One of the three most important jobs of a Data Governance program is to help resolve data-related issues. These may be conflicting data definitions, data usage concerns, or problems with how data is sourced, how it is integrated, how it is protected, or a myriad of other issues.

Data Governance programs are generally structured to allow an orderly and predictable issue escalation path for data issues that pulls together the right stakeholders at the right time with the right research and analysis, so they can make a decision that is right for the enterprise.

The DGI Data Governance Framework includes “Resolving Issues” as a key Governance process. Of course, every organization will decide how much structure and formality to bring to the process of resolving data-related issues.

Ideally, this process should be standardized, documented, and repeatable. It should be crafted in such a way to support regulatory and compliance requirements for Data Management, Privacy, Security, and Access Management. Record-keeping should provide a clear history of which stakeholders were involved in resolving an issue, what resources/analysis were used, and what alternatives were considered.

It’s essential that Data Governance and Stewardship program facilitators avoid being “caught up” in politics. It’s our jobs to acknowledge the realities of the situations we work with, while avoiding taking sides or engaging in behaviors that could be perceived as favoring one set of data stakeholders at the expense of others.

Establishing a Data Governance Office

Most organizations that begin a formal Data Governance and Stewardship effort need a support team to facilitate and coordinate activities of councils, stewards, and stakeholders. This support team may be individual contributors who have been doing this work informally...

Governance and Decision-Making

Remember our (long) definition for Data Governance? “Data Governance is a system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, and...

Demonstrating Value

Everything an organization does should tie to one of three universal value drivers. Data Governance efforts MUST tie back to one or more of these drivers. And YOU must communicate how it does.

Assigning Data Ownership

One of the tenets of Data Governance is that enterprise data doesn’t “belong” to individuals. It is an asset that belongs to the enterprise. Still, it needs to be managed…

Focus Areas for Data Governance: Policy, Standards, Strategy

This type of program typically comes into existence because some group within the organization needs support from a cross-functional leadership body. For example, companies moving from silo development to enterprise systems may find their application development teams...

Defining Data Governance

How you define your program will influence your ability to manage it — to keep all participants on focus, in sync, and striving toward the same goals.

Defining Organizational Structures

There is no single “right” way to organize Data Governance and Stewardship. Some organizations have distinct Data Governance programs. Others embed Data Governance activities into Data Quality or Master Data Management programs.

Governance and Alignment

Data Governance is a balancing act. On the one hand, you need to exert control over how groups create data, manage data, and use data. On the other hand, you need to promote appropriate levels of flexibility. You need to ensure that data-related efforts support the...

Focus Areas for Data Governance: Management Alignment

This type of program typically comes into existence when managers find it difficult to make “routine” data-related management decisions because of their potential effect on operations or compliance efforts.Managers may realize they need to come together to make...