Big data and analytics: issues, challenges, and opportunities

Abstract

Big data refers to the large heterogeneous data, being generated at a brisk rate, which cannot be stored or analysed using conventional methods. Big data requires reliable, fast, and distributed storage and access of voluminous data for which several data storage and access mechanisms are evolving. The variety, or heterogeneity, of data requires developing models that allow for a meaningful integration of data existing in disparate data sources. The velocity or rapid rate with which Big data is generated requires real time storage and processing models. Further, veracity or trustworthiness of data poses a major challenge with regard to volume, variety and velocity. Big data analytics, which adds value to Big data, has opened many challenges that are data centric, architectural and analytics-related. This paper discusses the issues related to Big data and its analysis, its challenges and its opportunities.