Selecting all columns (*)

The asterisk symbol provides a quick way to retrieve all columns without typing each name individually. When to Use * Choosing the Right Columns Now try selecting different columns from a product inventory table. Requesting only the columns relevant to your question means analysts reading your query can immediately understand what data you care about without scrolling through irrelevant output. The ability to select any combination of columns from a table is one of the core reasons SQL is so flexible for answering a wide variety of business questions from the same dataset.

About This Interactive Section

This section is part of the Query Structure: 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.