Module 1.1: Projecting Columns from a Source Table
Decide which columns you want and what to call them: explicit projection and clean aliasing.
Module 1.2: Filtering Rows
Cut a scan down to the rows a model needs: comparisons, sets and ranges, NULL logic, and boolean predicates.
WHERE and Comparison Operators
Restrict a scan to the rows a model actually needs.
IN, BETWEEN, and LIKE
Match sets, ranges, and text patterns when filtering source rows.
NULLs and Three-Valued Logic
Handle missing values correctly: the #1 source of silent data bugs.
Combining Predicates: AND / OR / NOT
Compose multiple conditions with correct precedence and parentheses.
Module 1.3: Shaping the Result Set
Order, limit, and de-duplicate output for deterministic previews and top-N inspection.
Module 1.4: Types, Casting, Strings, and Dates
Coerce and clean raw values: type affinity and CAST, string functions, and SQLite date/time handling.
Data Types and CAST
Convert values explicitly and understand SQLite's dynamic typing.
String Functions for Cleaning
Trim, case-fold, and slice text to standardize messy source strings.
Dates and Times in SQLite
Parse and format ISO-8601 date text, where dialects diverge most.