Service · Data & analytics
Dashboards, data pipelines & forecasting
Stop copying numbers between spreadsheets. I build the pipelines that collect your data automatically, the dashboards people actually open, and forecasts that come with honest uncertainty and a plain-English explanation.
- Python
- R
- SQL
- Snowflake
- Shiny
- React
- D3
- Posit Connect
- XGBoost
- Random forest
- Cross-validation
- MLOps
What’s included
What you get
- 01
Data pipelines & automation
Scheduled jobs that pull from databases, spreadsheets and APIs, clean the data, and land it somewhere reliable. Python, R and SQL.
- 02
Dashboards
The few numbers that matter, clear charts, and drill-downs for when someone asks why. Built in Shiny, React or the tools you already have.
- 03
Forecasting
Demand, staffing, energy and budget forecasts. Several models are tested on your history and the best one is chosen for each segment.
- 04
Anomaly detection & predictive maintenance
Catch unusual readings, failing equipment and data errors early, with alerts that explain what changed.
- 05
Machine learning
Classification, matching and prediction models, cross-validated and documented, with results your team can trust and explain.
- 06
Reporting for funders & boards
Repeatable reports for grants, boards and public accountability that update themselves instead of being rebuilt every quarter.
Good fit
This is for you if…
- Someone spends hours every week building the same report by hand
- Your data lives in several systems that don’t talk to each other
- You plan inventory, staffing or budgets on gut feel
- You need clear numbers for a board, funder or public audience
Related work
Case studies
- Data science · Manufacturing · industry workUtility forecasting portal A forecasting system that predicts utility consumption for each part of a manufacturing operation and publishes the results to a self-service web portal.
- Data science · Manufacturing · industry workPredictive maintenance Anomaly detection on equipment vibration telemetry that flags machines drifting out of normal behavior before they fail.
- AI system · Manufacturing · industry workAI inventory matching An AI system that matches aged inventory to open purchase orders, applying detailed material specifications and checking every match with an independent validator.
FAQ
Common questions
Do I need a data warehouse first?
No. Many projects start from spreadsheets and a database or two. I’ll recommend the simplest setup that’s reliable, and only suggest a warehouse like Snowflake if you need one.
What tools do you use?
Python, R and SQL for the data work. Shiny, React or Posit Connect for dashboards. Azure, Snowflake and SQL Server when you’re already on them.
How accurate will a forecast be?
Every forecast is tested against your own history before you rely on it, and it comes with a range, not just a single number, so you know how confident to be.
Can you work remotely with our team?
Yes. Data projects run well remotely: secure access to your data, video walkthroughs, and documentation your team keeps.
Service area
Kenosha, Milwaukee, Chicago, and anywhere in the US
I’m based in Kenosha, between Milwaukee and Chicago, and meet clients in person across Southeast Wisconsin and Chicagoland. Most projects run just as well remotely: weekly preview links, video calls, and one developer you can reach directly, wherever you are in the country.
- Kenosha
- Racine
- Milwaukee
- Waukesha
- Chicago
- Lake County, IL
- Remote, nationwide