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Course Outline
Introduction
- Definition of Analytic Functions.
- Benefits and practical 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 knowledge of SQL.
- Familiarity with relational database systems.
- Intermediate programming experience, preferably in SQL.
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.
