Let's now explore how to **handle missing data** in the dataset  using Power Query. Missing values can lead to **incomplete** and **inaccurate** analysis, so it's essential to address them properly. We'll learn to identify these gaps in our dataset and replace them with appropriate values using techniques like **filling in** with the mean, median, or mode. Additionally, we'll look at forward-fill and backward-fill methods.

What is the primary reason for handling missing data in Power BI?


Power BI is an essential tool for any aspiring data analyst or business professional. Learn how to transform raw data into insightful visualizations and interactive dashboards, connect to various data sources, and create compelling reports for informed decision-making.

Dive into the world of Power BI and build a solid foundation. You'll cover everything from installation and setup to connecting data sources and creating your first report.

Explore essential data preparation techniques, including cleaning, transforming, and combining multiple data sources. You'll also tackle handling missing values, data profiling, and various data manipulation methods.


Master the fundamentals of data modeling, from understanding data models and creating relationships to getting the hang of DAX basics. You'll also learn to create measures and calculated columns.


Discover various visualization techniques and customize visuals for better insights. You'll also explore advanced features like slicers, filters, and drill-down/drill-through capabilities to enhance your data analysis.


Boost the usability and storytelling power of your reports by using themes, configuring report pages, and leveraging advanced features like the Analyze feature and identifying outliers. You'll also create groups, bins, and clusters for deeper insights.


Introduction to Power BI

Handling Missing Values