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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Focus Areas for Data Governance: Privacy, Compliance, Security

This type of program typically comes into existence because of concerns about Data Information Security controls, or compliance. Compliance, in this context, may refer to regulatory compliance, contractual compliance, or compliance with internal requirements.This...
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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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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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Setting Governance Roles and Responsibilities

Who does what in a Data Governance program? First, a group of individuals (or a hierarchy of groups) representing a cross-section of stakeholder groups makes a set of rules in the form of policies, standards, requirements, guidelines, or data definitions. (Or, they...
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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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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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Working with Data Stewards

Approaches to Assigning Data Ownership and Stewardship Organizations can take multiple approaches to assigning Data Owners and Data Stewards for enterprise data. In doing so, they need to consider several factors and answer the following questions.Question #1:  Should...
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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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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...
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Dealing With Politics

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.

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