A better way toPrepare for your next big data role

Practise Excel, SQL, Power BI and Python using real-world datasets, guided projects, browser-based tools and instructor feedback.

Start practising free Browse the project library

Guided projects: 6Guided projects
Graded SQL exercises: 11Graded SQL exercises
Learners practising: 92Learners practising

Data Lab · SQL workspaceDuckDB ready

SELECT category, revenue, margin_pct
FROM category_margin
ORDER BY margin_pct DESC;

category	revenue	margin_pct
Personal Care	4,182,940	34.98
Snacks	2,461,220	31.87
Beverages	6,038,115	27.94
Household	3,120,660	22.05

✓ 6 rows returned · 41 ms

Four tools, one workflow

The stack a working data analyst actually uses

Each project tells you which tools it expects, and every submission is reviewed by a Data Science East Africa instructor against the same published rubric.

Microsoft Excel

PivotTables, XLOOKUP, cleaning and dashboards.

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SQL

Joins, CTEs and window functions in a live browser engine.

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Power BI

Star schemas, DAX, time intelligence and storytelling.

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Python

pandas, NumPy and exploratory data analysis.

Explore

Runs entirely in your browser

A real SQL laboratory, not a quiz box

The workspace runs DuckDB compiled to WebAssembly. Drop in a CSV, Excel workbook, JSON or Parquet file and query it immediately — your data never leaves your machine, and there is nothing to install.

Monaco editor with auto-completion for your own tables and columns
Joins, CTEs, window functions, date functions and views
Query history, saved scripts, multiple tabs and CSV export
Graded exercises marked on the server, so a score always means something

Open the SQL workspace

gross-margin-by-category.sql

SELECT
  p.category,
  ROUND(SUM(s.revenue), 2)          AS revenue,
  ROUND(SUM(s.cost_of_goods), 2)    AS cost,
  ROUND(SUM(s.revenue)
      - SUM(s.cost_of_goods), 2)    AS gross_profit,
  ROUND((SUM(s.revenue)
      - SUM(s.cost_of_goods))
      / SUM(s.revenue) * 100, 2)    AS margin_pct
FROM retail_sales s
JOIN retail_products p
  ON p.product_id = s.product_id
GROUP BY p.category
ORDER BY margin_pct DESC;

✓ 6 rows · 41 ms

How it works

From dataset to portfolio piece

1
Pick a real business problem
Every project opens with a client, a role and a decision that depends on your analysis — not a toy dataset.
2
Work in the browser or your own tools
Query the data in the SQL laboratory, or download it for Excel, Power BI and Python.
3
Submit and get marked
An instructor scores your work against a published rubric and returns specific, written feedback.
4
Publish it to your portfolio
Approved work becomes a public case study you can send to an employer.