Data Governance_ How to Design, Deploy and Sustain an Effective Data Governance Program
Metadata
- Author: John Ladley
Highlights
“Data governance is the organization and implementation of policies, procedures, structure, roles, and responsibilities which outline and enforce rules of engagement, decision rights, and accountabilities for the effective management of information assets.” — location: 561
Data governance visibly supports MDM in several ways: 1. Ensures that standards are defined, maintained, and enforced. — location: 631
- Ensures that MDM efforts are aligned to business needs and are not technology-only efforts. 3. Ensures that data quality, process change, and other new activity that are rooted in MDM are accepted and adapted by the organization. — location: 632
Data quality is probably the single most discussed term or concept in the EIM/DG universe. This is easy to comprehend once you understand what it really represents. Data quality is simply the root cause of the majority of data and information problems. Remediating data quality is one of the main drivers of data governance and MDM. — location: 635
Never say “better decisions” or “better data quality” as business vision statements. These are not business statements. — location: 1133
Frankly, if an organization has to debate if DG is “required,” or it has to test the legitimacy of the concept, it does not understand what DG is. We have dealt with too many companies where an executive has told the nascent DG team to “do a proof of concept.” When we hear that, we embark upon education, not selling. “Proving governance” is akin to asking the accounting area to rejustify double-entry bookkeeping. Governance is a required function that most organizations embrace comfortably. Anyone asking for a proof of concept either does not get it or is erecting barriers. — location: 1257
The successful deployment of DG will be viewed as yesterday’s news unless it is kept visible (and someone important gets credit for its success), and that is the purpose of the sustaining phase. We approach the planning and rollout of DG with the viewpoint that modern organizations, especially modern corporations, have the attention span of a two-year-old. This may or may not be true, but it helps with the planning. — location: 1604
In essence, once you have started to sustain DG, it never stops. Until DG is totally internalized, which may take years, there will be the need to manage the transformation from non-governed data assets to governed data assets. — location: 1610
There are three core success factors we want to make sure are identified at this point: 1. DG requires culture change management. By definition, you are moving from an undesirable state to a desired state. That means changes are in order. 2. DG “organization” is not a stand-alone, brand-new department. Ideally, in most organizations DG will end up being a virtual activity. 3. DG, even if started as a stand-alone concept, needs to be tied to an initiative. — location: 1644
Figure 6-1 and Figure 6-2 show the details and flows of the DG “Scope and Initiation” phase. Please do not assume this is a casual exercise. In our practice, the typical program/project plan deliverable from this phase averages 400 tasks. We have produced DG deployment plans that span three years and contain nearly 1000 discrete tasks. You may not follow each and every task, but you need to comprehend the amount of activity that can possibly take place, and how the workload will be addressed. Hence, the quote at the beginning of the chapter the planning activity sets the tone and the d team. Perhaps the most well-planned activity in history was the Operation Overlord invasion of Europe (sometimes referred to as D-Day). That event took two years to plan. The invasion was successful, but the plan was quite fluid once the event started.1 Therefore, the plan itself will change over time, but the focus and artifacts will help sustain the DG effort. — location: 1664