Are you interested to compare data management and data governance?

Recently, I have been exploring the concept of Yin and Yang: a ’concept of dualism […] describing how seemingly opposite or contrary forces may actually be complementary, interconnected, and interdependent in the natural world, and how they may give rise to each other as they interrelate to one another1. I decided to check whether such a Yin – Yang dualism exists between the concepts of data governance (DG) and data management (DM). The answer is not as obvious as you might expect, as everything depends on the context in which you put these two concepts, their definitions, and specified relationships between them.

I will do my best to explain it in the ‘Data Management & Data Governance 101’ article series. In this series, I will:

…show how definitions of data governance and data management and the relationship between them change in different contexts

…demonstrate differences of these concepts in the two most known industry reference guides: DAMA-DMBOK2 and DCAM

…share my vision on the definitions of data governance and data management and their relationships and deliverables.

Let’s start with the first topic and look at business definitions of ‘governance’ and ‘management’ in different contexts.

Data governance and data management definitions and their relationships vary in different contexts.

‘Governance’ and ‘management’ in the semantic business context.

Even though in daily (business) life, ‘governance’ and ‘management’ are often used interchangeably, linguistically they are not synonymous. The Merriam Webster dictionary defines ‘management’ as ‘the conducting or supervising of something (such as a business)’2, while ‘governance’ is associated with ‘governing’ which is ‘to exercise continuous sovereign authority’ or ‘to prevail or have decisive influence: control’3.

Also, provides very similar definitions.

Management is the organization and coordination of the activities of a business that are needed in order to achieve defined objectives.4

Governance is the establishment of policies, and continuous monitoring of their proper implementation, by the members of the governing body of an organization.5

Now, let us see how these definitions work in the data world.

Data governance, as a “sovereign authority”, specifies WHY and HOW data assets and their life cycle should be organized. Governance does it by setting up a framework and defining rules in the form of policies and procedures. Then data governance controls the implementation of these policies in practice.

Data management specifies WHAT should be done to conduct maintenance of data assets and their lifecycle according to the policies within the specified framework. Then data management conducts and supervises the data lifecycle operations.

Here is an illustration of all said above regarding data management and governance:

Figure 1. ‘Management’ and ‘governance’ in the semantic business context.

Now let’s check what the most known and widely used industry reference guide DAMA-DMBOK says on the subject.

‘Governance’ and ‘management’ in the context of DAMA-DMBOK.

Data governance

DAMA-DMBOK, Data Management Body of Knowledge by DAMA International, is the most known and widely used data management industry guide. DAMA-DMBOK consistently provides the same definition of data governance in its first and second edition, as well as in the Data Dictionary:

‘Data governance is the exercise of authority, control, and shared-decision making (planning, monitoring, and enforcement) over the management of data assets’6.

Data management

DAMA-DMBOK is less consistent with the definition of data management in different editions.

The second edition of DAMA-DMBOK provides the following definition:

‘Data management is the development, execution, and supervision of plans, policies, programs, and practices that deliver, control, protect, and enhance the value of data and information assets throughout their lifecycles’7.

DAMA-DMBOK 1 and the Data Dictionary used almost the same definition with a significant difference that they defined data management as a business function. For example, in the Data Dictionary, it sounds like this: data management is ‘the business function, that develops and executes plans, policies, practices, and projects that acquire, control, protect, deliver, and enhance the value of data’8.

We will not speculate on why the ‘business function’ status has disappeared in the last edition of DAMA-DMBOK as it does not matter that much in the context of our discussion. But yet, it would be an interesting question to the DAMA-DMBOK authors.

The most important point here is that the meaning of ‘governance’ and ‘management’ in the DAMA-DMBOK context differs from the common business context.

In the DAMA-DMBOK context, ‘management’ becomes accountable for the development of policies as well as supervising their execution, while ‘governance’ only controls and makes decisions about ‘management’.

Here is an illustration of the ‘governance’ and ‘management’ concept in the DAMA-DMBOK context:

Figure 2. ‘Management’ and ‘governance’ in the DAMA-DMBOK context.

Data governance exercises authority, control, and shared decision-making about data management.

Data management develops, executes, and supervises plans, policies, programs regarding the maintenance of data assets and supporting their lifecycle.

What is most intriguing about the concept of ‘data management’ in the DAMA-DMBOK context is the number of synonymous for data management. DAMA-DMBOK2 lists such terms as ‘Information Management (IM), Enterprise Information Management (EIM), Enterprise Data Management (EDM), Data Resource Management (DRM), Information Resource Management (IRM), Information Asset Management (AIM)9’.

Now let’s consider the concept of data management and data provided by another known industry guide: DCAM.

‘Governance’ and ‘management’ in Data Management Capability Assessment Model (DCAM) context.

DCAM is a methodology developed by the Enterprise Data Management Council (EDM Council). Unlike the openness and accessibility of DAMA-DMBOK, the DCAM methodology is only available to the members of the EDM Council. Therefore, all materials I use in this article are only those available in the public domain.

DCAM specifies the definition of ‘data management’ as: ‘proper data management is about managing data as ‘meaning’10. The interpretation of the word ‘meaning’ I leave to you, dear reader. I suspect the number of these defintions will be equal to the number of readers.

Data governance is specified as ‘the rules of engagement for data management, focused on the implementation of policies, standards, and operational procedures, necessary to ensure that stakeholders behave’11.  Your creativity might help you to imagine what ‘stakeholders’ behavior’ should mean.

My graphic translation of the DCAM definitions is presented here:

 Figure 3. ‘Management’ and ‘governance’ in the DCAM context.

It seems that the roles of data governance and data management in the DCAM context are similar to those in the business context (see Figure 1). There is one exception: control. From the materials available you cannot conclude whether data governance conducts some forms of control.

Now let’s make a brief summary of our analysis.


Conclusions of comparisons of ‘data governance’ and ‘data management’ in different contexts.

Even the quick analysis of two different industry reference guides shows the following:

  1. There is no clear aligned definitions of data governance and data management, their roles and relationships in the data management community.
  2. While implementing data governance and data management, every company should specify their own definitions and understanding of the role of data management and data governance and their relationships.

So, coming back to our question about Yin-Yang dualism between data management and data governance, it is obvious that these concepts are complementary, interconnected, and interdependent.

But how they give rise to each other and how they interrelate with each other depends on the context.

Stay tuned for the next article, in which we will:

…take a deeper look into differences in understanding of data management and data governance content in DAMA-DMBOK and DCAM

…discuss relationships between data governance and data management with organizational levels.




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  6. DAMA International. DAMA-DMBOK: Data Management Body of Knowledge, Second Edition. Bradley Beach, N.J.: Technics Publications, p.69.
  7. DAMA International. DAMA-DMBOK: Data Management Body of Knowledge, Second Edition. Bradley Beach, N.J.: Technics Publications, p.17.
  8. DAMA International. The DAMA Dictionary of Data Management, Second Edition: Technics Publications, 2011, p.78.
  9. DAMA International. The DAMA Dictionary of Data Management, Second Edition: Technics Publications, 2011, p.5.
  10., p.3
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