EventsMOL2NET'21, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 7th ed.
Published
This submission belongs to the session 01. USE.DAT-07: USA-Europe Data Analysis Trends Congress, Cambridge, UK-Bilbao, Basque Country-Miami, USA, 2021 of the event MOL2NET'21, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 7th ed.
Published date
13 Jun, 2021
Citation
Ajit Singh, Sultan Ahmad, Data Lakes Technologies and It's Significant Implementations, in Proceedings of MOL2NET'21, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 7th ed., 25 January–30 December 2021, MDPI: Basel, Switzerland, doi: 10.3390/mol2net-07-10308
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Data Lakes Technologies and It's Significant Implementations

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1. Patliputra University, India, India
2. Department of Computer Science, College of Computer Engineering and Sciences, Saudi Arabia
Abstract

This exploratory research of data lakes in big data times is a prominent topic for both academia and industry. One of the main motivations behind is that companies need to cope with more data than ever before, and the problems of how to analyze even how to store data are becoming more and more challenging in many industries. The occurrence of the concept of a data lake to meet such big data problems is enlightening and will most likely be considered in any relevant big data strategy. This idea is still on the way to prove itself out and inevitably it gives rise to much attention as well as much criticism. Luckily, more and more positive voices towards data lakes are emerging and give highly appreciation to the concept and even propose some workable and innovative suggestions to make improvement to the practical implementation. This study introduced basic background information of data lake implementation and can give valuable suggestions and insights to practitioners. After presenting and summarizing most of the popular implementation of data lakes from data professionals, three different approaches were introduced. All of these approaches have both advantages and disadvantages, and companies need to consider their own business needs and requirements to make a wise choice.

Keywords
Data Lake
Implementation
Hadooo
Data Virtualization
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