Dive into data transformation techniques. Master Power Query, relational table design, and DAX to prepare structured, analysis-ready datasets that support clear insights and professional reporting.
Overview
Syllabus
- Introduction to Data Preparation & Modeling
- Introduction to Data Preparation & Modeling lesson introduces students to the topics, highlights, and prerequisites of the course. And requirements to successfully complete the course are explained.
- Relational Data & Table Structure
- Relational Data & Table Structure lesson teaches the core concepts around working with data from multiple sources and tables. It explains what relational data is and how it works.
- Power Query & M Overview
- Power Query & M Overview lesson highlights the Power Query data wrangling system that is used within Power BI. Specific cleaning and organization tools and techniques are explored.
- Data Cleaning and Organization
- Data Cleaning & Organization lesson takes a practical deep dive into Power Query. Here more complex data cleaning and organization strategies are practiced, and the M language is explained.
- DAX Language & Quantitative Analysis
- DAX Language & Quantitative Analysis lesson dives into DAX, which is the primary analytical language of Power BI. Different foundational concepts around DAX calculations are covered.
- Population Statistics Data Model
- The project asks students to gather data about the US economy to understand better the makeup of the economy and how it’s changing. Students will submit a PowerBI report at the end.
- Microsoft Power BI Workspace
- In this lesson, you'll learn how to set up a Windows desktop workspace to use Power BI
Taught by
Joseph Lozada