Four ways I can help
Every project starts with the same question: what decision are you trying to make? These four areas are where that work usually lands.
Process Automation
Most businesses have at least one task that quietly eats hours every week: retyping the same data into two systems, downloading the same report from the same portal, filing the same documents by hand. That is the first place I look. I build processes that move, clean, and organize your data on their own, connecting systems through APIs, generating reports on a schedule, and keeping records in sync, so the busywork stops landing on someone's desk.
What this looks like
- Scheduled jobs that collect data from portals and APIs instead of manual downloads
- Reports that generate and send themselves on whatever cadence you need
- Systems connected through APIs, so the same data is only ever entered once
- Validation built into the pipeline, so problems surface early instead of at month end
Business Dashboards
If your team is deciding from spreadsheets that go stale the moment they are opened, or if 'the numbers' means five exports that disagree with each other, this is where we start. I build interactive dashboards that pull from your real data sources on a schedule, so the view is current when you open it. That might be a Power BI report for leadership, a Tableau dashboard your ops team checks every morning, or a lightweight web app in Streamlit or Dash when off-the-shelf tools do not fit. Either way the goal is the same: answering 'how is the business doing' should take seconds, not half a day of pulling numbers together.
What this looks like
- Sales, inventory, or operations dashboards that refresh on a schedule instead of being rebuilt by hand
- KPI views leadership can open directly, without waiting on someone to compile them
- Custom internal web apps for the workflows off-the-shelf tools do not cover
- A focused set of numbers that drive real decisions, rather than every metric available
Data Strategy
A dashboard is only as good as the data behind it, and plenty of businesses are either missing the numbers that matter or drowning in ones nobody reads. Before building anything, I like to establish what is worth tracking and why, so whatever comes next rests on something solid. In practice that means reviewing what you capture today, getting clear on the decisions you are actually trying to make, and mapping a realistic path from one to the other.
What this looks like
- A review of what you track today, what is missing, and what is just noise
- A short roadmap linking business goals to the metrics that actually reflect them
- Tool and structure recommendations sized to your business, not enterprise overkill
- A second opinion when you are weighing up a new system or vendor
Data Training & Education
Sometimes the better investment is not another tool. It is making sure your team can use the ones you already pay for. I run hands-on sessions built around your actual work: the Excel formulas people keep getting stuck on, a first introduction to SQL for someone who has outgrown spreadsheets, or a practical look at what AI tools can and cannot responsibly do in your day to day. Sessions use your data, not a generic sample file, and each one comes with a defined follow-up window so the training still holds once the room clears.
What this looks like
- Excel workshops built around your own spreadsheets and the places people get stuck
- Introductory SQL for team members ready to move past spreadsheet limits
- Practical AI sessions covering real use cases and the guardrails that belong with them
- A set follow-up window for questions once people start applying it
