There’s an old adage: You can’t manage what you don’t name. And then there’s its corollary: You can’t manage well what you don’t define explicitly.

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 Data Governance

And so, as you choose words to go into the definition of your program, consider the people you need to manage. In performing Data Governance activities, what details will they focus on? Do they have a strategic or tactical perspective? Are they more comfortable with business or technical terminology?

Consider, for example, the definition of Data Governance introduced by the Data Governance Institute:

“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 when, under what circumstances, using what methods.”

 

This is a general, all-purpose definition of Data Governance, focused at the mid-level managers who must come together to make cross-functional decisions, set policies, and execute on it.

It’s a little long, I confess. It highlights the “rules of engagement” components of the DGI Data Governance Framework. Why? When it was written and published, we wanted to provide an alternative to definitions that focused on authority and control structures, since we thought those definitions might not be accepted well in consensus-based cultures. .

Now look at some of the following definitions. Can you see how the way Data Governance is defined might influence how it is executed? Can you tell from the definitions whether it is aimed at executives, middle managers, or individual contributors? Can you guess what types of changes (to the organization, to processes, to power/authority structures, to data/metadata are being supported by Data Governance?

 

Data governance (DG) refers to the overall management of the availability, usability, integrity, and security of the data employed in an enterprise.

Source: searchdatamanagement.techtarget.com/sDefinition/0…

Data governance is the practice of organizing and implementing policies, procedures and standards for the effective use of an organization’s structured/unstructured information assets.

Source: www.sdn.sap.com…

Data Governance: The execution and enforcement of authority over the management of data assets and the performance of data functions.

Source: www.tdan.com/view-articles/5037

Data governance is the decision-making process that prioritizes investments, allocates resources, and measures results to ensure that data is managed and deployed to support business needs.

Source: www.b-eye-network.com/view/8393

Read Next:

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…

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.

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...

Starting a Data Governance Program

A successful Data Governance program does not begin with the design of the program! Before you start deciding who goes on what committee, you should be clear about your program’s value statement. You should have developed a roadmap to share with stakeholders. Those...

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...

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...

Governance Communications

At a Data Governance Conference in Orlando, Florida (USA), a group of managers of successful Data Governance programs reached a startling consensus: They agreed that Data Governance is actually somewhere between 80 and 95% communications!How can this be? They said...

Goals and Principles for Data Governance

What do you want Data Governance to accomplish?  Regardless of the focus of your program, chances are you hope to accomplish the following universal goals for Data Governance programs: Goal – Enable better decision-making Goal – Reduce operational friction Goal –...

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: Data Warehouses and Business Intelligence (BI)

This type of program typically comes into existence in conjunction with a specific data warehouse, data mart, or BI tool. These types of efforts require tough data-related decisions, so organizations often implement governance to help make initial decisions, to...