You’ll begin this Exploratory Data Analysis (EDA) course by learning how to use descriptive statistics and identify missing data, and apply imputation techniques to fill the gaps in your data.

What is exploratory data analysis?

Steps for exploratory data analysis

Steps to EDA

Initial EDA of AirBnB listings

Identify missing data

Descriptive statistics for a variable

Imputation for missing data

Initial Exploratory Data Analysis in Power BI

In the second chapter of this course you'll learn how to identify and address outliers within the dataset.  You will build histograms to analyze distributions and use winsorizing to remove outliers.

Distributions and outliers

Choices for finding outliers

Histograms and outliers in AirBnB listings

Create your first histogram

Identify outliers

Addressing outliers in the data

Distributions and Outliers

Now it’s time to explore the relationships between categorical variables using proportions. You’ll then use box plots and descriptive statistics to determine how a continuous variable is influenced by a categorical one. 

EDA with categorical variables

Histograms vs. box plots

Exploring categorical variables with AirBnB data

Analyzing a categorical variable

Proportions with categorical variables

Analyzing multiple categorical variables

Creating a box plot

EDA with Categorical Variables

In the final chapter, you’ll dive into scatter plots to analyze the relationship between two continuous variables and calculate the correlation coefficient.

Relationships between continuous variables

Practice interpreting a scatter plot

Exploring AirBnB listings with scatter plots

Analyzing relationships with scatter plots

Adding context to scatter plots

Correlation coefficient

Congratulations!

Relationships between Continuous Variables

Exercises and Datasets

DataCamp vs. Local Experience

Enhance your reports with Power BI's Exploratory Data Analysis (EDA). You'll start by using descriptive statistics to spot outliers, identify missing data, and apply imputation techniques to fill gaps in your dataset. You’ll then learn how EDA in Power BI can help you discover the relationships between variables—both categorical and continuous— by using basic statistical measures and box and scatter plots.

<h2>Introduction to Exploratory Data Analysis in Power BI</h2>
Enhance your reports with Power BI's Exploratory Data Analysis (EDA)! 

This beginner course for data analysts covers foundational aspects of EDA, including descriptive statistics, handling missing data, analyzing distributions, and identifying outliers. You'll learn to use histograms, box plots, and scatter plots to visualize data, interpret distributions, and understand relationships between variables.
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<h2>Apply Statistical Techniques</h2>
Explore how to manage categorical and continuous variables, use advanced visualization techniques, and calculate correlation coefficients. Interactive exercises and real-world examples ensure you can apply these skills to analyze and interpret your data effectively. 


Introduction to DAX in Power BI

Learn how to build impactful reports with Power BI’s Exploratory Data Analysis (EDA) that uncover insights faster and drive business value.

Exploratory Data Analysis in Power BI

Data Analyst in Power BI

Steps to EDA

Exploratory Data Analysis in Power BI

Hands-on interactive exercise