The preparation phase is the most important step in data analysis. Before data can be effectively analyzed, an effective data model is required, and creating that data model may utilize a wide range of skills. This course teaches the skills needed to load, clean, and organize data in Power Query and create relational tables in Power Query and Power BI. After completing this course, students will be able to effectively source data in Power BI and create a clean and efficient data model for analysis.
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
