Databases & SQL

About this track

SQL is declarative, which is exactly why it is hard to learn: you write what you want and the engine decides how. These pages show the how. Run a join and watch rows pair up; run a GROUP BY and watch rows collapse into one.

The track covers the relational model and its NoSQL alternative, then works through the clauses in the order a query is actually evaluated, ending on window functions and CTEs.

SQL is declarative, which is exactly what makes it hard to learn: you write what you want and the engine decides how. These pages show the how - which rows survive each clause, in the order the database actually applies them.

What you will be able to do

• Write queries with confidence about which clause runs when, and why that decides where an alias is legal.
• Choose the right join, and predict how many rows come back before running it.
• Tell WHERE from HAVING by what each one filters, and pick the faster of the two.
• Explain what an index costs on write and what it saves on read.
• Say what a transaction guarantees, and what normalisation is trading away.

How the track is ordered

The relational model comes first, along with its non-relational alternative, so the later clauses have something to act on. Then SQL itself, worked through in the order a query is actually evaluated - FROM and JOIN, WHERE, GROUP BY, HAVING, SELECT, ORDER BY - which is deliberately not the order it is written in, and explains most of the errors beginners hit. Subqueries, CTEs and window functions follow, and the track ends on the engine's own concerns: indexes, transactions and normalisation. No prior database experience is needed.

Where this leads

Indexes are B-trees, and query execution order is a plan over set operations, so the algorithms track explains the machinery underneath. If you are heading toward machine learning, this is where the training data comes from and where most feature engineering actually happens.