A Beginner’s Guide to Data Visualization

Data is an essential asset for every organization. However, possessing large volumes of data cannot help you make informed business decisions. Translating this complex information into a format your stakeholders can understand is crucial. By leveraging data visualization, you can make your data accessible and actionable. 

This article will explore data visualization in detail, including its advantages and the top five tools you can use for visualizing your data. It will also introduce you to several real-world data visualization examples to help you understand the scope of this technique.  

What Is Data Visualization?

Data visualization involves graphically representing raw data by transforming it into visual elements like charts, graphs, or maps. This makes it easier to explain and interpret complex information. Data visualization helps you identify patterns, trends, and outliers within your data that might be difficult to spot in numerical form. 

Using a visual approach, you can quickly gain insights from your data and make informed business decisions. Data visualization is widely used across industries, such as business, science, geography, and technology, to communicate new findings to a broader audience. 

Why Is Data Visualization Important?

With data visualization, you can compress the information residing in large volumes of data into a digestible, easy-to-remember format. It helps you create compelling narratives that convey your ideas while keeping your audience engaged. Data visualization promotes a data-driven culture within your organization by making data more accessible and understandable.

Here are five reasons why data visualization is crucial:

• Facilitates Compliance and Reporting: Visual reports can simplify compliance processes by enabling easier tracking and reporting on key metrics. 
• Bridges Communication Gaps: Visual data can be leveraged to break down communication barriers between technical and non-technical stakeholders, fostering better collaboration.
• Encourages Exploration: Interactive visualizations allow you to explore data from multiple perspectives, leading to new insights and discoveries.
• Contrasting Datasets: By graphically comparing multiple datasets, you can discover unexpected relationships, differences, and correlations that might not be apparent. 
• Supports Real-Time Monitoring: Dashboards with real-time data visualization allow your organization to monitor performance and react swiftly to disruptions.

Types of Data Visualization

When you think of data visualization, some of the most common types are bar graphs, pie charts, and line graphs created using Microsoft Excel. However, many data visualizations are now available based on their usage and requirements. 

In this section, you will explore some of the most effective and interesting types of data visualizations.

• Treemaps: A treemap displays hierarchical data in a nested format in rectangles, where each rectangle’s size represents a proportional percentage of data value. They help visualize your file systems or organizational charts.

• Gantt Charts: Gantt charts are bar charts that visualize the timelines of projects and their dependencies. You can use them for project management tasks to track progress and identify potential bottlenecks.

• Heat Maps: A heat map uses color gradients to represent data such as temperature distributions or geographical patterns across a two-dimensional grid. It showcases the intensity or frequency of data points, making it easier for you to spot trends or outliers. 

• Box-and-Whisker Plots: These are also known as box plots. They help summarize a dataset’s distribution by showing the median, quartiles, and potential outliers. You can use them to identify variability and skewness in your data.

• Population Pyramids: With population pyramids, you can visualize and analyze demographic trends and patterns, such as existing age groups, gender imbalances, and future population growth prediction.

• Area Charts: Area charts are like line charts, but the area beneath the line is filled in. You can utilize them to track changes over time and visualize cumulative totals or trends across multiple data series.

• Highlight Table: Highlight tables are simple tables with conditional formatting applied to highlight specific values or data points using color, shading, or other visual cues. They are beneficial for quickly drawing attention to important information within a table.

• Bullet Graphs: Bullet graphs are a simplified version of bar charts that help you compare a single value to a target or benchmark. They are often used to visualize performance metrics, such as sales targets or customer ratings.

Advantages and Disadvantages of Data Visualization

Data visualization is a powerful technique that enhances data comprehension using graphical representations. However, like any other technique, it has advantages and disadvantages. Understanding them is crucial to maximizing the potential of data visualization.

Advantages

• Data visualization allows you to easily share the crux of complex data, enabling stakeholders to grasp essential details quickly and collaboratively plan the next steps.
• You can interact with your data more effectively, explore various perspectives, and drill down into specific details to gain a deeper understanding.
• Data visualization offers a clear and concise overview of your data, enabling you to identify opportunities, risks, and potential areas for improvement.

Disadvantages

• Data visualizations can be misleading or oversimplified if not designed carefully or lack the necessary context, leading to incorrect conclusions and poor decisions.
• Complex visualizations with too much information can be overwhelming. This makes extracting meaningful insights or understanding the key message difficult.
• Data visualization is heavily dependent on the quality of the underlying data. If your data is inaccurate, incomplete, or biased, the visualizations will also be flawed.

Examples of Data Visualization

Many advanced techniques, such as infographics, bubble clouds, and time series charts, are available to help express your data in the most efficient way. Below are some real-world data visualization examples:

Active Satellites in Space

This data visualization was created for Scientific American to showcase the diverse population of satellites orbiting Earth. The satellites are clustered and arranged in grids based on country, orbit, and type—business/commercial, civil, amateur/academic, or defense. 

