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There are several different ways to connect people in and around the world. One such way is the use of internet and interactive communication tools (ICT) such as smart phone, tablet, electronic devices and voice assistant. Each and every second large volume and variety of data will be generated by these devices. This kind of large volume with varying speed and variety of data is called big data. Analyzing and identifying the intelligent pattern from this data is called big data analytics. Several different data analytical methods are used to classify and identify the hidden patterns from the raw data. Data is scattered in different systems in different places. Hadoop is the open source platform for processing such distributed data. Hadoop uses the HDFS and map reduce to do distributed computation in secured way. Even though hadoop and map reduce will impose securityin its own way, the data collected and processed need more secured methods to prevent the data leakage. There are several different methods, tools and techniques available to impose the security and prevent the privacy of any user’s identity. This paper will provide the overall view about the challenges faced during the data storage, data generation and processing in distributed and cloud environment. This paper is divided into 4 sections. Introduction part of map reduce, related works and challenges and vulnerability of data security are discussed in first and second sections. Different techniques used to impose the security is analyzed in the third section and fourth section is the conclusion

Analyzing Various Techniques to Safeguard user Sensitive Data