Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction
- Defining Analytics Functions
- Advantages and practical applications
- Overview of standard Analytics Functions
Core Analytics Functions
- ROW_NUMBER(), RANK(), DENSE_RANK()
- Comprehending PARTITION BY and ORDER BY clauses
- Illustrative examples and applications
Statistical Analytics Functions
- SUM(), AVG(), MIN(), MAX()
- LEAD() and LAG()
- Practical scenarios and use cases
Windowing Clause
- Exploring the WINDOWING clause
- Understanding UNBOUNDED, CURRENT ROW, and N PRECEDING/FOLLOWING
- Practical applications
Advanced Analytics Functions
- FIRST_VALUE() and LAST_VALUE()
- PERCENTILE_CONT() and PERCENTILE_DISC()
- Applications and comparative analysis
Complex Queries with Analytics Functions
- Merging Analytics Functions with GROUP BY
- Nested Analytics Functions
- Real-world examples
Optimizing Analytics Functions
- Efficient usage of Analytics Functions in large-scale datasets
- Evaluating query performance
- Indexing strategies
Troubleshooting and Best Practices
- Identifying and resolving common issues
- Best practices for drafting efficient queries
- Tips for maintaining and updating Analytics Function queries
Summary and Next Steps
Requirements
- Foundational knowledge of SQL
- Familiarity with relational database concepts
- Intermediate programming experience, with preference given to SQL knowledge
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.
