Data, Reporting & Integrations
Turn scattered business data into something you can actually use.
Most businesses already have the data they need. It's just spread across systems that don't talk to each other, and someone ends up combining it by hand. I connect those systems, APIs, files, and spreadsheets so the reports, exports, and dashboards arrive on their own — built on more than a decade of full-stack engineering experience.
What that usually looks like
- Automated reporting
- Data delivered as CSV or Excel
- Business dashboards
- Connected systems
- Data that stays current
Something in this list probably sounds familiar.
These are the situations this work usually starts from. None of them require you to know what the technical solution is.
“We export the same data every week and combine it by hand.”
“Our numbers live in four different systems.”
“The data we need sits in a platform that only offers an API.”
“Somebody rebuilds the same report every Monday morning.”
“We want this to update on its own.”
“We can't tell whether the numbers we're looking at are current.”
“Our tools already have the data — just not in the form we need it.”
Concrete things, not a technology menu.
Each of these can stand on its own, or become one part of something larger later.
- Automated reportingScheduled jobs
- The report someone rebuilds by hand each week becomes a scheduled job — same output, on time, without anyone opening a spreadsheet.
- Data delivered as CSV or ExcelAPI extraction & export
- Data pulled out of a system that won't export it cleanly, reshaped into a file your team can open and use immediately.
- Business dashboardsAggregation & visualization
- A focused view of the figures that drive decisions, drawn from every system holding part of the answer.
- Connected systemsSystem integration
- Two or more tools kept in step, so information entered in one place stops being re-entered somewhere else.
- Data that stays currentData pipelines
- Information collected from several sources on a schedule and kept in one place, so the reports and dashboards above it never wait on a manual refresh.
How the data actually moves.
The same four steps sit behind a one-off export and a system feeding a live dashboard. Only the scale changes.
Starts with
- Business systems
- APIs
- Spreadsheets
- Files
- Webhooks
Collect
Pull data on a schedule from wherever it currently lives — including systems with no export button.
Clean and combine
Reconcile formats, dates, currencies, and duplicate records so figures from different systems can sit side by side.
Store and organize
Keep the combined history in one place, so you can look at last quarter as easily as this morning.
Deliver
Send it back out in the form people actually use — and on the schedule they need it.
Ends with
- Scheduled reports
- CSV / Excel
- Dashboards
- Other systems
Then it repeats on a schedule. Each run records what it collected and whether it succeeded, so a report that quietly stopped updating is something you find out about — rather than something you discover in a meeting.
Automation is only useful if you can trust it.
Calling an API successfully once is the easy part. Most of the engineering goes into what happens on the days something goes wrong — because a report nobody trusts gets rebuilt by hand anyway.
- Retrying a failed step shouldn't quietly create duplicate records.
- Idempotent processing
- You should be able to tell whether this morning's data actually arrived.
- Run history and monitoring
- When a source changes shape, it should fail loudly — not write wrong numbers quietly.
- Validation on ingest
- A day that got missed should be repairable without rebuilding everything.
- Backfills and reprocessing
- One slow or rate-limited system shouldn't take down the whole report.
- Retries with backoff
- When two numbers disagree, you should be able to trace where each came from.
- Traceable sources
Here’s what that looks like when it’s running.
A working example built around a fictional home services company: three systems, one answer, refreshed every morning — including a morning where something goes wrong.
Operations Rollup · working example
Synthetic demo data
Tallis & Reed Home Services
3 business systems — scheduling, payments, and an ad-spend spreadsheet — collected and verified into one trusted operational view, refreshed every morning.
- Report status
- ● Up to date
- Verified through Oct 5, 2026
- Source verification
- 3 of 3 sources verified
- Every number traceable to its source system
Meta Ads (Facebook & Instagram) produced the most leads, but Google Local Services produced paid jobs at the lowest cost — $68 each.
An answer that only exists because three systems were combined — and that holds itself back when a source doesn’t deliver.
See a working exampleStart with one useful problem.
Most of this work begins as a single contained piece that solves something real on its own terms. What comes after it depends entirely on whether the first piece earned it.
Start here
- Automate one recurring report
- Pull data out of one system that won't export it
- Replace one manual spreadsheet routine
- Connect two systems that should already talk
- Produce one reliable CSV or Excel export
Expand when it proves useful
- Bring in the remaining systems
- Centralize the combined history
- Add dashboards on top of it
- Put the whole thing on a schedule
- Add monitoring and failure alerts
- Extend it as new questions come up
Solve the useful problem first. Expand only when the business value justifies it.
The engineering behind the automation.
The practices above are only worth promising if someone has had to live with them. This is the background behind that.
- Experience
- 10+ years building production software
- Scope
- Frontend, backend, databases, and cloud infrastructure
- Data work
- APIs, integrations, business rules, and complex data flows
- Delivery
- Automated testing and production reliability practices
Reasonable things to ask first.
No. It's more useful if you don't lead with that. Describe the manual process, the report, or the spreadsheet routine that's costing time, and I'll work out what's actually possible with the systems you have. Working out the right approach is part of the job, not a prerequisite for contacting me.
Usually, though it depends on the specific product. Most business platforms offer an API, a scheduled export, or webhooks, and any of those is enough to work with. Some are more restrictive than others. Tell me which systems are involved and I'll tell you honestly what each one will and won't allow — before either of us commits to anything.
Yes, and often it should. A single report, one export, or one connection between two systems is a sensible first piece of work — small enough to be worth doing on its own, and enough to show whether anything larger is justified.
Yes — on a schedule you choose, such as every morning, weekly, or at the start of each month. How fresh the data can be depends on how often the underlying systems make it available, so genuine real-time isn't always possible. I'll be specific about what's realistic for your sources rather than promising more than they can deliver.
Yes. Plenty of real business data lives in files rather than systems with an API — exports from a vendor portal, a spreadsheet someone maintains, a monthly file from an accountant. Those can be sources or destinations, and often both.
Tell me what's taking too much manual work.
You don't need a specification, a budget, or the right technical words. A description of the routine that keeps eating your time is genuinely enough to start from.
What to expect
- A direct reply from me — never an automated sales sequence.
- An honest read on what your systems will and won't allow.
- Clear next steps, whether or not I am the right fit.
Something as ordinary as “every Friday I download three spreadsheets and combine them” is a perfectly good place to begin.
Based in Las Vegas, Nevada. Working with clients remotely.