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Data Processing Overview

⚡ Data Processing & Transformation

Data processing is the core of data engineering. It involves cleaning, aggregating, and enriching raw data to make it useful for analysis.

🔍 Section Overview

Master the tools used to process gigabytes and terabytes of data efficiently.

1. ETL vs. ELT Patterns

Explore the shift from traditional ETL (Extract, Transform, Load) to modern ELT (Extract, Load, Transform) using tools like dbt.

2. Apache Spark Deep Dive

Deep dive into Spark. Learn about RDDs, DataFrames, and how Spark parallelizes work across a cluster of machines.

3. dbt: The Transformation Engine

Master dbt (data build tool). Learn how to write modular, version-controlled SQL that turns your warehouse into a transformation engine.

🎯 Key Learning Goals

  • Implement high-performance data transformations in both Python and SQL.
  • Use Apache Spark to process massive datasets that don’t fit in memory.
  • Build a version-controlled transformation layer using dbt.