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Data Visualization: Benefits, Techniques, and Industry Examples

Discover the benefits of data visualization, top techniques, and real-world examples to improve data-driven decision-making and communication.

  • Overview
  • The Value of Data Visualization
  • Popular Data Visualization Techniques
  • Data Visualization at Work
  • Customers Using Snowflake for Analytics
  • Analytics Resources

Overview

Data visualization transforms complex datasets into graphical or pictorial narratives, making it easier to understand and interpret data. In this article, we’ll explore the core benefits of data visualization and popular data visualization techniques for communicating insights. We’ll also share four industry-specific examples that illustrate how data-driven storytelling is improving decision-making and communication across organizations.

The Value of Data Visualization

Data visualization capitalizes on the human mind’s ability to understand visual information. Presenting data in a visual format has several benefits for today’s teams.
 

More easily communicate complex data insights

Data visualization enables stakeholders to draw conclusions efficiently from data. Data visualization tools present complex data in compelling ways that encourage interactive exploration, allowing users to filter, sort and analyze information to answer important business questions.
 

Uncover hidden trends and patterns

Presenting data in a visual format helps users discover important trends and patterns within large and complex datasets that would otherwise remain hidden. Data visualizations such as scatter plots and network diagrams illustrate interconnections between data, helping decision-makers identify patterns and relationships within a dataset that aren’t readily apparent in their raw form.
 

Improve data accessibility

Data visualization democratizes data, delivering data-driven insights into the hands of those in the best position to leverage their value. Representing data in visual formats empowers those without data science experience to tap into the full potential of their data. Data visualization applications provide a menu of intuitive features such as filtering, drill-down capabilities, and interactive exploration. Users can quickly access and analyze the most relevant data, helping them ask their data the right questions and receive answers most relevant to their needs.
 

Enhanced collaboration and knowledge sharing

Data visualization opens up new opportunities for cross-team collaboration and knowledge transfer. Visual data spans language and cultural barriers, allowing global organizations to capitalize on the synergy that comes when individuals with diverse experience and knowledge work together to solve difficult business problems. In addition, interactive data visualization dashboards foster a culture of data-driven decision-making, making it easy for teams to analyze and interpret data jointly.
 

Advanced decision support

Data visualization reduces time to value, allowing key decision-makers to quickly comprehend and react to the patterns, trends and relationships uncovered during analysis. Interactive visualizations encourage users to ask questions, test hypotheses and develop a more comprehensive understanding of the story the data has to tell.

Popular Data Visualization Techniques

A variety of data visualization techniques help decision-makers make better use of complex data. Here are several options that teams can use to visualize data.
 

Heat maps

Heat maps appear similar to thermal imagery. But rather than highlighting where heat is concentrated, data visualization heat maps help identify high concentrations of behavioral activity. With a hot-to-cool color scheme, heat maps can be used for a variety of purposes, including understanding consumer behavior on a website.
 

Scatter plots

Scatter plots map data points between the x and y axes and are used to illustrate the relationship between two numerical variables visually. This data visualization method is frequently used to identify correlation, making it possible to analyze the relationships between two variables. Scatter plots are frequently used in visualizing financial data, such as the relationship between bond prices and interest rates.
 

Histograms

Histograms are used to plot frequency distribution, visually illustrating how often each value in a set occurs. In data analytics applications they’re useful for understanding patterns and characteristics of large datasets. Using this data visualization technique, supply chain managers can track variations in delivery times and inventory levels. 
 

Tables

Tables offer the classic spreadsheet view with data organized by header, rows and columns. Although organizing data in tabular form is ideal for some use cases such as illustrating monthly sales numbers, tables are difficult to scale and don’t provide the strong visual element of the other data visualization techniques discussed here.
 

Pie charts

As the name implies, pie charts display data in a circular chart, with each slice of data representing a percentage of the whole. Pie charts are useful for illustrating the relationships of parts to the whole. They’re often used to visualize data in a tabular format such as illustrating the percentage of total revenue for individual products.

Data Visualization at Work

Data visualizations are used across a wide variety of industries. As the importance of big data analytics grows, so too does the need to effectively communicate the patterns, trends and insights it reveals. 
 

Business intelligence

Business intelligence tools combine data analytics, data mining and data visualization capabilities to provide actionable information that improves decision-making. The interactive nature of many data visualization tools makes it possible to visualize data from multiple sources, creating dashboards and reports that visually illustrate more business metrics such as inventory levels, sales revenue and marketing campaign performance.
 

Manufacturing

Manufacturing is a data-rich industry. Data visualization helps make sense of the massive wave of data streaming in from machine-mounted sensors, production lines and suppliers. Data visualization tools display this data in easy-to-navigate dashboards and charts, providing the real-time insights needed to optimize production and manage suppliers. Data visualization techniques can be used to quickly identify bottlenecks, pinpoint the root cause of quality control issues and track progress towards production targets.
 

Healthcare

Data visualization plays an important role in healthcare at both the macro level and the individual patient level. At the macro level, data visualization techniques such as social network graphs help providers and public health officials better understand how disease outbreaks spread across communities, making it possible to spot trends and patterns that may otherwise go undetected. Data visualization is also used to monitor patient vital signs such as blood pressure, pulse and heart rate. Displaying this information in a visual format makes it easier for healthcare providers to make time-sensitive treatment decisions and evaluate their effectiveness.
 

Sports analytics

Sports teams and media organizations rely heavily on data visualizations to boost engagement, allowing them to connect with fans at a deeper level than stats displayed in table format can support. Weaving raw data into interactive infographics and animations can create engaging narratives that highlight the accomplishments and challenges faced by individual players and teams.