Course overview
This course equips participants with the skills to leverage DAX for advanced data transformation and analytics. Through hands-on learning, participants will gain a solid foundation in building and optimizing data models while exploring advanced calculation techniques to turn raw data into actionable insights. Key topics include mastering relationships, schemas, and dynamic measures to confidently address complex data challenges. The course also covers advanced methods like time intelligence and performance optimization, enabling precise analysis and reporting. Participants will learn to create interactive, impactful Power BI dashboards, empowering data-driven decision-making and transforming complex datasets into meaningful business insights.
Target audience
This course is designed for data analysts, Power BI users, Excel professionals, and business intelligence specialists seeking to enhance their data transformation and performance optimization skills.
Course objectives
- Introduce DAX concepts and its applications in data transformation.
- Explain data modeling principles, including relationships and schemas.
- Highlight advanced calculation techniques for complex analytics.
- Demonstrate the use of time-based analysis for trends and insights.
- Support the creation of dynamic and interactive reports using DAX.
Target competencies
Course methodology
The course employs a hands-on methodology with interactive workshops, real-world case studies, and group exercises, ensuring practical learning and skill application for mastering DAX concepts effectively.
Course outline
FUNDAMENTALS OF DAX AND ITS APPLICATIONS
Introduction to DAX
- What is DAX?
- Importance of DAX in Power BI and Excel.
- Key Concepts: Tables, Columns, Measures.
Basic Syntax and Functions
- Overview of DAX syntax.
- Using Basic Functions (SUM, AVERAGE).
- DIVIDE Function.
Iterator Functions
- Introduction to Iterator Functions (SUMX, AVERAGEX).
- Scenarios of Using Iterators.
DATA MODELING PRINCIPLES
Overview of data model
- The data model and its role in analytics.
- Relationships: Terminology & Logic.
- Manage Relationships - How to Spot Problems.
Data Modeling Best Practices
- Many-to-Many Relationships.
- Create a Dynamic Calendar Table.
- Star Schema Vs. Snowflake.
- Why Not One Big Table? Optimizing Performance.
- Maintaining robust data models.
INTERMEDIATE DAX CONCEPTS
Combining DAX functions
- RELATED & SUMX.
Time Intelligence Functions
- Introduction to Time Intelligence.
- Year-to-Date (YTD), Month-Over-Month (MOM).
Error Handling in DAX
- Functions: ISERROR, IFERROR.
- Debugging Common Errors in DAX Formulas.
ADVANCED DAX TECHNIQUES
Advanced Calculations with CALCULATE
- Using CALCULATE with Multiple Filters.
- Dynamic Filtering Techniques.
- CALCULATE Modifiers (ALL, REMOVEFILTERS, KEEPFILTERS).
Working With Relationships
- Understanding Relationship Concepts.
- Functions: RELATED, RELATEDTABLE.
- USERELATIONSHIP to Activate Inactive Relationships.
DYNAMIC REPORTING USING DAX
Create a Dedicated Measures Table
- Techniques for DAX measures Aggregation.
Dynamic Measures and KPIs
- Creating Measures that Adapt to User Interaction.
- Building KPI Visuals with DAX.
Dynamic Reports
- Using DAX to Create Interactive Reports.
- Building a Complete Dashboard.
Want to run this for your team?
Request a tailored quote - we'll come back with delivery options, language preferences, group-size pricing, and dates that work for you.
Request a quote