International Journal of Advanced Research in Computer and Communication Engineering

Abstract: In the modern digital world, organizations generate large volumes of data every day. Managing and analyzing this data efficiently is a critical challenge for businesses. Traditional data processing systems rely on manual effort and server based infrastructure, making them slow, expensive, and difficult to scale. This project proposes a Serverless Data Aggregation and Automated Reporting System using Amazon Web Services (AWS). The system leverages AWS Lambda for serverless data processing, Amazon DynamoDB for scalable cloud based data storage, Amazon S3 for secure report storage, Amazon EventBridge for automated scheduling, and Amazon CloudWatch for real time monitoring. Sales transaction data stored in DynamoDB is automatically processed by Lambda functions that generate structured CSV reports uploaded to S3 at scheduled intervals. The proposed system eliminates manual reporting overhead, reduces infrastructure costs, and provides a scalable, reliable, and cost effective solution for real world data aggregation and business reporting requirements.

Keywords: AWS Lambda, Serverless Computing, Amazon DynamoDB, Amazon S3, Cloud Computing, Data Aggregation, Automated Reporting, Amazon EventBridge, Python.

Downloads: | DOI: 10.17148/IJARCCE.2026.15306