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Exploratory Data Analysis in Power BI

4.5+
27 reviews
Beginner

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

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Course Description

Introduction to Exploratory Data Analysis in Power BI

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.

Apply Statistical Techniques

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.
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In the following Tracks

Certification Available

Data Analyst in Power BI

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  1. 1

    Initial Exploratory Data Analysis in Power BI

    Free

    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.

    Play Chapter Now
    What is exploratory data analysis?
    50 xp
    Steps to EDA
    100 xp
    Initial EDA of AirBnB listings
    50 xp
    Identify missing data
    100 xp
    Descriptive statistics for a variable
    100 xp
    Imputation for missing data
    100 xp
  2. 2

    Distributions and Outliers

    Free

    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.

    Play Chapter Now
    Distributions and outliers
    50 xp
    Choices for finding outliers
    50 xp
    Histograms and outliers in AirBnB listings
    50 xp
    Create your first histogram
    100 xp
    Identify outliers
    100 xp
    Addressing outliers in the data
    100 xp
  3. 3

    EDA with Categorical Variables

    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.

    Play Chapter Now
    EDA with categorical variables
    50 xp
    Histograms vs. box plots
    100 xp
    Exploring categorical variables with AirBnB data
    50 xp
    Analyzing a categorical variable
    100 xp
    Proportions with categorical variables
    100 xp
    Analyzing multiple categorical variables
    100 xp
    Creating a box plot
    100 xp
  4. 4

    Relationships between Continuous Variables

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

    Play Chapter Now
    Relationships between continuous variables
    50 xp
    Practice interpreting a scatter plot
    50 xp
    Exploring AirBnB listings with scatter plots
    50 xp
    Analyzing relationships with scatter plots
    100 xp
    Adding context to scatter plots
    100 xp
    Correlation coefficient
    100 xp
    Congratulations!
    50 xp
For Business

GroupTraining 2 or more people?

Get your team access to the full DataCamp library, with centralized reporting, assignments, projects and more

In the following Tracks

Certification Available

Data Analyst in Power BI

Go To Track

datasets

Exercises and DatasetsDataCamp vs. Local Experience

collaborators

Collaborator's avatar
Carl Rosseel

prerequisites

Introduction to DAX in Power BI
Maarten Van den Broeck HeadshotMaarten Van den Broeck

Senior Content Developer at DataCamp

Maarten is an aquatic ecologist and teacher by training and a data scientist by profession. He is also a certified Power BI and Tableau data analyst. After his career as a PhD researcher at KU Leuven, he wished that he had discovered DataCamp sooner. He loves to combine education and data science to develop DataCamp courses. In his spare time, he runs a symphonic orchestra.
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Jacob Marquez HeadshotJacob Marquez

Data Scientist at Microsoft

Jacob H. Marquez is an insatiable learner and lifelong builder. He is a data scientist by day, answering audacious questions to support customer experience and company goals. He is a serial hobbyist by day and night: being an educator, building a coffee recommendation app, drinking coffee, writing on Medium, and amateur cycling and muay thai. He has a bachelor's in psychology and a master's in computational analytics (2024).
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Don’t just take our word for it

*4.5
from 27 reviews
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  • Wael R.
    about 2 months

    Clear, concise and understandable

  • Thomas K.
    2 months

    As a gamer, I have done my fair share of grinding to gain levels and skills in computer games. Data camp lets me tap in the same reservoir of energy to build my real RL data skills. Now I'm off to get more data camp XP.

  • Nicolas F.
    4 months

    These were fundamental skills to learn on how to conduct EDA in Power BI.

  • MOKONIU L.
    9 months

    A very good course that can help to link the spaces in one's knowledge of EDA and also carry out EDA

  • Mamkon O.
    11 months

    Excellent

"Clear, concise and understandable"

Wael R.

"As a gamer, I have done my fair share of grinding to gain levels and skills in computer games. Data camp lets me tap in the same reservoir of energy to build my real RL data skills. Now I'm off to get more data camp XP."

Thomas K.

"These were fundamental skills to learn on how to conduct EDA in Power BI."

Nicolas F.

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