Understanding Data Visualization from Scratch

 In today's information society, we are overwhelmed with vast amounts of data, and the ‘essence’ is often hidden behind numbers and tables, making it difficult to convey.

This is where data visualization comes in.

Data visualization is a technique that transforms complex data into visual representations such as graphs, charts, and infographics, facilitating intuitive understanding and supporting decision-making.

This article explains what data visualization is, how it is used, and the benefits of learning it.

1. What is Data Visualization?

Data visualization plays the following roles:

- Concretizing Abstract Information: It converts rows of numbers and vast statistical data into visuals such as graphs, charts, heatmaps, and network diagrams. This allows you to instantly see patterns, trends, outliers, and relationships, and communicate the ‘story’ of the data.

- Promoting Decision-Making: Visualized data serves as a basis for making important business decisions. Even in situations with multiple variables, visual information helps with rapid understanding, enabling the formulation of more appropriate strategies and responses.

- A Communication Tool: When data scientists and analysts explain results to management, other departments, or the general public, diagrams and graphs are highly effective. They provide a means of conveying complex information and large numbers in an easily digestible format.

2. In What Scenarios is it Used?

Due to its versatility and effectiveness, data visualization is widely used in various fields.

- Business & Marketing

Visualizing sales, customer trends, and the effectiveness of marketing campaigns through dashboards and reports helps with rapid decision-making and strategy adjustments. For example, line charts showing sales trends, pie charts showing customer segments, and ROI comparisons of advertising campaigns.

- Science & Research

By visualizing vast experimental data and observational data, researchers can discover hidden patterns and correlations, and formulate new hypotheses. For example, scatter plots of experimental results, time-series graphs of climate change, and heatmaps of gene expression.

- Healthcare

By visualizing patient vital signs, diagnostic data, and the spread of infectious diseases, healthcare professionals can quickly grasp the situation and determine the optimal treatment methods. For example, real-time graphs for patient monitoring, charts predicting the demand for medical resources.

- Public Policy & Administration

Policymakers and local governments convert statistical data into maps and graphs to understand population dynamics, economic conditions, and traffic situations by region. This information is used to provide information to residents and formulate plans. For example, maps showing regional population distribution, heatmaps of public transport usage, and visualizations of crime rates.

- Media & Journalism

News articles frequently use clear graphics and infographics to explain statistical data and social issues, helping readers understand the information.

3. What are the Benefits of Learning It?

Learning data visualization offers benefits beyond simply creating beautiful graphs:

- Improved Data Analysis Skills

Visualization is a key technique for intuitively grasping patterns and trends in data. The process of selecting and creating appropriate graphs and charts develops your ability to understand the story behind the data, contributing to an overall improvement in analytical skills.

- Enhanced Communication Skills

The ability to visualize complex data and explain it clearly is invaluable in team communication and presentations. Creating persuasive materials is essential for promoting data-driven decision-making.

- Accelerated Decision-Making

In fields requiring rapid judgment, such as business and public policy, visualized information becomes a powerful asset.  Intuitive understanding of information enables timely responses.

- Broadened Career Opportunities

In the modern era of big data, data visualization skills are in demand across all fields, including marketing, business analysis, scientific research, and healthcare. As a practical skill, it can directly contribute to career advancement.

- Proficiency in Tools and Technologies

Learning diverse visualization tools and libraries such as Python (matplotlib, seaborn, Plotly) and R (ggplot2) will build a flexible skillset capable of meeting various needs.

In conclusion

Data visualization is an extremely useful technique for extracting the essence from vast amounts of information and communicating it clearly.  For those embarking on a journey into data science, data visualization will undoubtedly be a powerful weapon.  Start by actually using the tools and challenging yourself to visualize various datasets to experience its appeal and potential.

If you want to learn data visualization, we recommend this book (access here).