Customer 360 - BigData Mini Project :• Developed a proof of concept to showcase the power of Big data in optimizing complex joins and group bys.• Utilized Hive, HBase, and Sqoop to significantly reduce the time it takes to perform these operations from hours to just a few minutes, depending on the size of the table.• Demonstrated how Big data technologies can help businesses analyze and make sense of large volumes of data in real-time, leading to more informed decision-making and better business outcomes.• Collaborated with a team of professionals to successfully implement the proof of concept, showcasing the potential of Big data in optimizing data processing and analytics.Credit Card Fraudulent Detection System :• Led the development of a prototype for a credit card fraudulent detection system using HBase, Hive, Sqoop, Kafka, and Spark.• Utilized Big data technologies to design and implement an efficient and scalable solution for detecting fraudulent activities in credit card transactions.• Conducted extensive data analysis and utilized data visualization techniques to identify patterns and anomalies in large volumes of credit card transaction data.• Implemented real-time data processing using Kafka and Spark, allowing for immediate detection and response to potential fraudulent activities.• Utilized HBase and Hive to store and analyze large amounts of data efficiently, ensuring high performance and scalability of the system.• Successfully delivered a functional prototype that demonstrated the potential of Big data technologies in detecting credit card fraud and mitigating risks for financial institutions.