Three ways to calm your data.
Pick one, or let me take a project end to end — from raw export to a clean, self-updating report.
Data cleaning
Messy exports in, analysis-ready data out. I fix formats, parse text into real numbers, standardize dates, consolidate stray categories, remove duplicates, and flag what was missing in the source — never guessed.
Dashboards
Interactive dashboards that turn a raw spreadsheet into answers at a glance — KPIs, trends, and filters your team can actually use. Built in Plotly, Shiny, or your existing BI tool.
Automated reporting
Recurring reports that build themselves. Set it up once and get a clean, on-brand summary on the schedule you need — no more copy-pasting into slides every month.
A few things I've built.
Sample projects built to show the process, using a demonstration dataset.
Sales overview dashboard
A clean BI-style report — KPIs, trend, and breakdowns by category, segment, and region.
Interactive R/Shiny app
A live dashboard with sidebar filters that recompute every chart in real time.
Data-cleaning case study
From a messy export to an analysis-ready dataset, with every fix documented.
Beauty in the essential.
Wabi Studio takes its name from wabi — the Japanese aesthetic of quiet, understated simplicity; finding beauty in what's stripped back to only what matters. That's exactly the work: taking noisy, chaotic data and returning something calm, clear, and easy to read.
Behind it is one person who codes and lives in data all day — fluent in Python and R, and happiest turning a spreadsheet nobody wants to open into something people actually use.
Let's clear the clutter.
Tell me what your data looks like and what you wish it could tell you. I'll take it from there.