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Read a small table as a set of real-world records: each row is one thing, each column is one fact about that thing, and each cell is one value at their intersection.
Use what you learned in the previous lesson to solve real-world problems.
Use column names to infer what each value means, and distinguish a column’s meaning from the values that happen to appear in a few sample rows.
Check what you understood with a short quiz.
Recognize how data types shape what a column can safely store, such as text, numbers, dates, and true/false values, and spot values that do not fit the column’s role.
Treat a row as one complete record, then check whether all its values describe the same person, order, product, or event rather than mixed facts from different things.
Interpret NULL as a missing, unknown, or not-applicable value, and avoid reading it as zero, an empty string, or the word “none” unless the table design says so.
Identify the column that uniquely names each row, and reason why a primary key must be unique, present, and reliable for finding one exact record.
Compare natural keys, like an email or ISBN, with surrogate keys, like an auto-generated customer_id, and decide why many tables use a separate ID column.
Trace how a foreign key stores another table’s primary key, letting one record point to a related record without copying all of its details.
Recognize one-to-many relationships by seeing the same foreign key value appear in many rows, such as many orders pointing to one customer.
Reason through why related data is split across tables: repeated facts stay in one place, while keys reconnect the records when you need the full story.
Read common schema clues such as table names, *_id columns, primary-key markers, and foreign-key lines so you can tell how tables relate before writing any SQL.
Review this chapter with practice based on your mistakes.
