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Most reporting problems don’t start with the dashboard.
They start with the data behind it.
Before I build a Power BI or Excel report, I usually check three things first:
• inconsistent categories and naming
• manual steps that can be automated
• KPIs being calculated differently across reports
Fixing these first usually makes the final dashboard simpler, more reliable and much easier to maintain.
Good reporting is not just about making charts look better.
It’s about creating numbers people can actually trust.
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Youth Skills Training Programme — Excel M&E Dashboard
Excel-based M&E analysis project covering data cleaning, formulas, PivotTables, charts and dashboard development.
Full Description:
Analysed a simulated youth training dataset using Excel to clean, structure and interpret programme data. Built PivotTables, charts, KPI summaries and an interactive monitoring dashboard to present attendance and assessment performance.
Nigerian Youth Unemployment — Power BI Dashboard
I built this Power BI dashboard to analyse youth unemployment across Nigeria’s six geopolitical zones using data from the National Bureau of Statistics (NBS).
The aim was to take the data beyond a spreadsheet and make it easier to see where unemployment and related challenges are more pronounced.
What I worked on
Created KPI cards for the main unemployment indicators
Compared unemployment rates across the six geopolitical zones
Analysed the difference between female and male unemployment
Looked at NEET rates (young people not in education, employment or training)
Added a zone slicer so users can explore the data by region
Created DAX measures for gender gap and above-average unemployment
Added key findings and programme recommendations based on the results
One of the main findings was that the South East had the highest youth unemployment rate at 14.8%, with a NEET rate of 29.6%.
Tools: Power BI, DAX, Microsoft Excel
Data: National Bureau of Statistics Nigeria — Labour Force Survey
This project helped me practise turning raw data into a dashboard that can be used to understand patterns and support programme and policy decisions.:
One thing I’ve learned from working with data is that the numbers are only the beginning. The real value comes from understanding the story behind them and turning that into action.