The graphic provides detailed information about each satellite, including its mass, category (e.g., Communications, Surveillance and Meteorology, Navigation and Research), and launch date. The data used for this visualization spans from November 1974 to August 2020. 

Every Total Solar Eclipse Until 2080

After the August 2017 coast-to-coast solar eclipse, the Washington Post created an interactive globe visualization showing eclipse paths up to 2080. The spinning globe highlights areas of total eclipse. 

The visualization also provides information about the timing of these eclipses, using light and dark shades and interactive tooltips. A unique feature of this visualization is that it allows you to input your birth year, and the tool calculates the number of eclipses you can see in your lifetime. 

Top 5 Data Visualization Tools

Many data visualization tools are available in the market. By selecting the tool that fits your use case, you can simplify the process of turning raw data into compelling visuals. Here are the five most versatile data visualization tools for you to explore:

PowerBI

Power BI, a comprehensive business intelligence platform, empowers you to transform data into actionable insights. It offers a user-intuitive interface and integrates with data sources, including Salesforce, PostgreSQL, Oracle, Google Analytics, Github, Adobe Analytics, Azure, SQL Server, and Excel.

Key Features

• Customizable Visuals: Beyond the vast library of pre-built visualizations, Power BI offers a marketplace where you can discover and download custom visualizations created by the community. This flexibility enables you to tailor your visualizations to specific data types or industries.
• Natural Language Queries: Power BI supports natural language queries, enabling you to ask questions about your data in plain English. This allows even your non-technical teams to explore and analyze data without requiring extensive knowledge of data modeling or query languages.

Tableau

Tableau is a powerful data visualization tool with an extensive library of visualization types and an easy-to-use drag-and-drop interface. It offers desktop, server, and web-based versions to suit different needs and provides CRM software for managing customer relationships. You can directly connect Tableau to various sources, including databases, spreadsheets, and cloud applications.

Key Features

• Geo-Spatial Visualization: Tableau’s powerful mapping capabilities enable you to create interactive maps displaying data points on a geographic canvas. These maps help you identify trends, analyze spatial distribution, and discover valuable insights into spatial patterns and relationships.
• Live Dashboards: You can create interactive dashboards that update instantly as new data arrives, giving you access to the most recent information. Tableau also has extensions for integrating external tools or APIs for real-time processing and improving functionality.

Zoho Analytics

Zoho Analytics is a data visualization and business intelligence tool you can integrate with online reporting services to create and share extensive reports in minutes. It allows you to ingest data from over 250 sources, such as local files, web URLs, cloud drives, business applications, and custom applications.

Key Features

• Blended Data Visualizations: Zoho Analytics allows users to combine data from multiple sources and create blended visualizations, enabling cross-functional analysis and a holistic view of business performance.
• Dynamic and Interactive Exploration: You can view underlying data to explore specific details, use drill-downs for granular analysis, and apply contextual filters to focus on relevant data. These features enable you to perform ad-hoc data exploration.

Datawrapper

Datawrapper is a free, open-source data visualization platform. This GDPR-friendly tool allows you to create interactive charts or maps that can be embedded within your websites or reports. Its interface is beginner-friendly and has a drag-and-drop facility, enabling people with non-technical backgrounds to easily explore data.

Key Features

• Responsiveness and Accessibility: The visualizations created by Datawrapper are responsive and optimized for different devices. They meet the web accessibility standards and are compatible screen readers, accommodating people with color blindness and visual impairment. 
• Documentation and Support: Datawrapper offers comprehensive documentation and support to help you create effective visualizations. You can access step-by-step tutorials, guides, and a supportive community to learn and get assistance.

Qlik Sense

Qlik Sense is a business intelligence tool that leverages artificial intelligence to help you explore data effectively. It allows you to create interactive dashboards, visualizations and reports to gain broader context and deeper insights. Qlik Sense is available as a software-as-a-service (SaaS) or a hybrid service that extends SaaS analytics to your on-premises data.

Key Features

• Associative Model: Qlik Sense automatically connects data relationships across different datasets and offers a comprehensive view of insights. You can visualize all relevant associations by making interactive selections or using the smart search.
• Data Storytelling: This feature allows you to combine charts and narratives, making it easier to communicate data analytics results. It provides intelligent and in-context commentary that helps you convey data in a more understandable way.

Closing Thoughts 

Data visualization is a powerful technique that can completely change how you interact with and understand data. By representing data visually, you can discover hidden trends and patterns, communicate complex ideas, and make informed decisions. 

While numerous data visualization tools are available in the market, make sure you choose the right tools and techniques relevant to your specific needs. Data visualization enables you to get the most out of your data and helps you leverage the information gained to stay ahead of the curve.