Data Engineer Learning Path
Your comprehensive resource for building expertise in data engineering.
01
Introduction to Data Engineering
Section 1.1: What is Data Engineering? Definitions and Scope
Section 1.2: The Data Engineering Ecosystem: Tools and Technologies Overview
Section 1.3: Data Infrastructure: Lakes, Warehouses, and Databases
- Video: Data Infrastructure (5min)
Section 1.4: Data Security and Compliance Basics
02
Data Modeling and Database Management
Section 2.1: Relational Databases: Design and Optimization
- Video: Relational Databases (6min)
Section 2.2: NoSQL Databases: Types and When to Use Them
- Video: NoSQL Databases (8min)
Section 2.3: Data Warehousing Solutions and Techniques
Section 2.4: Implementing Data Lakes: Architecture and Use Cases
03
Building Data Pipelines
Section 3.1: Introduction to Data Integration and ETL Processes
Section 3.2: Batch vs. Real-Time Processing
Section 3.3: Workflow Automation with Apache Airflow
Section 3.4: Monitoring and Optimizing Data Pipelines
04
Data Storage and Retrieval
Section 4.1: Advanced SQL Techniques for Data Handling
Section 4.2: Indexing Strategies and Full-Text Search Implementations
- Video: Indexing Strategies (10min)
Section 4.3: Implementing Caching Solutions for Performance Improvement
Section 4.4: Data Replication and Backup Strategies
05
Big Data Technologies
Section 5.1: Introduction to the Hadoop Ecosystem
Section 5.2: Real-Time Processing with Apache Spark
- Video: Real-Time Processing with Apache Spark (10-15min per video)
Section 5.3: Stream Processing with Apache Kafka
Section 5.4: Big Data and Machine Learning with PySpark
- Video: Big Data and Machine Learning with PySpark (10-15min per video)
06
Cloud Solutions for Data Engineering
Section 6.1: Building Data Infrastructure on AWS
Section 6.2: Data Engineering with Google Cloud Platform
- Video: Data Engineering with Google Cloud Platform (10-15min per video)
Section 6.3: Microsoft Azure for Data Engineers
Section 6.4: Multi-Cloud Strategies for Data Storage
07
Data Security and Compliance
Section 7.1: Data Governance Frameworks
Section 7.2: Security Best Practices for Sensitive Data
Section 7.3: Implementing GDPR and Other Compliance Measures
Section 7.4: Audit and Monitoring of Data Access
08
Advanced Data Engineering Projects
Section 8.1: Designing a Scalable Data Warehouse
Section 8.2: Real-Time Analytics System Design
Section 8.3: Building and Optimizing a Lakehouse Architecture
Section 8.4: Capstone Project: From Data Collection to Insights
- Video: Capstone Project: From Data Collection to Insights (10-15min per video)