- What is PowerBI?
- Download and Install Power BI Desktop
- Quick Interface Tour
- Mini Project: Transform Data
- Mini Project: Visualize Data
- Mini Project: Creating a Data Model
- Exploring Query Editor
- Connecting to our DataSource
- Editing Rows
- Changing DataTypes
- Replacing values
- Close and Apply
- Connecting to a CSV File
- Connecting to a Webpage
- Extracting Characters
- Splitting and Merging Columns
- Creating Conditional Columns
- Creating Columns from Examples
- Merging Queries
- Pivoting and Unpivoting
- Appending Queries
- Practice and Solution: Population Table
- The Fact-Dimension-Model
- Practice: Load the Dimension Table
- Organizing Our Queries in Groups
- Entering Data Manually
- Creating an Index Column
- Workflow and More Transformation
- Module Summary
- Practice Assignment 1
- Advanced Editor-Best Practices
- Performance: References Versus Duplicating
- Performance: Enable/Disable Load and Report Refresh
- Group By
- Mathematical Operations
- Run Python Script
- Using Parameters to Dynamically Transform Data
- M Formula Language: Basics
- M Formula Language: Values, Lists, and Tables
- M Formula Language: Functions
- Why a Data Model?
- Create and Edit Relationships
- One-to-Many and One-to-One Relationship
- Many-to-Many(m:n) Relationship
- Cross-Filter Direction
- Activate and Deactivate Relationships
- Practice Assignment 2
- Our First Visual
- The Format Tab
- Understanding Tables
- Conditional Formatting
- The Pie Chart
- All about the filter Visual
- The Filter Pane for Developers
- Cross Filtering and Edit Interactions
- Practice Assignment 3
- Synching Slicers across Pages
- Creating Drilldowns
- Creating Drill-Throughs
- The Treemap Visual
- The Decomposition Tree
- Understanding the Matrix Visual
- Editing Pages
- Buttons and Actions
- Bookmarks to Customize Your Report
- Analytics and Forecasts with Line Charts
- Working with Custom Visuals
- Get Data Using Python Script
- Python in Power BI
- Setting Up Python for Power BI
- Transforming Data Using Python
- Creating Visualizations Using Python
- Violin Plots, Pair Plots and Ridge Plots Using Python
- Machine Learning (BayesTextAnalyzer) Using Python
- Introduction
- The Project Data
- Measures Versus Calculated Columns
- Automatically Creating a Data Table in DAX
- Calendar
- Creating a Complete Data Table with Features
- Creating a Key Measure Table
- Aggregation Functions
- The Different Versions of COUNT
- SUMX- Row-Based Calculations
- CALCULATE- The Basics
- Changing the Context with FILTER
- ALL
- ALLSELECT
- ALLEXCEPT
- Introduction - Best Practices
- Show Empathy and Identify the Requirements
- Find the Most Suitable KPIs
- Choose an Effective Visual
- Make Use of Natural Reading Patterns
- Tell a Story Using Visual Cues
- Avoid Chaos and Group Information
- JSON and REST API
- Setting Up a Local MySQL Database
- Connecting to a MySQL Database in Power BI
- Connecting to a SQL Database (PostgreSQL)
