Relational Data & Joins
Relational Data & Joins groups the core ideas a learner needs at the 2 · data ingestion, storage & integration stage. Work through the lessons in order when new to the area, or use them independently as a reference when implementing an analysis.
Learn the mechanism one decision at a time
Work through the lessons in order if the topic is new. If you already know the basics, open the specific leaf lesson that matches the operation, diagnostic or failure mode you need.
1Definition→
2Mechanism→
3Example→
4Diagnostic→
5Decision
Primary and foreign keysPrimary and foreign keys is a core data-integration operation. In analytics, correctness depends not only on syntax but on the relationship between keys, row cardinality and the grain of each table.
02One-to-one joinsOne-to-one joins is a core data-integration operation. In analytics, correctness depends not only on syntax but on the relationship between keys, row cardinality and the grain of each table.
03One-to-many joinsOne-to-many joins is a core data-integration operation. In analytics, correctness depends not only on syntax but on the relationship between keys, row cardinality and the grain of each table.
04Many-to-many joinsMany-to-many joins is a core data-integration operation. In analytics, correctness depends not only on syntax but on the relationship between keys, row cardinality and the grain of each table.
05Inner, left, right and full joinsInner, left, right and full joins is a core data-integration operation. In analytics, correctness depends not only on syntax but on the relationship between keys, row cardinality and the grain of each table.
06Join validation and row-count checksJoin validation and row-count checks is a core data-integration operation. In analytics, correctness depends not only on syntax but on the relationship between keys, row cardinality and the grain of each table.
07Reshaping with pivot and meltReshaping with pivot and melt belongs to the operational phase where an analytical result becomes a maintained system. Production quality requires the data contract, preprocessing, model, decision logic and monitoring to remain consistent over time.