The illustrations in this book are created by "Team Educohack".
Data Privacy and Big Data: A Foundational Guide is your essential resource for understanding the importance of data privacy and its critical role in data security. As firms expand and data volumes grow, safeguarding data becomes increasingly vital. This book offers comprehensive knowledge on the subject, ensuring data is handled correctly and protected from misuse.
We begin with an introduction to data privacy, followed by chapters on machine learning, statistical learning, and the implications of data protection. The book also covers compliance tools, classification approaches for Big Data security, and the evolving landscape of user privacy and innovation.
A crucial chapter on big data privacy explores privacy models, disclosure risk measures, and data masking methods. We also delve into performance measurement of big data analytics and selecting appropriate data masking techniques. The book concludes with a compelling case study on data forensics, providing practical insights.
Data Privacy and Big Data: A Foundational Guide is an indispensable guide for anyone looking to navigate the complexities of data privacy in today's digital world.
