A Review on Big Data Challenges and Techniques Used to Overcome from IT

In todays era of software industry big data is a common term used in each and every field. As the name suggests big data means large or vast amount of data which are either in the form of structured, unstructured or in semi-structured format. The major sources of big data generation are social media data, search engine data, Black box data etc. Now-a-days big data is generally used in different domains for decision making process, Hence analyzing big data is a biggest challenge in trending time and different researches are going on how to analyze and process big data so that it can be used in different application domains for decision making process. This paper provides a summary about different challenges that are generally associated with big data analysis process and different application of big data in different domains of software industry. This paper also provides a basic description of different framework which is generally used to process the big data. The main aim of this paper is to find out some optimization techniques to overcome from different challenges which are occurred during big data analysis process. In general optimization means to get the possible results under the given circumstances and big data optimization means to optimize the analysis process of big data.