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Why Is Data Visualization Important to Your Business?

Year after year, the amount of data created worldwide continues to grow. In fact, studies estimate that the world generates over 320 million terabytes of data each day. These estimates present an opportunity for your business to increase revenue and achieve long-term success. One way your organization can benefit from the large volumes of data available in the world is through data visualization. But why is data visualization important? And what are the different types of data visualization? More importantly, what is data visualization? Let’s dive in.

What Is Data Visualization?

To “visualize” something is to form a clear picture of it in your mind. As such, data visualization is the process of making data easier to understand and interpret just by looking at it. This technique leverages visual elements like charts, maps, and graphs to help both technical and non-technical audiences (such as those with no background in data analysis) better understand the data they’re reviewing. Data visualizations are generally more visually appealing than tabular data or text, in addition to being more easily digestible and generally self explanatory.

What Are Some Ways Of Visualizing Your Data?

When you think about data visualization techniques, you probably think of pie charts or graphs. While these are some of the most common types of data visualization, you would only be scratching the surface when it comes to data visualization techniques. 

Types of Data Visualization

Here’s a more comprehensive list of some common types of data visualization:

  • Bar charts: Ideal for comparing categories of data using rectangular bars.
  • Line charts: Display trends over time or relationships between continuous variables by connecting data points with lines.
  • Pie charts: Show parts of a whole, useful for illustrating percentages.
  • Histograms: Display the distribution of continuous data by dividing it into intervals or bins and representing frequencies with bars.
  • Heat maps: Represent data values with colors on a grid. They are particularly useful for visualizing patterns or concentrations in large datasets.
  • Tree maps: Visualize hierarchical data structures using nested rectangles. The size of each rectangle represents a quantitative value, while the hierarchy is shown by the nesting of rectangles within larger ones.
  • Network diagrams: Illustrate relationships between interconnected entities, such as nodes and edges. They are commonly used in social network analysis, systems biology, and other fields.
  • Word clouds: Visually represent text data by displaying words in varying sizes, with larger words indicating higher frequencies or importance within the dataset.
  • Box plots: Also known as box-and-whisker plots, box plots provide a visual summary of the distribution of a dataset, including measures of central tendency and variability, as well as identifying outliers.

Importance of Data Visualization

So, why is data visualization important? Because of the different roles it plays when adopted by a business. These roles include:

Enhancing Communication

Communication between data analysts and other business stakeholders is inevitable if your organization deals with data, be it customer data, sales figures, market trends, or any other type of information. However, more often than not, communication issues usually arise because of the lack of a “common language” between these two sets of stakeholders.

Data visualization acts as the middle ground between these two sets of stakeholders. Instead of presenting stakeholders with raw numbers or lengthy reports, data visualization tools offer intuitive and digestible insights, making it easier for non-technical audiences to grasp key findings. This way, technical and non-technical stakeholders can both have meaningful and productive discussions around data-driven insights.

Supporting Strategic Decision-Making

Data visualization helps reveal patterns, trends, and relationships that may have otherwise stayed hidden in large and complex datasets. These insights are important for making business decisions based on pricing strategies, market targeting, supply chain optimization, etc. For instance, if your business plans on expanding into new markets, data visualization can help identify untapped customer segments, assess market demand, and optimize pricing strategies to maximize profitability and competitiveness.

Driving Innovation

In a highly competitive business environment, innovation can be what sets your business apart. The insights you derive from data visualization can help reveal hidden opportunities for innovation and growth, such as identifying emerging market trends and customer preferences that inspire new product or service offerings. For instance, if you uncover a consistent preference for ethically sourced products after visualizing customer purchase patterns, you could innovate by sourcing materials from sustainable suppliers and launching a new line of eco-friendly products to meet this demand. This would position your business as a leader in sustainability and attract environmentally conscious consumers. 

Improving Data Literacy

Data literacy among all staff in your organization is essential to reaping the benefits of using data for business decisions. One way to enhance data literacy is by incorporating interactive data visualizations into employee training materials, presentations, and reports.

Data Visualization Best Practices

As with most processes, you must approach data visualization strategically to get the best possible outcomes. This might involve implementing the following data visualization best practices:

  • Understand your audience: Before creating visualizations, consider your target audience and their level of expertise with data. Then, tailor your visualizations to meet their needs and preferences, ensuring they are relevant to their interests.
  • Simplify and focus: Keep your visualizations simple and focused to avoid overwhelming your audience with unnecessary information. Eliminate clutter, unnecessary labels, and distractions to ensure your audience can quickly grasp the main message of the visualization.
  • Provide context: Always provide context for your visualizations to help your audience understand the significance of the data. