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Exploratory Data Analysis in Power BI

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3 hr
2,050 XP
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Loved by learners at thousands of companies


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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  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.

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    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.

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  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.

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  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.

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For Business

Training 2 or more people?

Get your team access to the full DataCamp platform, including all the features.

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Exercises and DatasetsDataCamp vs. Local Experience

collaborators

Collaborator's avatar
Carl Rosseel
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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