Big Data Analytics and Security Over the Cloud: Characteristics, Analytics, Integration and Security

Abstract

Big Data is a term used to refer to massive amounts of data, which is complex and obtained from a variety of sources. This type of data is large-scale, growing exponentially with time, and adds a substantial value if analyzed properly. It can be characterized using the 5 Vs of Big Data. Deriving meaningful insights and correlations to enable intelligent decisions is done via the process of Big Data Analytics (BDA). Big Data Analytics can thus help an enterprise cut costs, increase efficiency, focus on local preferences and improve sales. Many industries such as healthcare, finance, advertising, banking and security benefit from BDA. The emergence of big data has made it disadvantageous for corporations to store such large amounts of data in silos. Cloud computing provided a stable and established alternative, enabling remote access to data, faster crunching of large volumes of raw data and reliable storage of the data and the analysis. Therefore it emerges as the perfect complement for big data. Despite the benefits, there exist some security concerns that are not uncommon in applications of cloud computing. This chapter begins with an introduction of Big Data, including its advantages, followed by Big Data analytics, its relationship with Big Data and its benefits and barriers. We also analyze challenges in Big Data such as data storage, computational complexities and information security. This chapter discusses the relationship between Big Data analytics and the Cloud, including cloud services used in BDA. We also discuss future research areas such as high-speed processing accompanied with elevated performance and exalted throughput in BDA.