

• Real-time Analytics: When up-to-date data is required for real-time decision-making.

• Machine Learning: For preparing and processing data for machine learning models.