Data engineering, automation, and analytics for growing businesses
Get your data in one place, put the busywork on autopilot, and see what's coming next.
I build the pipelines, warehouses, automations, and predictive models that small and mid-sized businesses need but rarely have a data team for. Based in Hamilton, working with businesses across Greater Cincinnati and the U.S.
What I do
Three ways to put your data to work
Each one builds on the last: reliable data makes automation possible, and both make better predictions possible. Start wherever the biggest headache is.
Data Engineering & Infrastructure
One trusted home for all of your business data.
- Automated pipelines from your apps, databases, and exports
- A cloud data warehouse modeled for reporting
- Monitoring that catches failures before your reports do
Custom Automation
Hand off the data work your team repeats every week.
- Scheduled syncs between the tools you already use
- Reports that build and send themselves
- Alerts for the numbers that need your attention
Analytics & Data Science
See what's happening now, and what's likely to happen next.
- KPI dashboards built on data you can trust
- Customer segmentation and lifetime value
- Forecasts and prediction models
Featured build
A data platform that runs itself
Cincinnati publishes every police crash report as open data, in a shape that resists analysis: one row per person instead of per crash, every value stored as text, and record IDs that change each time the city republishes. I built the pipeline that turns that feed into a warehouse you can query and a dataset ready for forecasting, then deployed it to run on Google Cloud with no one watching.
Your sources will be different, maybe an online store, accounting software, and a CRM. The problems are the same: messy exports, IDs that don't line up, and reports that break without anyone noticing. This is the standard I build to.
See the code and design notesHow the data flows
- 1
City open-data API
Every Cincinnati police crash report, paged from the public feed
- 2
Python on Cloud Run
A scheduled container that extracts, validates, and loads
- 3
BigQuery warehouse
A star schema: one fact table and six dimensions
- 4
Forecasting dataset
53 neighborhoods × 3,882 days, with lag features
221,289
crashes modeled in the warehouse
Daily
incremental loads, plus a full rebuild on Sundays
Every run
checked against the source and logged
2 alerts
that email a person when something goes wrong
Engineering rigor, small-business focus
I'm Brandon Ytuarte. I hold an MS in Business Analytics from Franklin University (2026, GPA 3.95) and build with Python, SQL, BigQuery, Google Cloud, and machine learning. I've also built and run e-commerce operations myself, so I build for the questions owners actually ask, not for the technology's sake.
You work directly with me from the first call to the final handoff. I was born and raised in Hamilton, Ohio, and work with businesses here and across the country.
Learn more about meFrom the Blog
Practical data guides for small businesses
Ready to put your data to work?
Tell me where your data lives and what you wish it could tell you. The discovery call is free, takes 30 minutes, and you'll leave with a clear next step.
Book a Free Discovery Call