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AnnotatedBibliography-DataGovernance.docxRunning head: ANNOTATED BIBLIOGRAPHY
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Annotated Bibliography- Data Governance
Annotated Bibliography
Data Governance
Chalker, A. (2014). Data Governance Overview. Powerful Insights, Proven Delivery. Risk & Business Consulting Internal Audit. Available at https://www.isaca.org/chapters3/Atlanta/AboutOurChapter/Documents/GW2014/Implementing%20a%20Data%20Governance%20Program%20-%20Chalker%202014.pdf
Anthony Chalker, the author, is a Managing Director of Proviting, a risk and business consulting organization. He defines what data governance is and states that it is the specification of decision rights and an accountability framework that encourages good behavior in handling of information. The author further helps us understand that data governance is an integration of data warehousing, risk management, risk management, data security, policies and procedures, business process management as well as organizational integration. This source is relevant as it helps us identify where data governance can be applicable. It also shows organizations how they can get started with data governance.
Nelson, S. G. (2015). Getting Started with Data Governance. Thotwave Technologies, Chapel Hill, NC. Paper 1886.
This paper presents a summary of what data governance is, as well as its role. It also provides a practical guideline on how to guild a governance capability that is appropriate to the purpose, size and scale of the enterprise. Best practices are discussed as well and the author focuses on the organization, its people, culture, policies and technology. This is important as organizations have only recently started to understand the need to have programs that manage the concerns related to quality, access, provenance, usability and sharing of information assets. With the increasing consumption of data by organizations, this paper informs on the best practices.
Sun, H. (2014). Enterprise Information Management: Best Practices in Data Governance. An Oracle White Paper on Enterprise Architecture.
The author points out that data governance is one of the most pertinent components of any Enterprise Information Management as it is connected to all other data management functions. Recommendations are offered suggesting that the best practices of data governance are those that help identify the right amount of control. The foundation of any kind of governance is a certain amount of control. Also, an interactive approach helps to mitigate any execution of risks and the enterprise is able to focus on the right levels of controls to manage its information assets. There need to be different focuses and styles of data governance so as to meet the specific requirements.
Thomas, G. (2014). The DGI data governance framework. The Data Governance Institute, Orlando, FL (USA). http://www.datagovernance.com/wp-content/uploads/2014/11/dgi_framework.pdf
The author presents a designed framework for data governance that can assist an organization with a number of things. Among them are data clarity, creating a clear mission, ensuring there’s value in efforts, maintaining focus and scope, establishing accountabilities as well as defining the measurable achievements. The paper describes the main concepts and components of the DGI Data Governance Framework and the general steps towards implementing the program. Although data governance can mean different things to different organizations, the framework provided is important as it helps enterprises to organize and communicate the complicated concepts which helps the people get more clarity of thought and purpose.
Woody, T., & Felty, A. (2016). Data Governance Overview. Office of Management and Enterprise Services Data Governance Program Office, Oklahoma. Retrieved from https://www.ok.gov/cio/documents/DataGovernanceOverview.pdf
The author, Autumn Felty is a data governance program manager while Tonette Woody is a data stewardship facilitator. They identify that data governance programs should have a specific focus which should keep changing with time. This helps an enterprise to set and prioritize objectives, develop a clear path to achieving these goals and mature. They present us with some possible areas of focus such as data quality, management support, business intelligence, as well as privacy, security and compliance. The page gives us an overview of what data governance is and emphasizes that it is the practice of making effective and strategic decisions concerning an entity’s data assets.
