PRESERVING DATA PRIVACY IN AN ERA OF BIG DATA ANALYTICS

Priyanka R. Dodake; Mr. Lowlesh Yadav; Mr. Vijay M. Rakhade

doi:10.59367/w1t2c855

Authors

Priyanka R. Dodake Department of Computer Science and Engineering, Technology, Shri Sai, College Chandrapur, India
Mr. Lowlesh Yadav Department of Computer Science and Engineering, Technology, Shri Sai, College Chandrapur, India
Mr. Vijay M. Rakhade Department of Computer Science and Engineering, Technology, Shri Sai, College Chandrapur, India

DOI:

https://doi.org/10.59367/w1t2c855

Keywords:

data analytics, GDPR, CCPA, anonymization, homomorphic encryption

Abstract

In the age of big data analytics, where organizations harness the power of vast and diverse datasets to gain insights and make informed decisions, the preservation of data privacy has emerged as a paramount concern. This research paper delves into the challenges and strategies for preserving data privacy in the context of big data analytics. As the volume of data continues to grow exponentially, concerns related to data breaches, unauthorized access, and misuse of personal information have become increasingly prevalent. The paper begins by establishing the significance of data privacy within the realm of big data and outlines the associated challenges.

This work explores the landscape of data privacy regulations and laws, both in the United States and internationally, emphasizing the role of regulations such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) in shaping data protection practices. Furthermore, it discusses a range of privacy-preserving technologies and methodologies, including encryption, anonymization, homomorphic encryption, and differential privacy, and evaluates their effectiveness in safeguarding data privacy.

Real-world case studies are examined to illustrate the practical application of data privacy principles in big data analytics. These case studies demonstrate the evolving approaches and solutions implemented by organizations to protect the privacy of sensitive data in a big data context. Ethical considerations are also addressed, highlighting the trade-offs between data utility and data privacy, as organizations strive to balance the two.

In conclusion, this research paper emphasizes the growing importance of data privacy in the era of big data analytics. It calls for continued research and implementation of robust data protection measures and the need for businesses, organizations, and policymakers to prioritize data privacy in the face of ever-increasing volumes of data. Understanding and addressing the challenges and solutions in preserving data privacy within big data analytics is vital not only for compliance with existing regulations but also for building trust with data subjects and the general public.

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