2020Unpublished venueRequires access

Big Data: Current Challenges and Future Scope

Ardavan Ashabi, Shamsul Sahibuddin, Mehdi Salkhordeh Haghighi

Open publisher page 32 citations

Abstract

Big Data encompasses huge amounts of raw material which influence multitude of research fields as well as different industries performance such as business, marketing, social network analysis, educational systems, healthcare, IoT, meteorology, fraud detection. It aimed to uncover hidden trends and has prompted a development from a model-driven perspective to a data-driven approach. Among numerous properties of Big Data, datasets of Big Data are identified primary as 3Vs attributes which have high variety, velocity and volume. These provide an invaluable insight and assist in making precise decisions. Analyzing this information and outlining the outcome into helpful data is the method for extricating an incentive from these enormous volumes of datasets. Nevertheless, Big Data containing unique features that cannot be handled and processed using the conventional methods. This has presented a significant challenge to the industry. This research paper presents a general outline of the characteristics of Big Data as well as expounds on the present challenges and limitations in this area. It further discusses the future scope in particular the future direction for Big Data research.

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What this paper is about

Big Data encompasses huge amounts of raw material which influence multitude of research fields as well as different industries performance such as business, marketing, social network analysis, educational systems, healthcare, IoT, meteorology, fraud detection. It aimed to uncover hidden trends and has prompted a development from a model-driven perspective to a data-driven approach. Among numerous properties of Big Data, datasets of Big Data are identified primary as 3Vs attributes which have high variety, velocity and volume. These provide an invaluable insight and assist in making precise decisions. Analyzing this information and outlining the outcome into helpful data is the method for extricating an incentive from these enormous volumes of datasets. Nevertheless, Big Data containing unique features that cannot be handled and processed using the conventional methods. This has presented a significant challenge to the industry. This research paper presents a general outline of the characteristics of Big Data as well as expounds on the present challenges and limitations in this area. It further discusses the future scope in particular the future direction for Big Data research.

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OpenAlex reports 32 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Big Data encompasses huge amounts of raw material which influence multitude of research fields as well as different industries performance such as business, marketing, social network analysis, educational systems, healthcare, IoT, meteorology, fraud detection. It aimed to uncover hidden trends and has prompted a development from a model-driven perspective to a data-driven approach. Among numerous properties of Big Data, datasets of Big Data are identified primary as 3Vs attributes which have high variety, velocity and volume. These provide an invaluable insight and assist in making precise decisions. Analyzing this information and outlining the outcome into helpful data is the method for extricating an incentive from these enormous volumes of datasets. Nevertheless, Big Data containing unique features that cannot be handled and processed using the conventional methods. This has presented a significant challenge to the industry. This research paper presents a general outline of the characteristics of Big Data as well as expounds on the present challenges and limitations in this area. It further discusses the future scope in particular the future direction for Big Data research.

Key concepts: Big data, Scope (computer science), Data science, Computer science, Variety (cybernetics), Raw data, Incentive, Multitude

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