Q1 Chapter 10 - From this chapter, in addition to the previous Chapters, we continue to enhance our knowledge and understanding about IG best business practices, and how good data governance can ens

10 Levels of the DGI Data Governance framework

1. Mission and vision

This level includes three pats, which are proactive definition and alignment of rules, providing ongoing, boundary-spanning services and protection to data stakeholders, and effectively reacting to and resolving issues arising from non-compliance with rules (Thomas, 2018).

1. Goals, Governance Metrics / Success Measures, Funding Strategies

The determination of goals that should be pursued starts with the anticipation of the effect of governance efforts on projects, people, professional disciplines, and programs. Metrics ate developed to help those involved in data governance to know the expected success and how it will be measured (Thomas, 2018). This clarity helps in the determination of funding options.

1. Data Rules and Definitions

These encompass data-related standards, policies, business rules, compliance requirements, and data definitions. The program may focus on creating new rules, gathering existing rules, addressing overlaps and gaps, or formalizing rules.

1. Decision Rights

It is important to determine those responsible for making decisions and the process of making decisions. This is to ensure that there will be no conflicts during times when critical decisions about data will need to be made. The determination of decision rights may require more negotiation.

1. Accountabilities

The development of rules and determination of decision rights is followed by the definition of accountabilities that can be incorporated into everyday activities and the software development life cycle. This is important to ensure that those involved in data management take responsibility for their actions and decisions made.

1. Controls

It is important to note that data is always at risk, such as data breaches, which necessitates the management of data to prevent events that should not occur. Those that an organization may not be able to prevent should be detected and corrected (Thomas, 2018). Risk management strategies are made operational through the development and implementation of controls.

1. Data stakeholders

There is a wide range of data stakeholders, including those involved in the creation of data, use of data, and development of rules and requirements for data. Data stakeholders to not only affect but are also affected by data-related decisions, thus to ensure that their expectations are addressed by the Data Governance program.

1. Data Governance Office

A Data Governance Office is required to facilitate and support governance activities. The office is responsible for the collection and metrics and success measures and reporting on them to stakeholders (Thomas, 2018).

1. Data Stewards

The Data Stewardship Council comprises various data stakeholders responsible for making data-related decisions. They are responsible for setting policy and specifying standards as well as making recommendations for the Data Governance Board (Thomas, 2018).

1. Proactive, Reactive, and Ongoing Data Governance Processes

It is important to ensure that these processes are standardized, documented, and repeatable. They are developed in a way that ensures they support compliance as well as regulatory requirements for the management of data, security, privacy, and access management.

Reference

Thomas, G. (2018). The DGI Data Governance Framework. The Data Governance Institute.