Shaolin Data Services

[Note on Brand Evolution] This post discusses concepts and methodologies initially developed under the scientific rigor of Shaolin Data Science. All services and executive engagements are now delivered exclusively by Shaolin Data Services, ensuring strategic clarity and commercial application.

Occasionally the questions come up: “So are you doing a PhD or not?” or “When will you finish your PhD?” For those of you who already know the answer, you should not be mad. The fact is, many people don’t fully understand the implications of a PhD despite its popularity. (After all, dentists are doctors too, you know!)

The truth is, my degree is a Doctor of Computer Science (DCS) from Colorado Technical University. The distinction is crucial, and it’s one that defines the very core of my approach to data science. We call ourselves “scholar-practitioners” because we straddle the line between theory and application. What that means is that a DCS is much more focused on getting actual, real-world results than the purely theoretical approach often found behind a Doctor of Philosophy (PhD).

The Data Speaks for Itself

This graphic, using data from the 2024 Bureau of Labor Statistics, beautifully compares the distinctions for forecasted and projected career elements through 2033 between a Doctor of Business Administration and a PhD.

As you can see, the data is very clear. Whereas PhDs are more likely to be accepted and targeted for education, research, or otherwise theoretical work, practice-oriented certifications like a DBA or a DCS are more readily trained to produce results in given market sectors, industry, and other high-stakes arenas.

In RPG Terms: The Battle Mage vs. The Wizard

If we were to look at this in role-playing game terms, the difference becomes even clearer. We are closer to being OP battle mages than strict wizards, sorcerers, or warlocks. We have a deep understanding of the arcane arts of data science, but our training is focused on using that knowledge to achieve tangible, measurable results on the battlefield of business. Some of us are even more specialized, like magic swordsmen or magic archers, but the core principle remains the same.

The punchline to all of this, however, is a statement I sometimes come across: “theory is different from practice.” It is an argument I find is often made by those who have either failed to apply the theory correctly or do not truly understand it. The ultimate irony is that our disciplined approach to data science is founded on the very principle of merging theory with practice, ensuring that one is never detached from the other. This fusion is the essence of Shaolin Data Science.

The path to mastery is built on a foundation of merit. What does “merit” mean in your career, and how do you ensure your work reflects it?