For the past 3 decades, the data security researchers have been exploring and focusing on the aggregation and inference issue. As privacy and security, issues emerged due to retention, manipulation, storage, and collection of data. For instance, Identification of an individual can be done even if any information that has been identifiable personally already been excluded from the data is combined with another data. Along with big data management, this issue is escalating. As various resources of data are present that are relational to different individuals.

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 instance, activities can be outsourced by a company like an insider detection of a threat to the cloud and malware analysis. This is due to the huger amounts that are being gathered for such applications and analysis of such data is required. The apparent question is that security issues can be resolved through the techniques related to analytics and the developments of management of big data.

It also has been found that in the modern economy, it becomes quite difficult for companies to survive who failed to understand the significance of data management. 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 decision 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 if it is not then it will only result harmful for the company. Thereby, for enhancing the information and data quality, initiatives of data management must be considered by companies.

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