Secure Data Analysis and Data Privacy

Abstract

A secure data system is an essential tool for the performance and stability of any enterprise. Data loss, theft, or contamination might have severe consequences on an entire enterprise’s activities. Enterprises utilize secure data analytic tools to prevent, tackle, and recover from data breaches prevent such occurrences. The nature of the breach or the analysts’ objectives determines the methods through which the tools are deployed. Different organizations implement different strategies to secure their data. The strategies provide long-term solutions and must be carefully constructed. This chapter includes dissecting the concepts of data, data analysis, data security, and data privacy and how they interact. The information is developed in a systematic format where one concept leads to the next. This chapter discusses the leading data analysis strategies, types, methods, and tools currently utilized in data analysis and how they fit with contemporary computing technologies. This chapter summarizes effective data security types, strategies, and methods, showing situations in which, each can be utilized. Also, we project the relationship between data security processes and contemporary issues within the organizations and on advancing global patterns. The patterns include advancements in AI, cloud technology, and quantum adoption. This chapter includes a discussion on data privacy and how it compares with data security. The content information aims to inform the essence of data protection and guide on ways to deal with oncoming threats to the data.