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Course Outline
Introduction
- Definition of Analytic Functions
- Advantages and application scenarios
- Survey of commonly used Analytic Functions
Core Analytic Functions
- ROW_NUMBER(), RANK(), DENSE_RANK()
- Deciphering PARTITION BY and ORDER BY clauses
- Illustrative examples and use cases
Statistical Analytic Functions
- SUM(), AVG(), MIN(), MAX()
- LEAD() and LAG()
- Application 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()
- Comparative analysis and use cases
Complex Queries with Analytic Functions
- Integrating Analytic Functions with GROUP BY
- Utilizing nested Analytic Functions
- Real-world case studies
Optimizing Analytic Functions
- Efficient application of Analytic Functions in large datasets
- Evaluating query performance
- Indexing strategies
Troubleshooting and Best Practices
- Identifying and resolving common issues
- Best practices for crafting efficient queries
- Advice for maintaining and updating Analytic Function queries
Summary and Next Steps
Requirements
- Foundational knowledge of SQL
- Working familiarity with relational databases
- Intermediate programming experience, with a preference for 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.
