Food price tracker and forecast
Track staple food prices over time, find the trend, and forecast what comes next so buyers and planners can act earlier.
Build: clean price dataset → trend view → forecast
I turn scattered numbers and repetitive tasks into insight and workflows that people can trust and keep running.
Analysis shows what is happening. Automation handles the routine part. Together they free you to decide what to do next.
Bring scattered, inconsistent data into one reliable view, from cleaning and joining to a dashboard people actually use.
Data cleaningSpreadsheetsDashboardsConnect the tools you already use. n8n workflows move information, handle routine steps, and leave a clear trail.
n8n workflowsAPI connectionsNotificationsTurn recurring reports into a clear read on what changed, what matters, and what might need a closer look.
KPI designTrend analysisReportingDocument the moving parts, add sensible failure paths, and make sure the person who inherits it is not left guessing.
QA and monitoringDocumentationReplace these cards with your real projects, one problem, one build, one result each. Status labels keep them honest.
Track staple food prices over time, find the trend, and forecast what comes next so buyers and planners can act earlier.
Build: clean price dataset → trend view → forecast
Important emails are picked out, grouped by type, and sent as a short digest to a chat app, so nothing urgent hides in the pile.
Build: n8n flow + clear error handling
Many reports list a dozen measures with no sign of which needs action. A short list of agreed indicators makes the review faster and more focused.
Build: KPI definitions → decision-ready view
Good systems start with listening. I want to understand the real handoffs, definitions, and exceptions before deciding what to build.
Edit this section to match your actual working style.
Map the current process, its inputs and decisions. Start with the task that costs the most attention.
Check definitions, clean the source, and agree on what a trustworthy answer should look like.
A clear analysis or a focused workflow first, with no extra machinery for its own sake.
Try real-world exceptions, document the logic, and leave a clear path for what comes next.
If the person using it cannot explain what it does, it is not finished.
The best dashboard changes a decision. The best automation is one you can trust.
Visible logic, sensible alerts, and documentation are part of the deliverable.
Build around the tools and constraints already in the room, then improve from there.
Placeholder bio. Replace it with your own background, location, and examples before publishing.
I am an economist and statistician in Ogun State, Nigeria. I work across data analysis and automation to make everyday operations easier to understand and easier to run, with a focus on information that can be trusted and workflows that stay clear enough to maintain.
Tell me what is taking too long, hard to see, or too easy to forget. We can start with the actual problem.
Email me