Full vs Incremental Loading

Concepts covered: paFullVsIncremental

What They Want to Hear 'Full refresh drops the entire table and reloads from scratch. Incremental only processes rows that changed since the last run. I default to incremental because it is faster and cheaper, but I run a full refresh weekly as a safety net.' That is the answer. Two strategies, a default choice, and the safety valve.

About This Interactive Section

This section is part of the Keeping Data Fresh: Beginner 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.