Description

Introduction
This course equips participants with essential skills in Power BI for creating efficient data models and writing DAX calculations. Learn how to structure data, define relationships, and implement business logic using DAX to drive actionable insights.

Prerequisites

• Basic understanding of Excel and data analysis concepts

• Familiarity with Power BI Desktop interface

• Knowledge of tables, columns, and basic formulas

Table of Contents
1. Introduction to Power BI Data Modeling
 1.1 Understanding Data Models in Power BI
 1.2 Importing and Transforming Data
 1.3 Tables, Columns, and Data Types

2. Relationships and Data Modeling Concepts
 2.1 Creating and Managing Relationships
 2.2 One-to-Many and Many-to-Many Relationships
 2.3 Star Schema vs Snowflake Schema
 2.4 Handling Role-Playing Dimensions

3. Introduction to DAX (Data Analysis Expressions)
 3.1 DAX Syntax and Structure
 3.2 Calculated Columns vs Measures
 3.3 Basic DAX Functions: SUM, AVERAGE, COUNT, DISTINCT

4. Intermediate DAX for Analytics
 4.1 Time Intelligence Functions
 4.2 Filtering and Row Context
 4.3 Conditional Logic in DAX
 4.4 Handling Blanks and Errors

5. Advanced DAX Concepts
 5.1 CALCULATE and Context Modification
 5.2 Variables and Performance Optimization
 5.3 Advanced Aggregations and Calculations

6. Optimizing and Validating Data Models
 6.1 Best Practices for Model Performance
 6.2 Data Model Optimization Techniques
 6.3 Troubleshooting Common Issues

7. Reporting and Visualization Integration
 7.1 Using DAX Measures in Visuals
 7.2 Dynamic Titles, KPIs, and Tooltips
 7.3 Interactive Reports with Slicers and Filters

By the end of this course, participants will confidently design robust data models in Power BI, leverage DAX for insightful calculations, and deliver high-performance reports to support data-driven decisions.