Big Data: Survey, Technologies, Opportunities, and Challenges

By Nawsher Khan, Ibrar Yaqoob, Ibrahim Abaker Targio Hashem, Zakira Inayat, Waleed Kamaleldin Mahmoud Ali, Muhammad Alam, Muhammad Shiraz, Abdullah Bin Gani. 2014

528 citations recorded by the source corpus.

Big Data has gained much attention from the academia and the IT industry. In the digital and computing world, information is generated and collected at a rate that rapidly exceeds the boundary range. Currently, over 2 billion people worldwide are connected to the Internet, and over 5 billion individuals own mobile phones. By 2020, 50 billion devices are expected to be connected to the Internet. At this point, predicted data production will be 44 times greater than that in 2009. As information is transferred and shared at light speed on optic fiber and wireless networks, the volume of data and the speed of market growth increase. However, the fast growth rate of such large data generates numerous challenges, such as the rapid growth of data, transfer speed, diverse data, and security. Nonetheless, Big Data is still in its infancy stage, and the domain has not been reviewed in general. Hence, this study comprehensively surveys and classifies the various attributes of Big Data, including its nature, definitions, rapid growth rate, volume, management, analysis, and security. This study also proposes a data life cycle that uses the technologies and terminologies of Big Data. Future research directions in this field are determined based on opportunities and several open issues in Big Data domination. These research directions facilitate the exploration of the domain and the development of optimal techniques to address Big Data.

Subfields: Information Systems, Information Systems and Management

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Citations in the corpus

A Survey on Cleaning Dirty Data Using Machine Learning Paradigm for Big Data Analytics (2018, background): “There are different tools available in market to handle the big data but these tools concernts with few issues [3].”
A Big Data Analytics Method for Tourist Behaviour Analysis (2017, unknown): “Social media provides voluminous, varied and velocitous data of potential value to decision makers and is a rich source for big data [31].”
The role of big data in smart city (2016, background): “The phenomenon of big data has long been characterized by volume, velocity, and a variety of data types that have been created at everincreasing rates (Khan et al., 2014).”
Big Data technologies: A survey (2017, unknown): “The challenge in Big Data is how to manage the complexity of Big Data nature (velocity, volume and variety) (Khan et al., 2014) and process it in a distributed environment with a mix of applications.”
Barriers to the adoption of industry 4.0 technologies in the manufacturing sector: An inter-country comparative perspective (2020, background): “Furthermore, when data frequently changes and is shared with multiple collaborators, data integrity and consistency becomes a major challenge (Khan et al., 2014).”
Big Data and cloud computing: innovation opportunities and challenges (2017, background): “Finally, ensuring data consistency and integrity is challenging with Big Data especially when the data change frequently and are shared with multiple collaborators (Khan et al. 2014).”
Future Trends and Current State of Smart City Concepts: A Survey (2020, background): “The term ‘‘big data’’ is characterized by volume, velocity, and different data types [102], [103].”