Governance and Issue Resolution

Processes and Alignments

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.

Governance and Issue Resolution

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.

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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...
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Engaging Stewards and Stakeholders

It seems like there are two types of Data Governance and Stewardship programs: Thriving ones, with highly-engaged stakeholders, and Ones whose futures are in question, since stakeholders and stewards are only sporadically involved or give only weak support to the...
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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.

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Choosing Governance Models

It’s important to define the organizational structure of your Data Governance program. But before you can do that you have to define your governance model at a higher level. You need to consider what types of decisions your governance bodies will be called upon to...
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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.

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Implementing Change Management

Most organizations have string change management – or at least change control – mechanisms for technology. They usually have change management for software applications. They have change management for websites. And yet, many organizations do not practice structured...
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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.

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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...
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Focus Areas for Data Governance: Data Quality

This type of program typically comes into existence because of issues around the quality, integrity, or usability of data. It may be sponsored by a Data Quality group or a business team that needs better quality data. (For example: Data Acquisition or  Mergers &...
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Data Governance Program Phases

As you perform the activities needed to gain support and funding, remember that your program may plan to address multiple focus areas. Each new effort should be introduced using the seven steps of the life cycle. Even specific governance-led projects, such as creating a set of data standards, will want to follow the Data Governance Life Cycle steps.

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