The core principle of data management is to have data you can trust; without trustworthy data, there is no real ability to understand what is true about the question(s) you are trying to answer. There can be so many reasons to not trust the data you use.

Let us use an ice cream shop trying to find out what flavor people most want to buy, as an example. We can trust our data to answer that question only when it is 1) Accurate; if someone submitted 82 responses out of 500, your data is skewed, and It will provide a misrepresentation of interest. 2) Complete, if you serve 15,000 people a day, but only receive 500 survey responses over the course of a week, you end up with too small of a sample to be effective. 3) Current, if the data is from 5 years ago, it likely no longer reflects the feelings and attitudes of people today. It is human nature to only trust things when we know they are accurate, complete, and current!

To maintain trust in our data once we have it, there are many things that can be done: deduplication, keeping it clean, standardizing values, enforcing management policies, and helping data entry understand the “why” and “what” of the data being entered. Never underestimate the insight of those who see and experience firsthand the data you use every day. When we look at a database, the goal is typically to have one place from which we derive answers to questions, come up with new questions, and have a singular place from which we can understand and make predictions about future events.

While all of this is easily said, it can take many forms: the monotonous march of entering and reviewing existing work, creating APIs and integrations, reformatting or moving between databases, creating dashboards, and sometimes the terrifying prospect of migrating to a new database (a challenge I would only wish upon my worst enemies)!

How does all of that become embodied in a way that reflects our spiritual nature? Unlike what you would pull from analytics, this question likely has many answers. In the worst case, this would seem to lead to a spiritual disposition that demands clarity, instant (or as long as the query takes) answers, that with enough information, any question can be concretely answered. In the best case, it can lead to the understanding that process, how you get to an answer matters, that there is an unpredictability to outcomes in life, that even despite our best and most effective efforts, we can be wrong, and it’s okay.

Being surrounded by data, working to make it tell a story, can drive a person to a sort of critical absolutism, the desire to rid oneself of the grey that is much of life. This is a temptation to avoid. The rich story of life can be summed up in 1’s and 0’s, but there is this special quality to reading into data that can make one inquisitive, step outside themselves, and have the desire to understand the larger picture for which they can only ever have a small piece. To work with data today can make one like Theophrastus, the first philosopher to write on economics. Data is not itself an answer but a way to explore, ponder large questions, play with ideas, and see if they are true or at least predictable. While philosophers still exist today, I would argue that those who take insights from data are doing much the same work that Theophrastus did, trying to bring order and understanding while considering the world around him. We manage data because it helps us to understand and hopefully pull us out of ourselves.