The Data Transformation Playbook: Turning Raw Data into Business Gold Thinking of data transformation as just "coding" is missing the bigger picture. It's a strategic process that involves choosing the right environment , the best language , and the most powerful framework . If you're gearing up for an interview, here's a fun, easy-to-remember breakdown of the key concepts! Part 1: Where We Transform (The Environment) The "where" dictates the "how." The three main places data engineers transform data are the Data Warehouse, the Data Lake, and the Data Lakehouse. 1. Data Warehouses (The Structured Powerhouse) How it Transforms: Primarily using SQL . Key Advantage: Modern warehouses (like Snowflake, BigQuery, Redshift) are serverless , meaning they automatically scale computing power up and down for intense workloads. They are fantastic for large, structured datasets. Pro-Tip: They have built-in features like ...
