Change and Not Change is Ultimately Zen in Action

Attempting to be a change agent is difficult. Nonetheless, all data architects should con­sider themselves change agents for the organiza­tions in which they work. To think otherwise is to give short shrift to their occupation. Certainly, every business wants to improve and grow. But at the same time, business also wants to keep much the same. Such discoveries can be confusing when business is say­ing that change is desired, but their actions seem focused on preventing change. It can suggest the Albert Ein­stein quote (or the Baba Ram Dass quote, based on which version of history one sub­scribes to) that “We cannot solve our problems with the same thinking we used when we created them.”

Worse, change is rarely free; the more change planned, then the larger the cost—and that can be a problem when budgets are tight and human resources are scarce. These thoughts and more create interesting paradoxes for all data architects. At times, it can appear as if solutions and enhancements are being constructed upon minefields. Often work is built upon existing solutions, and there is no starting green field on which to proceed however one wishes. Wholesale change is often an opportunity rarely seen.

In most large organizations, it is typical to find current naming standards or other practices that say one thing, while simultaneously discovering many existing objects following standards that were in place at various points in time from the past. New data architects who find themselves in such surroundings can feel like archeologists sifting through multiple layers of cultural transitions. But such inconsisten­cies are a natural result of today’s data landscape.

Data modelers and architects that lean toward being perfectionists, desiring nothing more than to eliminate all inconsistencies immediately, must learn to live with a certain level of mild frustration. Designers and leads need to plan for the future while taking baby steps today. And, ideally, those baby steps help enable the desired futures. The planned-for futures likewise need to allow for some lev­els of change as technology moves forward and best practices evolve. As is said, life is change. Therefore, between the start and the planned-for future, change is largely guar­anteed. Change does not negate the need for having a future vision; it only means that there must be some level of flexibility in the conceived future state.

The mindful meditation that might best serve data architects to practice would be to find a bal­ancing point. The budding data bodhisattva must practice patience and promote effort working toward the worthy goals determined to move an organization’s data landscape forward. What pieces leading to change can go into place now? What would then be the path forward for future steps? How can those future steps be refined to be not only practical, but expected, as the future unfolds?

Planning the path forward for a data architec­ture may be very similar to a chess match requiring designers to plan several moves ahead before mak­ing the first move. At the same time, that planning-of-future-moves process is not allowed the luxury of taking its own sweet time. Today’s projects must move at a fast and steady pace.

Achieving balance will often require having a goal that is well understood. At the same time, architects need to understand which elements are foundational to the desired end state and which elements are not foundational. Change is a constant; but changes impacting foundational elements are more likely to be those items worth fighting over. Any potential battles need to be chosen wisely; picking the proper battle will enhance the architect’s gravitas so that future battles may become easier to wage. Initial suc­cess can be very subtle; but with a clear vision, even those small changes can be most satisfying.