Abstract
The recent rapid rise in the availability of big data due to Internet-based technologies such as social media platforms and mobile devices has left many market leaders unprepared for handling very large, random and high velocity data. Conventionally, technologies are initially developed and tested in labs and appear to the public through media such as press releases and advertisements. These technologies are then adopted by the general public. In the case of big data technology, fast development and ready acceptance of big data by the user community has left little time to be scrutinized by the academic community. Although many books and electronic media articles are published by professionals and authors for their work on big data, there is still a lack of fundamental work in academic literature. Through survey methods, this paper discusses challenges in different aspects of big data, such as data sources, content format, data staging, data processing, and prevalent data stores. Issues and challenges related to big data, specifically privacy attacks and counter-techniques such as k-anonymity, t-closeness, l-diversity and differential privacy are discussed. Tools and techniques adopted by various organizations to store different types of big data are also highlighted. This study identifies different research areas to address such as a lack of anonymization techniques for unstructured big data, data traffic pattern determination for developing scalable data storage solutions and controlling mechanisms for high velocity data.