This paper is an attempt to enhance the existing real-time Big Data analytical architecture for remote sensing satellite application with enhancement using Social Network Data. For future work, we are planning to extend the proposed architecture to make it compatible for Big Data analysis for all applications, e.g., sensors and social networking. We are also planning to use the proposed architecture to perform complex analysis on earth observatory data for decision making at realtime, such as earthquake prediction, Tsunami prediction, fire detection, etc. Assets of real time digital world daily generate massive volume of real-time data (mainly referred to the term ―Big Data‖), where insight information has a potential significance if collected and aggregated effectively. In today’s era, there is a great deal added to real-time re mote sensing Big Data than it seems at first, and extracting the useful inform at ion in an efficient manner leads a system toward a major The computational challenges, such as to analyze, aggregate, and store, where data are remotely collected. Keeping in vie w the above mentioned factors, there is a need for designing a system architecture that welcomes both real time, as well as offline data processing. Therefore, in this paper, we propose real-time Big Data analytical architecture for processing such data environment. This paper aims to implement an intelligent architectural system to analyze and access the sensor data using Big Data analytics. As cloud resources enable the Wireless Sensor Networks to store and analyze their vast amount of data, Sensor Cloud is designed using Service Oriented Sensor Architecture. Sensor Cloud acts as an enabler for big sensor Data analytics. In the current application these three become the compelling combination. It is proposed to use the Hadoop Distributed File Systems (HDFS) concept to store the streaming sensor data on to sensor cloud for further analysis using MapReduce technique. This paper describes a public sensor cloud delivery model through cloud data analytics for sensor services. The proposed architecture acts as a Cloud Access Execution and Monitoring environment for sensor systems and is able to respond to the requested sensor client applications with greater intelligence.