YOUR LEARNING PATH

Data Engineering

Build reliable data pipelines with SQL, validation and repeatable imports. Deliver a tested event-data pipeline and an operational runbook.

6 steps / 4-6 months estimated

Before you start: Basic Python, command-line confidence and familiarity with tables. Complete Python & Data Analysis first if needed.
What you will build: A reproducible event-data pipeline with SQL models, quality checks, a recovery runbook and a documented sample dataset.

Choose a step

STEP 01 OF 6

Model data with SQL

Start with a fictional student events service. Separate events, venues and registrations instead of keeping every fact in one spreadsheet.

Break it down

01Build it yourself

Draw the relationships and create tables with primary keys, foreign keys and meaningful constraints. Insert a small sample dataset, join registrations to events and count registrations per event. Include an event with no registrations.

02Ready to move on?

Explain the grain of each table and why a join might duplicate rows. Your query includes zero-registration events and rejects a registration for a nonexistent event.

Take it further

Continue learning on these source websites.

PostgreSQL: relational databases and SQL tutorial

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Data Engineering

Model data with SQL

Break it down

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