Introduction
Introduction to advanced analytics engineering
()
GitHub Codespaces introduction
()
Introduction to CoderPad
()
1. Database Schema
What are database schema?
()
Flat schema
()
Relational schema
()
Star schema
()
Snowflake schema
()
2. Advanced SQL Practice
Advanced SQL techniques
()
Recursive common table expressions (CTEs) and when to use them
()
Improving query performance by indexing tables
()
Updating database tables
()
Window functions
()
Solution: Time series data analysis with Python
()
3. Complex and Problematic Data
Common stumbling blocks in analytics engineering
()
Working with JSON files and fields
()
XMLs and their uses
()
Time series data
()
Dealing with missing data in SQL
()
Solution: Create tests for data with Python
()
Solution: Create tests for data with SQL
()
4. Decision-Making in Analytics Engineering
Decision-making introduction
()
Getting to the root of the problem
()
Investigating the data
()
Planning data projects
()
Avoiding tech debt
()
5. Protecting Data
Why protect and encrypt data?
()
Handling sensitive data
()
Encrypting data for protection
()
Protecting your database
()
Legal and ethical considerations
()
6. Communication Best Practices
Communication facilitates analytics engineering
()
Working with stakeholders
()
Project management for analytics engineering
()
Leading analytics engineering teams
()
Data dictionaries
()
Conclusion
Brief overview of topics covered
()
What to do next
()