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TechRelated Track: Data Engineering →

ETL (Extract, Transform, Load)

💡 Quick Definition: The three-step data integration process of extracting raw data from multiple sources, transforming it into a clean schema, and loading it into a data warehouse.

Detailed Explanation & Workplace Application

ETL forms the backbone of business intelligence and analytics. Tools like Apache Airflow, PySpark, dbt, and Power Query handle automated data extraction, deduplication, type casting, and schema loading.

Practical Syntax / Framework Formula

// ETL Architecture:
Extract: MySQL OLTP DB + REST APIs + CSV S3 Dumps
Transform: PySpark cleans missing nulls, computes customer LTV
Load: Snowflake / BigQuery Analytical Tables
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