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  • Continental Academy Press

    Published by Continental Academy Press, London

    Seller: Continental Academy Press, London, SELEC, United Kingdom

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    Softcover. Condition: New. Dust Jacket Condition: no dj. First. Big data analytics is a rapidly growing field, but it also presents a unique set of challenges and opportunities. Data Anonymization Methods for User Privacy in Big Data Analytics offers a comprehensive guide to building a robust and secure data anonymization posture, providing readers with the knowledge and strategies needed to protect user privacy and prevent data breaches. From data masking to data encryption, this book covers all aspects of data anonymization, offering real-world examples and expert analysis to help readers build a secure and resilient data analytics program. With its clear and concise language, Data Anonymization Methods is an indispensable resource for any data analyst looking to protect their users and prevent cyber threats. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

  • Continental Academy Press

    Published by Continental Academy Press, London

    Seller: Continental Academy Press, London, SELEC, United Kingdom

    Seller rating 5 out of 5 stars 5-star rating, Learn more about seller ratings

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    US$ 10.24 shipping from United Kingdom to U.S.A.

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    Softcover. Condition: New. Dust Jacket Condition: no dj. First. Big data analytics has revolutionized the way organizations make decisions, but it also raises significant concerns about user privacy. Data Anonymization Methods for User Privacy in Big Data Analytics provides readers with a comprehensive overview of the latest data anonymization methods and techniques, including data masking, data suppression, and data aggregation. The book examines the key challenges and risks associated with data anonymization, including data quality, data accuracy, and data consistency. Readers will learn how to identify and mitigate these risks, develop effective data anonymization strategies, and protect user privacy in big data analytics. By adopting these methods, organizations can balance their need for data insights with their responsibility to protect user privacy. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.