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Big Data for Lawyers: How to Use and Regulate?

https://doi.org/10.17803/2313-5395.2020.1.13.079-095

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Abstract

This paper is a research on using a big data analysis for lawyers, attorneys and law firms. Big data is a new gold — has been noticed in media and many conferences. Today big data is driven by digital transformation. It helps to analyze a huge amount of data, creates opportunities for increasing performance and gets competitive advantage for private and public sector.

A legal regulation of big data is still under the question in many countries. The main aspect and confusion are privacy concerns. Meanwhile, big data analysis actively used by governments, private and public market players. The market offers different legal tech innovations,  software  for  analyzing  big  data  and  methods  that we  review  in  the  article.  Interestingly,  there  are  different  tools and application of big data for lawyers; and this what each legal professional must know.

In this paper we are observing some aspects of using big data analysis for legal ndustry and discussing issues of legal regulation. We provide some practical ways on application of big data analysis for legal professionals. Some insights in this article adopted from author’s previous research made during the study in the Maastricht School of Management based in the Netherlands. The research is partly published in the Second Edition of Global Legal Insights AI, Machine Learning & Big Data in 2020.

About the Author

Rustam Rafikov
Rafikov & Partners Law Firm
Russian Federation

Master of Laws (LL.M at the University of Manchester), currently EMBA at the Maastricht School of Management (the Netherlands), Managing Partner at Rafikov & Partners Law Firm, a member of Moscow City Council Working Group on Blockchain and cryptocurrency regulation.

Bolshaya Pochtovaya St., 26V s. 2, Moscow, 105082. 



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For citation:


Rafikov R. Big Data for Lawyers: How to Use and Regulate? Kutafin Law Review. 2020;7(1):79-95. https://doi.org/10.17803/2313-5395.2020.1.13.079-095

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ISSN 2713-0525 (Print)
ISSN 2713-0533 (Online)