2016International Journal of Automation and LogisticsRequires access

Role of big data and predictive analytics

Sneha Kumari, Yogesh Patil, Shirish Jeble

Open publisher page 11 citations

Abstract

Big data has emerged as an important area of interest pertaining to the study and research of practitioners and academicians. The exponential growth of data is fuelled by the exponential growth of various internet and digital devices. Advancement in technology has made it economically feasible to store and analyse huge amounts of data. Big data is a juxtaposition of structured, semi-structured and unstructured real time data originating from a variety of sources. Predictive analytics provides the methodology in tapping intelligence from large data sets. Many visionary companies such as Google, Amazon, etc. have realised the potential of big data and analytics in gaining competitive advantage. These techniques provide several opportunities like discovering patterns or better optimisation algorithms. Managing and analysing big data also constitutes a few challenges - namely size, quality, reliability and completeness of data. This paper provides an extensive review of literature on big data and predictive analytics. It gives the reader details of the fundamental concepts in this emerging field. Finally, we conclude with the findings of our study and have outlined future research directions in this field.

About this research paper

What this paper is about

Big data has emerged as an important area of interest pertaining to the study and research of practitioners and academicians. The exponential growth of data is fuelled by the exponential growth of various internet and digital devices. Advancement in technology has made it economically feasible to store and analyse huge amounts of data. Big data is a juxtaposition of structured, semi-structured and unstructured real time data originating from a variety of sources. Predictive analytics provides the methodology in tapping intelligence from large data sets. Many visionary companies such as Google, Amazon, etc. have realised the potential of big data and analytics in gaining competitive advantage. These techniques provide several opportunities like discovering patterns or better optimisation algorithms. Managing and analysing big data also constitutes a few challenges - namely size, quality, reliability and completeness of data. This paper provides an extensive review of literature on big data and predictive analytics. It gives the reader details of the fundamental concepts in this emerging field. Finally, we conclude with the findings of our study and have outlined future research directions in this field.

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OpenAlex reports 11 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Big data has emerged as an important area of interest pertaining to the study and research of practitioners and academicians. The exponential growth of data is fuelled by the exponential growth of various internet and digital devices. Advancement in technology has made it economically feasible to store and analyse huge amounts of data. Big data is a juxtaposition of structured, semi-structured and unstructured real time data originating from a variety of sources. Predictive analytics provides the methodology in tapping intelligence from large data sets. Many visionary companies such as Google, Amazon, etc. have realised the potential of big data and analytics in gaining competitive advantage. These techniques provide several opportunities like discovering patterns or better optimisation algorithms. Managing and analysing big data also constitutes a few challenges - namely size, quality, reliability and completeness of data. This paper provides an extensive review of literature on big data and predictive analytics. It gives the reader details of the fundamental concepts in this emerging field. Finally, we conclude with the findings of our study and have outlined future research directions in this field.

Key concepts: Big data, Data science, Predictive analytics, Computer science, Analytics, Variety (cybernetics), Field (mathematics), Data analysis

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