Planning and Prioritization in Data Governance

Planning and Prioritization in Data Governance

Data governance is a key facet of any organization; it creates frameworks for the effective, secure, and optimum utilization of information resources to enable an organization to achieve both its short and long-term targets (Abraham, 2019). It is widely acknowledged that the field of information technology (IT) is one of the most rapidly evolving sectors. Therefore, leaders in this field must be visionary, strategic, and, most importantly, flexible. It’s the responsibility of a leader to use all resources and tools available to them to drive the growth and sustainability of their organization. A data governance plan is an important management tool that leaders in the IT field can utilize to best manage enterprise data, by ensuring the quality, consistency and security of data are prioritized. A well-drafted data governance plan guides the IT team on the best approach in data management, by outlining how data will be treated, assigning duties to stakeholders and detailing a continuous policy and plans assessment. Consistently, planning and prioritization in data governance entail the strategy as mentioned earlier and the flexibility of leaders to achieve data security and protect data privacy for their organizations, as well as how these leaders go about said planning and prioritization.

By nature, IT organizations deal in data as the base currency. For this data to be useful, it has to be whole and accurate. These are tenets of data integrity – better data quality increases competitiveness (Abraham, 2019). Likewise, poor data quality hampers an organization’s goals. Therefore, leaders must implement a data governance plan that accounts for access control, storage, and transmission of data and how these can be done securely and confidentially. Additionally, this data has to be timely (Abraham, 2019), as the aforementioned rapid evolution in the industry leaves little room for slack.

The quantity of data available means that leaders are required to filter and prioritize data that is consumed with a long-term strategy in mind while at the same time facilitating day-to-day operations so the organization remains competitive in the present. A data governance plan helps lay out time frameworks within which specific data is useful and how to preserve this data for future use, as well as proper disposal of noise, especially with regards to privacy compliance such as is required by the GDPR for countries in Europe (Layton, 2017).

Leadership Roles and Responsibilities for Planning and Prioritizing

Leadership is a very important aspect of planning and prioritization in data governance. Through leadership, effective rules and regulations are developed to effectively handle any issues regarding organizational data. Various leadership roles, such as the board of management, the chief information security officer, and the system administrator, are key to this successful management and utilization of organizational data. The board of management, led by the head of the organization, is responsible for strategy development and oversight; therefore, the head of the organization is the figurehead responsible for prioritizing data governance. The role of planning falls to the chief information security officer (Abraham, 2019). They are responsible for developing and/or incorporating the data governance plan and conducting audits on the effectiveness of the said plan. The system administrator/DevOps Engineer assists the chief information security officer in creating the data governance plan and is responsible for ensuring its adherence to the daily operations of research, operations, and development for all IT activities.

Determining Priority for Data Security and Privacy

Various data levels have different security and privacy requirements. Private and confidential data requires a higher level of security and privacy compared to organizational data available in the public domain. The level of security and privacy assigned to a data level is dependent on the ramifications of this information falling into the wrong hands or being leaked to the public. Some highly critical data includes critical enterprise information and client information, including personal data and financial details. Critical enterprise information such as the organization’s core business, trade secrets, research, and development are among the most critical data and should be kept secure under the highest level of security and privacy (Al-Badi, 2018). This data-level requires the most security and least access – roles related to these factors must be strictly on a need-to-know basis. The organization also needs to store old data securely for future reference, whether or not this data might actually be revisited in the future. Leaving this data vulnerable to breaches could expose the business to competitors who are able to analyze and reverse-engineer that organization’s business or products.

Another important facet of an organization’s data is its data about its clients (Layton, 2017). The organization has a responsibility to the client to ensure that this data is used confidentially, especially with regard to personal and financial records. The highest security priorities should be given to these types of data, followed by the daily operational data and medium-term strategies.

Levels of Support

The individuals concerned with the creation and implementation of the data governance plan form the support hierarchy for successful data governance. They include the project management hierarchy, the DevOps engineer, the compliance and regulatory institutions or officials, information security auditors and the relevant individuals with access to sensitive or mission-critical data/information. Planning and prioritization dictate how these parties contribute to the conception and use of a data governance plan, their roles and responsibilities, the technology and relevant tools afforded to them, and their duty to carry out the policies and guidelines stipulated within the governance plan.

All internal levels of support defer to the head of the organization, who is held accountable for proper data governance by legal stipulations such as the aforementioned GDPR, and by audit agencies who ensure compliance with privacy and information security standards. The head has to prioritize levels of security depending on the privacy necessity of specific data and delegates the implementation of their planning to the chief information security officer, assisted by project managers and the DevOps engineer.

References

Abraham, R., Brocke, J. v., & Schneider, J. (2019). Data Governance: A conceptual framework, structured review, and research agenda. International Journal of Information Management. 49. 10.1016/j.ijinfomgt.2019.07.008.

Al-Badi, A., Tahrini, A., Khan, A. I. (2018). Exploring Big Data Governance Frameworks, Procedia Computer Science, Volume 141, Pages 271-277, https://doi.org/10.1016/j.procs.2018.10.181

Layton, Roslyn (2017). How the GDPR Compares to Best Practices for Privacy, Accountability and Trust. Available at SSRN: https://ssrn.com/abstract=2944358 or http://dx.doi.org/10.2139/

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Section 2: Planning and Prioritization in Data Governance

Use the Library or reputable sources from the internet and find at least three references on the topic of planning and prioritization as a leader in the IT field. Respond to the following:

Planning and Prioritization in Data Governance

Based the research you do and any leadership experience you may have, compose a minimum 2-page, double-spaced research paper using the current APA version with a title page and reference page.

Given today’s work environment, particularly with professions dealing with data governance, discuss how a leader’s planning and prioritization can help achieve data security and protect privacy using a data governance plan. What leadership roles and responsibilities are most important for planning and priorities in data governance? How do you decide what is a higher priority for data security and privacy? What level of support is needed for successful data governance, and how do planning and prioritization help achieve that?

Your paper needs to include a title page and follow current APA formatting guidelines.