James (Jim) Love

There is no "coasting" in data governance (DG). One must be focused on incremental improvements or the data governance is in decline. Is there a point where the DG programs move to a purely maintenance mode? No. New initiatives for improvement may scaleback however improvements in cost effectiveness of maintenance will then become the primary goal once the organization as reached a high level of data maturity.

Understanding human dynamics is critical in data governance. We talk about building trust as key to community, but then forget that it takes time and intentional work. Relationship building takes time but will pay off if directed toward those who are open to data governance. Remember the bell curve. At one end is the change agents and at the other end is the change resisters. In the middle is everyone else, start with the change agents and then move the needle. Eventually the team building translates into a strong enough shared vision to tackle more issues. I call it "Strategic Patience". Celebrate each success.

Governance methodology is important as is all the technical skills, however in the end, data governance is about people. Good change management skills, understand how people are motivated or demotivated, and a good dose of strategic patience. Doing everything is an ineffectual path; one must understand the culture of the organization and the people who create/gather the data, modify the data, and ultimately use the data. The data governance role is to discern what is most important for data maturity and then lead the organization towards greater maturity. It will take time and tenacity, and developing change in people's understanding so they come to value the importance of governance.

Locking down the hardware layer is the first step for data access security. Locking down the software layer through least privilege access; the defining and limiting what data they have access to is the second step. The third layer is developing a culture whereby staff appreciate and enact the best data security practices. This is done with training yet the training is moot unless it gives rise to culture; so that staff are not just following orders, but understand the fundamental importance to clients, the organization and own good security as part of their professional identity. It takes time and investment to inculcate these values. Knowledge is insufficient. The goal is formation.

Data literacy is rising, as is the uptake of technical data skills. While there is the technical evolution to consider, one must consider how people's skills and perspectives are also evolving. Initially data lakes were of interest to data scientists and enthusiasts, but they increasingly are becoming multitenant. For example, Excel was once a tool for a small group of people, but now it is a standard business skill. As people become more data literate the data lake use will increase. As people discover what a data lake can do they will need support to utilize these expectations. This people side of the data lake evolution must be considered in order to maximizing its value.