This repository showcases a Medallion Architecture Data Lakehouse designed for both batch and real-time processing of e-commerce and marketing data. It supports comprehensive data analysis, reporting, and monitoring, providing a scalable solution for deriving insights from integrated datasets.

This project simulates a real-world enterprise data migration and modernization strategy. It extracts transactional data from a simulated "On-Premise" environment (hosted on AWS EC2), performs heavy distributed processing using a Hadoop/Spark cluster, and ultimately serves the data via a Cloud-Native, serverless architecture to optimize costs .

This project demonstrates the process of extracting data from a MySQL database, transferring it using Apache Sqoop, storing it in Hive Data warehouse (the data actually is store in Hadoop Distributed File System (HDFS)), and performing analysis using Hive Query Language (Hive QL) (it is a language close to SQL). Then visualize the data in Power BI,

My Tasks at Big Data Training At Samsung innovation Campus

Analyze over 2.5 million ATM transaction records from Spar Nord Bank to optimize ATM usage patterns and enhance customer service using AWS Services and Big Data Analytics.