Data Security and Governance in Business

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Table of Contents

Literature Review
Summary
References

The topic for the final paper is Data Security and Governance. As long as at present, information technologies (IT) have embraced all sectors of the economy; for most companies, data becomes one of the principal resources, the preservation and proper disposal of which is of crucial importance for business development and reducing the level of various risks. Therefore, data security is becoming an urgent problem for an enterprise. The purpose of the final paper is to examine how businesses can ensure complete and reliable information security. Data governance is a new concept, as the IT sphere is growing; therefore, the research is accompanied by data limitation and a lack of theoretical background.

Literature Review

The articles served as a basis for the paper to illustrate the profound analysis of cloud and non-cloud data governance. Abraham et al. (2019) analyze the conceptual framework dimensions for data governance. However, the topic remains an under-researched area in terms of inter-organizational relationships. The study conducted by Al-Ruithe et al. (2019) provides methodical literature reviews. Al-Ruithe et al. (2019) present a systematic and accurate approach to explaining state-of-the-art investigation of data governance. These sources offer the fundamental and relevant knowledge of data security and data governance in organizations.

Summary

First, it is needed to clarify the term “data governance” and its importance in the business context in the 21st century. Hence, irrelevant literature should be eliminated, which might confuse the concept of data governance (Al-Ruithe et al., 2018). Whereas the difference between data management and data governance might be unclear, the latter is high-level planning and control over data management (Al-Ruithe et al., 2018). Such aspects as confidentiality, integrity, and availability are presented through the examples of global organizations. Moreover, there are various challenges companies face when implementing data governance in the cloud. The issues can be divided into technological, legal, and business — numerous threats, divided into several categories by their origin (Al-Ruithe et al., 2018). For instance, internal threats occur within the enterprise and external ones that originate outside the enterprise’s IT infrastructure (Al-Ruithe et al., 2018). Therefore, one of the paper’s objectives is determining what data governance is and what it controls.

Furthermore, the paper explains companies’ mechanisms to conduct their data governance and management activities. Abraham et al. (2019) highlight four types: governance, structural, procedural, and relational mechanisms. Governance includes legal structures relating to business, IT, data management functions (Abraham et al., 2019). It also involves formal means and methods for decision-making and practices, encouraging stakeholders’ active cooperation (Abraham et al., 2019). Structural mechanisms define reporting structures, governance institutions, and accountabilities (Abraham et al., 2019). They contain functions, duties and the allocation of authority (Abraham et al., 2019). Procedural governance tools aim to ensure that data is recorded accurately, handled securely, managed effectively, and distributed appropriately (Abraham et al., 2019). Relational governance mechanisms assist collaboration within stakeholders (Abraham et al., 2019). Thus, this part of the paper distinguishes the most important elements and factors in data governance.

Concerning the potential implications of the study, further research of big data governance is required as the topic and its practical importance are understudied. As the final paper aims to assess the concept of data security and governance in enterprises, the data governance impact on companies’ performance should be examined. Therefore, it is crucial to conduct research on data quality management and analytics to optimize processes and increase business efficiency.

References

Abraham, R., Schneider, J., & Vom Brocke, J. (2019). Data governance: A conceptual framework, structured review, and research agenda.International Journal of Information Management, 49, 424-438. Web.

Al-Ruithe, M., Benkhelifa, E., & Hameed, K. (2019). A systematic literature review of data governance and cloud data governance.Personal and Ubiquitous Computing, 23(5), 839-859. Web.

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Data Security and Governance in Business

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