Analyzing Data Visualization Requirements
Being able to create visualizations is a powerful skill that you can learn. This course teaches you how to analyze your dataset and requirements, and how to adjust your visualization to create the most impactful visualization possible.
What you'll learn
At the core of creating meaningful data visualizations is a thorough knowledge of understanding your data and your visualization requirements. In this course, Analyzing Data Visualization Requirements, you’ll learn how to prepare to build data visualizations. First, you’ll learn how to distinguish different types of data. Next, you’ll discover how to use visualizations to explore a dataset, or explain a point. Finally, you’ll examine how to adapt a visualization for a specific audience and medium. When you’re finished with this course, you’ll have a foundational knowledge of data visualizations that will help you as you move forward to create visualizations for your own datasets.
Table of contents
- Introducing Qualitative and Quantitative Visualizations 2m
- Defining Qualitative and Quantitative Visualizations 3m
- Exploring Examples of Quantitative Visualizations 2m
- Exploring Examples of Qualitative Visualizations 3m
- Evaluating Strengths and Weaknesses of Qualitative and Quantitative Visualizations 5m
- Combining Quantitative and Qualitative Visualizations 5m
- Demo: Choosing a Qualitative or Quantitative Visualization for a Dataset 5m
- Introducing Numerical and Categorical Data 2m
- Defining Numerical and Categorical Data 3m
- Splitting Numerical Data into Discrete and Continuous 3m
- Splitting Categorical Data into Nominal and Ordinal 4m
- Determining Whether Data is Numerical or Categorical 5m
- Converting Between Numerical and Categorical Data 5m
- Choosing Visualizations for Numerical Data 5m
- Choosing Visualizations for Categorical Data 3m
- Demo: Dividing Data Into Numerical and Categorical 4m
- Introduction to Data Detail Levels 1m
- Why Choosing a Level of Detail Matters 2m
- Showing Trends vs. Detailed Reports 5m
- Examples of Different Detail Levels in Visualizations 6m
- Considering the Visualization Medium 5m
- Changing Scales: When to Adjust the Y-Axis 6m
- Demo: Choosing an Appropriate Level of Detail 4m
- Introduction to Applying Data Visualization Requirement Analysis 1m
- Classifying Data Types 3m
- Creating Exploratory Data Visualizations 3m
- Selecting Data for an Expository Visualization 4m
- Creating an Expository Visualization 4m
- Adapting an Expository Visualization for Different Audiences 3m
- Reviewing the Data Visualization Process 3m
About the author
Chris is an independent software consultant focused on web, mobile, and machine learning. He primarily uses React.js with Node.js or Ruby on Rails for web applications, React Native for mobile applications, and Python for machine learning and data science. He's written an ebook about React, and is excited about teaching software development to others. Recently, he's been experimenting with generative AI models and other advanced AI techniques.