Adaptive Data Governance: The AT-EASE Change Management Approach - Data Governance: Creating Value from Information Assets - page 163

increase by including more detail, but by including elements that add value
to a particular inquiry (Imam, LaGoy, and Williams, 2007). Different data
governance approaches that emphasize a systemic or holistic approach
may differ widely in how they define data governance, and make dif-
ferent choices on issues and practices included in their scope. While
selecting a data governance approach, it is important to consider questions
such as: What does a given model of data governance include/exclude?
What are the implications of these boundary choices in practice?
While existing models may differ in many ways, the key d istinction for
this chapter involves the extent to which existing models of data gover-
nance incorporate the idea of helping people move from initial disequili-
brium to greater levels of AT-EASE over time. The noninvasive data
governance approach (Seiner, 2012) recognizes that data governance efforts
are adversely affected by the need for above-normal work efforts and a
command and control approach. The underlying idea behind noninvasive
data governance practices is that data governance is already embedded
in informal ways in organizations, and that formalizing and integrating
these practices results in a nonthreatening approach to data governance
implementation. The idea of at ease underlying noninvasive governance
focuses on minimizing threat. Managers and employees are more likely to
be at ease if current data governance practices are evolved gradually.
In contrast, DMBOK focuses on different areas of data management and
integrating data governance and management. DMBOK materials provide
detailed guidance on data governance and nine other disciplines:
• Data architecture management
• Data development
• Database operations management
• Data security management
• Reference and master data management
• Data warehousing and business intelligence management
• Document and content management
• Meta data management
• Data quality management
The DMBOK also includes seven environmental variables:
• Goals and principles
• Organization and culture