Introduction
How to read this book
Helpers
Part 1: Understanding DEH
1.
Begin to Introduction
1.1.
Analytics Platform
1.2.
Data Architecture
2.
Basic Skills
2.1.
How Data Pipeline Structured
2.2.
Data Processing Practices
2.3.
Data Management Procedure
2.4.
Big Data Engineering
2.5.
Cloud System Understanding
2.6.
Data Infrastructure & Automation
3.
Recommended Books and Courses
Part 2: Dicing into DEH
4.
Advanced Skills
4.1.
Scaling
4.2.
High-Availability and Disaster-Recovery
4.3.
Large Data Handling
4.4.
Data Engineering Layers
4.4.1.
Connecting
4.4.2.
Buffering
4.4.3.
Processing
4.4.4.
Storing
4.4.5.
Visualizing
4.5.
Security Maintenance
4.6.
Data Governance
5.
Best Practices on Cloud
6.
Data Camping
6.1.
Week 1 - Infrastructure
6.1.1.
Docker and SQL
6.1.2.
Docker and AWS
6.1.3.
Terraform and AWS
6.2.
Week 2 - Data Ingestion
6.2.1.
Ingesting with Airflow
6.2.2.
Customizing Airflow
6.3.
Week 3 - Data Warehouse
6.3.1.
Snowflake 101
6.4.
Week 4 - Analytics Engineering
6.4.1.
Building dbt
6.5.
Week 5 - Batch Processing
6.6.
Week 6 - Stream Processing
6.7.
Week 7 - Data Quality
6.8.
Week 8 - Data Automation
6.9.
Week 9 - Capstone
7.
Hands On
8.
Mock Interview Questions
Part 3: Builing a Second Brain
9.
Brain
10.
Mapping of Contents
Changelog
Copyright
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