Course
Exploratory Data Analysis in Power BI
БазовыйУровень мастерства
Обновлено 10.2024Power BIExploratory Data Analysis3 ч9 videos26 Exercises2,050 XP48,827Свидетельство о достижениях
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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.Предварительные требования
Introduction to DAX in Power BI1
Initial Exploratory Data Analysis in Power BI
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.
2
Distributions and Outliers
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.
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.
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.
Exploratory Data Analysis in Power BI
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