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Understanding Datasets, Databases, and Data Lakes

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32 lessons✓ Certificate of completion

About this course

A comprehensive technical course covering the full data engineering stack: relational databases, data lakes, cloud platforms, file formats, security, AI integration, and hands-on labs. Designed for engineers who want to build production-grade data platforms.

Course content

The Modern Data Landscape

  • The Modern Data Landscape
  • Datasets in Depth

Database Fundamentals

  • What Is a Database?
  • The 15 Major Types of Databases

Relational Databases and SQL

  • Relational Databases and SQL Foundations
  • Oracle Database — Technical Deep Dive
  • Microsoft SQL Server — Technical Deep Dive
  • PostgreSQL — Technical Deep Dive
  • MariaDB and MySQL — Technical Deep Dive

Database Administration

  • Database Administration Fundamentals

Data Warehouses, Lakes, and Lakehouses

  • Data Warehouses, Data Lakes, and Lakehouses
  • Data Lake Architecture
  • Dataset Sources and Access Methods

Data Engineering and Processing

  • Data Ingestion and Pipeline Design
  • Data Processing with Python, SQL, DuckDB, and Spark

File Formats and Cloud Platforms

  • File Formats for Analytics and AI
  • Cloud Data Platforms

Security, Operations, and AI Integration

  • Security, Governance, and Compliance
  • Backup, Restore, Retention, and Disaster Recovery
  • Databases and AI Integration
  • Observability and Troubleshooting

Hands-On Labs

  • Lab Environment Setup
  • Lab 1 — Build a Database Source
  • Lab 2 — Build the Data Lake Folder Structure
  • Lab 3 — Ingest Data into Bronze
  • Lab 4 — Clean and Standardize Data into Silver
  • Lab 5 — Build Gold Analytics Tables
  • Lab 6 — Create a Dashboard
  • Lab 7 — AI Integration Lab

Capstone, Career, and Reference

  • Capstone Project
  • Job Preparation and Career Roadmap
  • Glossary and References