Build Accurate Data Models in Power BI

Course description

The course should provide a Beginner Learner an end‑to‑end walkthrough of building a Power BI Desktop data model, guiding learners from initial data connection all the way to validating the finished model with test visuals. At its core, the training emphasizes the importance of structured modeling practices, especially the Star Schema, as the foundation for reliable analytics, fast performance, and intuitive report building. It begins with Connecting to Data Sources, showing how to choose the correct source type and select the specific tables, sheets, or queries to import. From there, the course moves into Power Query transformations, teaching essential shaping tasks such as removing unnecessary columns, filtering rows, splitting or merging columns, and preparing clean dimension tables. Next, learners explore Table Relationships, identifying primary keys, foreign keys, cardinality, and cross‑filter directions to ensure the model behaves predictably. This leads naturally into constructing a proper Star Schema, separating dimension tables (descriptive attributes) from fact tables (transactional data). The course then introduces Calculated Columns and Measures, focusing on KPI logic and time‑intelligence patterns. It also covers essential model‑polishing techniques such as hiding technical fields, renaming columns for clarity, and building hierarchies. Finally, learners validate their work using Test Visuals, checking relationships, slicing across dimensions, and confirming totals and subtotals. By the end, the viewer understands not just how to build a Power BI model, but why each modeling decision matters for accuracy, usability, and long‑term scalability.

Course outline