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Data Engineering Foundations

🏗️ Data Engineering Foundations

Data Engineering is the practice of designing and building systems for collecting, storing, and analyzing data at scale. It is the foundation upon which all data science and analytics are built.

🔍 Section Overview

Master the core concepts of the data lifecycle and the different ways data flows through an organization.

1. The Data Lifecycle

Learn about Ingestion, Transformation, Storage, and Serving.

2. Batch vs. Stream Processing

Understand the trade-offs between processing data in large chunks (Batch) vs. real-time events (Streaming).

3. SQL for Data Engineers

Master the most important language in the data world. (Linked to our SQL Deep Dive).

🎯 Key Learning Goals

  • Explain the journey of a single data point from source to dashboard.
  • Choose between Lambda and Kappa architectures for specific use cases.
  • Build resilient ingestion pipelines using SQL and Python.