Turn your data into decisions.
Most businesses already have the data — in SQL Server, in spreadsheets, in the app database — they just can't see it. I build Power BI dashboards that pull it together, model it correctly, and show the numbers that actually drive decisions, refreshed automatically so they're never stale. And because I build the databases underneath, the reports are right at the source. Remote, worldwide.
Dashboards people actually use, over data they can trust.
A report is only worth building if the numbers are right and someone reads it. Here's the reporting work I do, with the correctness handled at the data layer, not papered over in the chart.
Executive & operational dashboards
The handful of numbers leadership checks, and the detail your team works from — designed to be read at a glance, not deciphered.
Data models & DAX
A proper star-schema model and DAX measures so totals reconcile, filters behave, and the same metric means the same thing everywhere.
Connecting your sources
SQL Server, Excel, APIs and cloud services pulled into one model — one version of the truth instead of five conflicting spreadsheets. See database work →
Automated refresh
Scheduled refresh and gateways so the dashboard is current every morning without anyone exporting and pasting.
Row-level security & sharing
The right people see the right data — row-level security so each region, client or team sees only their slice.
Reports that load fast
A model and queries tuned so the report opens quickly even over large data — the difference between a dashboard people use and one they avoid.
What every reporting build includes
A dashboard is trusted when the numbers reconcile and it stays current on its own. Every build ships with that, not just pretty charts.
- A clean, documented data model (star schema)
- DAX measures for your key metrics
- Dashboards designed to be read, not decoded
- Connections to your real data sources
- Scheduled automated refresh
- Row-level security where you need it
- Performance tuning so it opens fast
- A short guide so your team can maintain it
The reports and the database, one engineer
Bad dashboards usually aren't a Power BI problem — they're a data problem. I build the SQL Server layer underneath too, so the reporting is correct at the source instead of patched in DAX.
- Deep SQL Server background, not just the BI tool
- Numbers fixed at the data layer, where they belong
- Models built to extend as you add metrics
- Honest about what the data can and can't tell you
- Honest scope and a clear quote up front
- You own the reports and the model
From scattered data to a live dashboard, in five steps.
Questions
What decisions the dashboard should support, and the handful of metrics that actually matter. We agree those before building anything.
Connect
Getting to your data — SQL Server, spreadsheets, APIs — and checking it's clean enough to report on honestly.
Model
A proper data model and the DAX measures, so every number reconciles and filters behave predictably.
Design
The dashboards themselves — laid out to be read at a glance, reviewed with you and refined.
Publish & support
Automated refresh, access set up, and support to add metrics as your questions change. See support options →
What the reporting sits on.
Related services — the database the reports read from, and a live example of a data-heavy dashboard I've built.
Database engineering
The SQL Server layer your reports read from — modelled and tuned so the numbers are right and the refresh is fast.
When data slows down at scale
Why reporting queries crawl as the data grows, and how to keep a dashboard fast over millions of rows.
Live dashboard demos
Working, interactive dashboards on sample data — the kind of data-heavy UI I build, with KPIs, charts and filterable tables.
Sitting on data you can't see?
Tell me what you'd want to know and where the data lives — a rough idea is enough. You'll get an honest scope and a clear quote, with no pressure.