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Course Outline
Introduction
- What are Analytic Functions?
- Benefits and use cases
- Overview of common Analytic Functions
Basic Analytic Functions
- ROW_NUMBER(), RANK(), DENSE_RANK()
- Understanding PARTITION BY and ORDER BY clauses
- Examples and use cases
Statistical Analytic Functions
- SUM(), AVG(), MIN(), MAX()
- LEAD() and LAG()
- Use cases and scenarios
Windowing Clause
- Exploring the WINDOWING clause
- Understanding UNBOUNDED, CURRENT ROW, and N PRECEDING/FOLLOWING
- Practical applications
Advanced Analytic Functions
- FIRST_VALUE() and LAST_VALUE()
- PERCENTILE_CONT() and PERCENTILE_DISC()
- Use cases and comparisons
Complex Queries with Analytic Functions
- Combining Analytic Functions with GROUP BY
- Nested Analytic Functions
- Real-world examples
Optimizing Analytic Functions
- Efficient use of Analytic Functions in large datasets
- Analyzing query performance
- Indexing strategies
Troubleshooting and Best Practices
- Identifying and resolving common issues
- Best practices for writing efficient queries
- Tips for maintaining and updating Analytic Function queries
Summary and Next Steps
Requirements
- Foundational understanding of SQL.
- Familiarity with relational database concepts.
- Intermediate-level programming experience, preferably in SQL.
Target Audience
- Database administrators.
- SQL developers.
- Data analysts.
21 Hours
Testimonials (2)
Doing Exercise
Joe Pang - Lands Department, Hong Kong
Course - QGIS for Geographic Information System
Hands-on examples allowed us to get an actual feel for how the program works. Good explanations and integration of theoretical concepts and how they relate to practical applications.
