For the past 3 decades, data security researchers have been exploring and focusing on the aggregation and inference issue. Privacy and security, issues emerged due to the retention, manipulation, storage, and collection of data. For instance, the Identification of an individual can be done even if any information that has been identifiable personally has already been excluded from the data is combined with other data. Along with secure data management, this issue is escalating. As various resources of data are present that are relational to different individuals.
Secure Data Management
Privacy and security issues and concerns are led by a huge collection of data. This indeed results in explosions of analytics of big data in cybersecurity. For example, companies may choose to outsource certain activities such as insider threat detection or cloud and malware analysis, due to the large amounts of data involved and the need for specialized analysis.
The apparent question is whether security issues can be resolved through techniques related to analytics and the development of management of big data. As one of the highly important assets of an organization is its data.
Therefore, understanding the outs and ins of data management is essential for creating a completely data-focused company. Moreover, the wisdom for correct actions and decisions and the foundation of knowledge and information of business is the data.
An organization can only grow when its data is actionable, meaningful, accurate, complete, and relevant. In case it is not then it will only result harmful to the company. Thereby, for enhancing the information and data quality, initiatives of data management must be considered by companies.