timiczn/ekiti-state-unemployment-survey-analysis — explained in plain English
Analysis updated 2026-05-18
See which job sectors unemployed survey respondents are most interested in.
Compare sector interest and skills across gender and age groups.
Identify which schools account for the largest share of unemployed respondents.
Track graduation year trends to spot when respondents left education.
| timiczn/ekiti-state-unemployment-survey-analysis | 0xkinno/neuralvault | 0xlocker/d17-contracts | |
|---|---|---|---|
| Stars | 1 | 1 | 1 |
| Language | — | TypeScript | Solidity |
| Setup difficulty | easy | hard | hard |
| Complexity | 2/5 | 4/5 | 5/5 |
| Audience | pm founder | developer | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires Power BI Desktop to open and explore the report file.
This project is a Power BI analysis built for an NGO working on youth and graduate employment in Ekiti State, Nigeria. The NGO collected survey responses from unemployed people to understand who they are, what they studied, which industries they want to work in, and what skills they already have. The goal is to help the NGO's leadership decide where to focus training, job placement, and outreach programs, based on what respondents actually say rather than assumptions. The raw data started as a single messy Excel export of 1,006 submissions, full of duplicate entries, inconsistent free text, and multiple answers crammed into single fields separated by semicolons. The project cleaned this down to 921 usable responses. Duplicates were matched by full name and date of birth rather than phone number, since phone digits often had typos. Implausible ages, missing gender fields, and future graduation dates were removed. Vague age labels like Youth or Young Adult were replaced with clear ranges. Hundreds of inconsistent school names and skill entries were consolidated into clean, canonical lists, with care taken not to merge schools that just share a similar name. The cleaned data was organized into a proper data model with separate tables linking respondents to the sectors and skills they selected, since people could pick more than one of each. A set of measures was built to calculate totals, averages, percentages by gender and age group, and even auto generated summary sentences that update as filters change. The finished dashboard has two pages: an overview with respondent totals, age and qualification breakdowns, top skills, and graduation trends, and a sector analysis page showing which industries appeal to which demographic groups. Key findings include that respondents skew female and are mostly working age rather than recent graduates, that health and education are the two most popular sectors of interest, and that interest in these sectors splits sharply along gender lines. A handful of schools account for a large share of all respondents, making them useful targets for outreach. The README does not state a license, so the terms under which this project can be reused are not specified.</content>
A Power BI dashboard that cleans and analyzes an unemployment survey of 921 people in Ekiti State, Nigeria, to help an NGO target training and job placement programs.
Setup difficulty is rated easy, with roughly 30min to a first successful run.
Mainly pm founder.
This repo across BitVibe Labs
double-check against the repo, no cap.