Data visualization is the art of creating maximum impact through an insightful representation of your data. It involves selecting the right chart type, creating consistent and neat aesthetics, being contextual, answering the right questions, and designing the right interactivity. As you can see, a lot of things have to go right to create a powerful visualization.
Why is Data Visualization Important?
To understand the full-force of data visualization, watch Hans Rosling’s most famous TED-talk or better still, interact with the Gapminder tool to explore insights about the changes in world income and life expectancy since 1800.
Human eyes are more drawn to colors and patterns, which is why data visualization tools and technologies have found their way to the business information systems and contribute towards analyzing massive data and information for making data-driven decisions. Data visualization has helped to understand trends, outliers, and patterns in data at both individual and organizational levels. Its usage is as basic as for managing some data of regular expenditure at home, to as advanced as managing organizational data.
Learning Data Visualization
Since data visualization is critical to advanced analytics, big data, and data science, that’s why it is highly recommended that every data scientist develops data visualization and analytical skills. To help you, this article lists some of the best data visualization courses available online.
Those of us working in the analytics related roles know that there is a lot of effort that goes into extracting, cleaning, and loading data before it is ready to be processed for visualization. In this scope of this discussion, however, let’s assume that the hard part of getting data is done and we have to only focus on the harder part of creating impactful visualizations.
In this article, we have curated a list of courses that can help you get started with data visualization. We have divided this article based on the current skills and tools that you are comfortable with. Even if you’re not a programmer, we expect some understanding of analytics (could even be in excel). For keeping the list short and powerful, we have based this list on the most powerful tools/technologies for data visualization, such as Tableau, R, Python, D3, PowerBI, etc.
Let’s have a look at these courses:
Data Visualization: A Practical Approach for Absolute Beginners by Microsoft on edX
Course Description – The course targets data visualization beginners and helps them to learn the theories and techniques of data visualization for data analysis. In this course, you will learn about building the most-used and simplest data visualizations and chart types, and get an idea of how basic data visualization artifacts are improved by interaction, design, and the science of visualization.
Duration – 4 weeks
Efforts – 2 -3 hours per week
Difficulty Level – Beginner
Subject – Data Analysis & Statistics
- Module 1: Visual Literacy
- Module 2: Visual Analysis
- Module 3: Visualizations for Business
- Module 4: Visualizations of Tomorrow
Data Visualization with Tableau Specialization on Coursera
Rating – 4.5 stars (6,662 ratings)
Duration – 6 Months
Skill Level – Beginner
Program Description – The course is ranked among the best online courses in Data Visualization. This specialization is designed for every person who intends to learn data visualization without having any prior experience in Tableau. It will help you to generate powerful reports and dashboards, which can help in making smart business decisions using business data. The specialization also includes a capstone project at the end of the course, to help create visualizations, dashboards, and data models, and present the data before business leaders of a fictitious company.
This specialization includes 5 courses –
Course 1 – Fundamentals of Visualization with Tableau
This is the first course of the specialization and teaches the basics of data visualization using Tableau, and will help you to see and understand data in a descriptive way. In this 15 hours long course, you will learn to –
- Install Tableau Public Software and create a visualization
- Examine and navigate the Tableau Public workspace
- Practice and connect to different data sources
- Examine ways to define your project
Course 2 – Essential Design Principles for Tableau
This is the second part of the main course that will help you to analyze and apply essential design principles to Tableau visualizations. By the end of the previous course, you should get a complete idea about the Tableau tool and have a basic knowledge of the data visualization concepts. In this course, you will explore how to –
- Examine and improve an ineffective visualization
- Examine and improve an ineffective visualization
- Apply visualization best practices
- Create and design visualizations that work best for the target audience
Course 3 – Visual Analytics with Tableau
The third course of the specialization dives deeper into charting, dates, table calculations, and mapping using Tableau tools. You will also get to learn about charting guidelines, create custom and quick table calculations and parameters. The course covers –
- Create a chart using Tableau
- Create dates using calculated fields
- Customize table calculations
- Customize and create dual layer maps
With the help of this course, you can create a powerful story using your data points for maximum impact. You will also learn to apply advanced functions within Tableau, such as hierarchies, actions, and parameters to guide user interactions. This is a 19 hours course that enables you to learn to –
- Combine the data and follow the best practices to present your story
- Create calculated fields for KPIs to build a figure that will be used to measure progress in the data
- Assemble a dashboard
- Analyze concepts and techniques for compelling storytelling with data
Course 5 – Data Visualization with Tableau Project
This is a project-driven course that requires you to complete a project stepwise where you will find the business data, import it in Tableau, create a dashboard, and extract meaningful insights. It will take around 16 hours for you to complete this course and you will learn to –
- Develop a project proposal
- Assess the quality of the data and perform exploratory analysis
- Create KPIs and dashboards and assess your analysis
- Create your data story and write a narrative to accompany your visualization
Suk S. Brar, M.B.A.: Lead Business Consultant, Blue Shield of California
Govind Acharya: Principal Analyst – Budget and Institutional Analysis
Hunter Whitney: Sr. Consultant, Author, Instructor – University of California, Davis
Data Science: Visualization (using R) by Harvard University on edX
Course Description – This course is a part of the Professional Certificate Program in Data Science of Harvard University and covers the fundamentals of data visualization and exploratory data analysis. It will also cover the ways of handling different types of mistakes, biases, systematic errors, and other unexpected issues in data that may lead to incorrect interpretation and how they should be handled with care. The course instructor is Rafael Irizarry, Professor of Biostatistics, T.H. Chan School of Public Health.
In this course, you will learn –
- Data visualization principles
- How to communicate data-driven findings
- How to use ggplot2 to create custom plots
- The weaknesses of several widely used plots and why you should avoid them
Duration – 8 weeks
Efforts – 1 – 2 hours per week
Difficulty Level – Beginner
Subject – Data Science
Introduction to Data Visualization in Python on DataCamp
Course Description – This course will help you to enhance your Python skills and develop a stronger foundation in data visualization in Python. The course will cover topics like customizing graphics, plotting two-dimensional arrays, statistical graphics, and working with time series and image data. You will also get to learn about the Matplotlib library and get an overview of Seaborn, a package for statistical graphics.
- Customizing plots (Free course)
- Plotting 2D arrays
- Statistical plots with Seaborn
- Analyzing time series and images
Dhavide Aruliah, Data Scientist and Applied Mathematician
Bryan Van de Ven, Software Engineer, Anaconda and Developer of Bokeh
D3.js Data Visualization Fundamentals on Pluralsight
Course Description – This is a beginner level course that would help you to learn the usage of D3.js (data-driven documents) for creating presentable and insightful data visualizations. Starting with the core concepts of D3.js version 3, the course also includes examples of building data visualizations and business dashboards. It is a 4-5 hours long video.
- The Basics
- Basic Charting
- Working with Data Part 1 – External Data Sources
- Working with Data Part 2 – Getting Data from Web APIs
- Enhancing Your Viz Part 1 – Scales and Axis
- Enhancing Your Viz Part 2 – Interactivity
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