Choosing a Business Key

Concepts covered: paBusinessKey, paSurrogateKey

MERGE and deduplication both depend on a key that uniquely identifies each row. The right key seems obvious until the pipeline ingests its first edge case: an order with a null user_id, two events with the same timestamp, a CDC stream that emits one event for the row before the change and another for after, sharing the same primary key, a vendor that recycles IDs after a long enough interval, a soft delete that resurfaces the same logical row weeks later. Picking the wrong key turns an idempotent pipeline into a non-idempotent one without changing any other code. Picking the right key requires a clear-eyed view of where the key comes from, how stable it is across upstream changes, and what happens at the seams where multiple sources contribute to the same destination. The key choice is one

About This Interactive Section

This section is part of the Idempotency and Backfill: Intermediate 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.

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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.