Amit Mitra Amit.Mitra@uwe.ac.uk
Associate Professor in Strategy & Operations Management
Big data application in manufacturing industry
Mitra, A; Munir, K
Authors
Kamran Munir Kamran2.Munir@uwe.ac.uk
Professor in Data Science
Contributors
Sherif Sakr
Editor
Albert Y. Zomaya
Editor
Abstract
Proliferation of modes of communication today also implies that people are generating a wide variety of data by themselves. At the same time the value of organisations has become increasingly dependent on the amount and type of data that it holds about its customers. So, business intelligence is today driven by accessing feedback and touch point data that is being created by customers. Manufacturing organisations are no exception to this general trend and to operate effectively need to garner supply chain and customer centric data on a vast scale. The main premise of this chapter is to illustrate the significant role of NoSQL in comparison to SQL for manufacturing organisations. Unlike traditional data that can be processed by fitting it into time tested formats like those of RDBMS, big data is incompatible with any such format. Therefore, a manufacturing organisation by its reliance on NoSQL will be able to deal with the complexities that have come about because of the growth of big data and the consequent reliance on it.
Citation
Mitra, A., & Munir, K. Big data application in manufacturing industry. In S. Sakr, & A. Y. Zomaya (Eds.), Encyclopedia of Big Data Technologies (1-7). UK: Springer
Deposit Date | Apr 12, 2018 |
---|---|
Peer Reviewed | Peer Reviewed |
Pages | 1-7 |
Book Title | Encyclopedia of Big Data Technologies |
ISBN | 9783319320090 |
Keywords | SQL, NoSQL, Big data, manufacturing industry, RDBMS, volume, velocity, variability |
Public URL | https://uwe-repository.worktribe.com/output/845827 |
Publisher URL | https://www.springer.com/gp/book/9783319320090 |
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