You don’t need a computer-science degree to land a data-analyst role — you need to show you can turn raw data into answers. This project does exactly that: load a real dataset, answer real business questions with SQL, and present the findings in a dashboard. It’s the ideal first portfolio piece for career-changers.
What you’ll build: a SQL analytics project — load a public dataset into PostgreSQL, write queries that answer pointed business questions, and build a dashboard that visualizes the answers. The deliverable is a repo with your SQL + a dashboard a hiring manager can read in 30 seconds.
Analyst hiring is about SQL fluency and the ability to communicate insight. A repo where you ask sharp questions and answer them with clean queries and a clear dashboard proves both. It maps to the keywords on analyst postings: SQL, PostgreSQL, data analysis, dashboard, data visualization, business intelligence.
Skills & keywords you’ll demonstrate
SQL — joins, aggregations, window functions, CTEs
Data modeling & loading (CSV/API into Postgres)
Data cleaning & validation
A dashboard (Metabase, Power BI, Tableau Public, or a simple web chart)
Pick a dataset + questions. Choose a real public dataset and write down 5–8 business questions worth answering. Commit your README with the questions.
Load it. Get the data into PostgreSQL (a small Python or COPY script) and document the schema. Commit.
Clean it. Handle nulls, types, and duplicates; note what you changed and why. Commit.
Answer the questions. Write one well-commented query per question — use joins, aggregations, and at least one window function. Commit each.
Visualize. Build a dashboard with the key charts (a trend, a breakdown, a top-N). Commit screenshots.
Tell the story. Write a short “findings” section in the README: what you asked, what you found, what you’d do next. Commit.
Stretch goals
A reproducible pipeline (one command to load + refresh).
A second data source joined in for a richer question.
A published, interactive dashboard link.
Put it on your résumé
“Built a SQL analytics project on a [domain] dataset in PostgreSQL — modeled and cleaned the data, then answered 8 business questions with joins, aggregations, and window functions.”
“Delivered a dashboard summarizing the findings (trends, breakdowns, top-N) with a written insight narrative.”
Then run your résumé through the free ATS resume score to see your match for analyst and BI roles.
Frequently asked questions
Do I need to code to do this project? Barely. The core is SQL and a dashboard tool — no software-engineering background required, which makes this ideal for analyst roles and career-changers. A little Python for loading data is a bonus, not a requirement.
Where do I get a dataset? Use a real public dataset (open government data, a public API, Kaggle). Pick a domain with clear business questions — sales, transit, public health — so your analysis tells a story a hiring manager cares about.