Understanding Data Modelling in Power BI: Joins, Relationships, and Schemas Explained

Data Modelling in Power BI: A Comprehensive Guide

Data modelling is the backbone of effective analysis in Power BI. It involves structuring and organizing your datasets to ensure that they are clean, efficient, and ready for insightful visualizations. This guide will walk you through the essential concepts and best practices for data modelling in Power BI.

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1. Data Modelling Overview

Data modelling is crucial because it defines how data is structured and interpreted within Power BI. Proper data modelling ensures that your datasets are clean, efficient, and ready for analysis. It involves:

• Cleaning Data: Removing duplicates, handling missing values, and ensuring consistency.
• Joining Tables: Combining related tables to create a unified dataset.
• Defining Relationships: Establishing logical connections between tables in Power BI.

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2. Joins in Power Query

Joins are used to combine data from multiple sources into a single table. In Power BI, you can perform joins using the Power Query Editor:

Types of Joins

1. INNER JOIN

   • Combines only records that exist in both tables.
   • Example: Which students have recorded test scores? (Alice and Brian)

2. LEFT JOIN

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