Everything in Power BI is more complicated if you don’t build a good data model. Business Intelligence consultants spend an entire career learning how to build data models, but NOT you! Understanding the fundamentals of dimensional modeling (Star Schema) can get you very far in Power BI. During this session, you will learn what a Star Schema is, building facts and dimensions, understanding relationships, role-playing tables and calculation groups.
Overview
COURSE DIFFICULTY
COURSE DURATION
3h 1m
Skills Learned
After completing this online training course, students will be able to:
Apply window functions for advanced analytical queries
Navigate the platform interface and core features
Apply fundamental concepts to practical scenarios
Database Administrators, Data Analysts
None
01. What you need to get started
02. Introduction to SQL Server Window Functions
03. Window Functions (Introduction)
04. Window Aggregates (Introduction)
05. Window Aggregates (Running Totals)
06. Window Ranking Functions (Row_number)
07. Window Ranking Functions (Rank and Dense Rank)
08. Window Ranking Functions (Identifying Duplicates)
09. Window Analytical Functions (Lag and Lead)
10. Window Analytical Functions (Use Cases)
11. Window Analytical Functions (Working with Blanks)
SKILLS LEARNED
Skills Learned
After completing this online training course, students will be able to:
Apply window functions for advanced analytical queries
Navigate the platform interface and core features
Apply fundamental concepts to practical scenarios
WHO SHOULD ATTEND
Database Administrators, Data Analysts
PREREQUISITES
None
COURSE OUTLINE
01. What you need to get started
02. Introduction to SQL Server Window Functions
03. Window Functions (Introduction)
04. Window Aggregates (Introduction)
05. Window Aggregates (Running Totals)
06. Window Ranking Functions (Row_number)
07. Window Ranking Functions (Rank and Dense Rank)
08. Window Ranking Functions (Identifying Duplicates)
09. Window Analytical Functions (Lag and Lead)
10. Window Analytical Functions (Use Cases)
11. Window Analytical Functions (Working with Blanks)
