A translator of data.
I work at the intersection where data integrity meets human communication. By training, I'm a data and BI analyst. By instinct, I'm a translator — between engineers and executives, between SQL schemas and business stakes, between English and Chinese, between what the numbers technically say and what people actually need to decide.
My path is unusual. A Bachelor's in English literature in China, then a Master's in Information Science at UW–Madison. Most people read those as opposites. I read them as the same craft: the discipline of saying exactly what is true, with care for how it lands.
That's the through-line in my work. SQL audit trails. Segregation of Duties frameworks. ERP metadata governance. Executive-facing Tableau dashboards. These look like different things — they're really one question viewed from different angles: how do you build a system whose claims you can actually defend?
I've practiced this inside IBM's enterprise ERP consulting practice, inside a 5-stakeholder logistics operation in New Jersey, and inside my own company — Lunarix Technologies LLC — where I build analytics platforms for healthcare, pharma, and supply chain clients.
The two-mode hand.
I think of my craft as having two modes. One that listens. One that builds. They're not separate hats — they're two ends of the same hand.
The listening mode
Where I spend more time than most data people do. The questions a CFO asks at 9pm that no dashboard answers. The thing a process owner is too tired to articulate. The gap between what a stakeholder requests and what they're actually protecting. Most data work fails here — not in the SQL.
The building mode
Where I refuse shortcuts. Clean schemas. Traceable logic. Audit-ready documentation. The kind of system where six months later, when someone asks "where did this number come from?", the answer is one click away. I'm allergic to data work that can't survive scrutiny.
The first mode is why stakeholders trust me. The second is why the auditor signs off.
The NJ pharma corridor & enterprise risk in AI.
I'm focused on the data challenges facing New Jersey's pharma corridor — J&J, Merck, BMS, Sanofi. Problems where the data has to be right because the stakes are real: patient outcomes, regulatory exposure, board-level decisions.
In parallel, I'm preparing for the CISA certification (Certified Information Systems Auditor) — formalizing the audit-discipline lens I already apply to my work.
Reading across systems.
I read across systems I'm not formally trained in — Vedic astrology, energy work, contemplative traditions. Not as escape from rigor, but as a complement to it. Some of the best frameworks for understanding people, timing, and pattern weren't written in PDFs after 1950.
I keep a small, deliberate circle. I write in two languages. I'm building slowly and on purpose, because the work I'm interested in compounds, and short-term wins rarely do.