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

  • Basic understanding of SQL
  • Familiarity with relational databases
  • Intermediate-level programming experience, preferably in SQL

Audience

  • Database administrators
  • SQL developers
  • Data analysts
 21 Hours

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