Surrogate Keys

Surrogate keys are system-generated identifiers that replace natural keys in dimensional models. Every dimension row gets its own surrogate key (customer_sk, product_sk, date_sk). Fact tables reference dimensions using these surrogate keys, not the natural business keys. Why Not Just Use Natural Keys? Natural keys (email, SKU, employee_id) come from source systems. They have three problems in analytical models: they change (email updates), they get reused (SKU recycled for a new product), and they complicate SCD Type 2 (a customer with 5 historical versions would have 5 rows with the same email, and fact rows need to reference the specific version). How Surrogate Keys Enable SCD Type 2 When a customer moves from Portland to Seattle, you create a new dimension row with a new surrogate key.

About This Interactive Section

This section is part of the Star Schemas lesson on DataDriven, a free data engineering interview prep platform. Each section includes explanations, worked examples, and hands-on code challenges that execute in real time. SQL queries run against a live PostgreSQL database. Python runs in a sandboxed Docker container. Data modeling problems validate against interactive schema canvases. All content is framed around what data engineering interviewers actually test at companies like Meta, Google, Amazon, Netflix, Stripe, and Databricks.

How DataDriven Lessons Work

DataDriven combines four interview rounds (SQL, Python, Data Modeling, Pipeline Architecture) with adaptive difficulty and spaced repetition. Easy problems get harder as you improve. Weak concepts resurface until you master them. Your readiness score tracks progress across every topic interviewers test. Every lesson section ends with problems you solve by writing and running real code, not by picking multiple-choice answers.