Issues and Challenges in Convergence of Big Data, Cloud and Data Science

Big data, Cloud Computing and Data Science are currently trending in organizations across the globe. Big Data refers to technologies and techniques that involve data that is massive, heterogeneous and fast-changing for conventional technologies, skills and infra-structure to address efficiently. Cloud Computing is a paradigm that provides dynamically scalable and virtualized resource as a service over the Internet. The need to store, process, and analyze large amounts of data is making enterprise customers adopt cloud computing at scale. Cloud enables users to perform advanced analytics with big data. Data Science is a field that comprises of everything that related to data cleansing, preparation, and analysis. It is the umbrella of techniques used when trying to extract insights and information from data. Big Data Analytics the science of examining big data with the purpose of drawing conclusions and inferences. It is a subset of data science. Big data analytics is unimaginable without cloud in the current scenario. This paper discusses the convergence of big data, cloud and data science. It also identifies various issues in Big Data, Cloud, Data Science and their convergence.