Architecting Real-Time Big Data Analytics: An AWS-Powered Framework Integrating AI and ML for Predictive Insights

Sai Tarun Kaniganti

Abstract: In the digital era, data generation from various sources such as IoT devices, social networks, and transactions has significantly increased, necessitating efficient management solutions. AWS offers a comprehensive real-time data analytics system incorporating Amazon Kinesis, Amazon S3, Amazon DynamoDB, and Amazon SageMaker to handle this influx effectively. By utilizing these tools, organizations can process and analyze data in real-time, aiding in immediate decision-making crucial for sectors like finance, manufacturing, and retail. The integration of AI and ML enhances predictability, allowing for advanced data analysis and timely insights, which improves operational efficiency and customer experience. This architecture includes layers for data ingestion, processing, storage, machine learning integration, and visualization, all designed to support scalable and real-time data analytics. The frameworks implementation has demonstrated significant improvements in operational responsiveness and decision-making speed, proving essential for maintaining market competitiveness and fostering innovation.

Keywords: real-time data analytics, AWS, big data management, AI integration, machine learning