Overview What You Will Learn Curriculum Instructor

Course Overview

Microsoft Power BI Desktop is a companion desktop application to Power BI. With Power BI Desktop, you can: Get data The Power BI Desktop makes discovering data easy. You can import data from a wide variety of data sources. After you connect to a data source, you can shape the data to match your analysis and reporting needs. 

This course will begin with a basic introduction to Power BI followed by downloading and installation and a quick interface tour. You will then learn about data transformation, followed by creating a data model using Nmap. You will also gain in-depth knowledge on how to visualize data effectively. Later, in this course, you will explore various advanced features such as working with parameters, using R scripts, optimizing performance, and row-level security. 

By the end of the course, you will have mastered Microsoft Power BI.

What You Will Learn

  • Learn the complete workflow in Power BI from A to Z
  • Advanced analytics with DAX - calculated columns & measures
  • All-in-One: Power BI Desktop
  • Power BI Cloud & Power BI Mobile!
  • Learn how to design and implement professional reports
  • Learn storytelling with data to visualize your data effectively

Program Curriculum

  • Welcome!
  • What is Power BI?
  • Download & Installing Power BI Desktop
  • Quick Interface Tour
  • Mini Project: Transform Data
  • Mini Project: Visualize Data
  • Mini Project: Creating a Data Model
  • Course Outline: What Will You Learn in This Course?
  • $7 Million Cybersecurity Scholarship by EC-Council
  • Chapter 1 Quiz

  • Creating Our Initial Project File
  • Working with the Attached Project Files

  • Exploring the Query Editor
  • Connecting to Our Data Source
  • Editing Rows
  • Changing Data Types
  • Replacing Values
  • Close & Apply
  • Connecting to a csv File
  • Connecting to a Web Page
  • Extracting Characters
  • Splitting & Merging Columns
  • Creating Conditional Columns
  • Creating Columns from Examples
  • Merging Queries
  • Pivoting & Unpivoting
  • Appending Queries
  • Practice & Solution: Population Table
  • Fact-Dimension-Model
  • Practice: Load the Dimension Table
  • Organizing Our Queries in Groups
  • Entering Data Manually
  • An Index Column
  • Workflow & More Transformations
  • Module Summary
  • Chapter 3 Quiz

  • Advanced Editor - Best Practices
  • Performance: References vs. Duplicating
  • Performance: Enable/Disable Load & Report Refresh
  • Group by
  • Mathematical Operations
  • Run R Script
  • Using Parameters to Dynamically Transform Data
  • M Formula Language: Basics
  • M Formula Language: Values, Lists, & Tables
  • M Formula Language: Functions
  • M Formula Language: More Functions & Steps
  • Chapter 4 Quiz

  • Why a Data Model?
  • Create & Edit Relationships
  • One-to-many & One-to-one Relationship
  • Many-to-many (m:n) Relationship
  • Cross Filter Direction
  • Activate & Deactivate Relationships
  • Module Summary
  • Chapter 5 Quiz

  • 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 & Edit Interactions
  • Creating Drill Downs
  • Syncing Slicers Across Pages
  • Creating Drill Throughs
  • The Tree Map Visual
  • The Decomposition Tree
  • Understanding the Matrix Visual
  • Editing Pages
  • Buttons & Actions
  • Bookmarks to Customize Your Report
  • Analytics and Forecasts with Line Charts
  • Working with Custom Visuals
  • Get Data Using R Script & R Script Visual
  • Asking Questions - Q&A Visual
  • Wrap up - Data Visualization
  • Chapter 6 Quiz

  • Python in Power BI - Plan of Attack
  • Setting up Python for Power BI
  • Transforming Data using Python
  • Creating Visualizations using Python
  • Violin Plots, Pair Plots, & Ridge Plots using Python
  • Machine Learning (BayesTextAnalyzer) using Python
  • Performance & Troubleshooting
  • Chapter 7 Quiz

  • Introduction
  • The Project Data
  • Measures vs. Calculated Columns
  • Automatically Creating a Date Table in DAX
  • CALENDAR
  • Creating a Complete Date Table with Features
  • Creating Key Measure Table
  • Aggregation Functions
  • The Different Versions of COUNT
  • SUMX - Row Based Calculations
  • Chapter 8 Quiz

  • CALCULATE - The Basics
  • Changing the Context with FILTER
  • ALL
  • ALLSELECTED
  • ALLEXCEPT
  • Chapter 9 Quiz

  • Intro - Best Practices
  • Show Empathy & Identify the Requirements
  • Find the Most Suitable KPIs
  • Choose an Effective Visual
  • Make Use of Natural Reading Pattern
  • Tell a Story using Visual Cues
  • Avoid Chaos & Group Information
  • Wrap up - Storytelling with Data
  • Chapter 10 Quiz

  • How to Go on Now?
  • Power BI Pro vs. Premium & Signing up
  • Exploring the Interface
  • Discovering your Workspace
  • Connecting Power BI Desktop & Cloud
  • Understanding Datasets & Reports
  • Working on Reports
  • Updating Reports from Power BI Desktop
  • Creating and Working with Workspaces
  • Installing & using a Data Gateway
  • Get Quick Insights
  • Creating Dashboards
  • Sharing Our Results through Apps
  • Power BI Mobile App
  • Creating the Layout for the Mobile App
  • Wrap up - Power BI Cloud
  • Chapter 11 Quiz

  • Introduction
  • Creating a Row-Level Security
  • Row-Level Security in the Cloud
  • Row-Level Security & Data Model
  • Dynamic Row-Level Security
  • Dynamic Many-to-Many RLS
  • Hierarchical Row-Level Security
  • Chapter 12 Quiz

  • JSON & REST API
  • Setting up a Local MySQL Database
  • Connecting to a MySQL Database in Power BI
  • Connecting to a SQL Database (PostgreSQL)

  • Congratulations & Next Steps
Load more modules

Instructor

Nikolai Schuler

Nikolai Schuler is a data scientist and BI consultant. While going through hours of research and training, Nikolai came up with the idea of creating a course that would offer extremely valuable content but that would be at the same time easy to follow due to its structure. His goal is to help as many people as possible to pursue their desired career in this new Digital Age by enabling them to upgrade their data analysis skills. I am proud to say that he is heading in the right direction as his courses have already found their audience in over 170 countries and received thousands of positive feedbacks.

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