— A Cloud is expanding from application aggregation and sharing to data aggregation and utilization. To make use of data tens of terabytes and tens of beta bytes of data to be handled. These massive amounts of data are called as a big data. Range-aggregate queries are to apply a certain aggregate function on all tuples within given query ranges. Fast RAQ first divides big data into independent partitions with a balanced partitioning algorithm, and then generates a local estimation sketch for each partition. When a range-aggregate query request arrives, Fast RAQ obtains the result directly by summarizing local estimates from all partitions & Collective Results are provided. Data Mining can process only Structured Data only. Big Data Approach is spoken all over the Paper. They insist of Three Tier Architecture, 1. Big Data implementation in Multi System Approach, 2. Application Deployment - Banking / Insurance. 3. Extraction of Useful information from Unstructured Data. We implement this Project for Banking Domain. There will be Two Major Departments. 1. Bank Server for Adding New Clients and maintaining their Accounts. Every User while Registration has to provide their aadhar card as a ID Proof to create Account in any Bank. 2. Accounts Monitoring Sever will monitor every users and their Account Status in different Banks. This Server will retrieve users who maintain & Transact more than Rs. 50,000 / Annum in all 3 Accounts in different Banks using the same ID Proof. Map & Reduce is achieved.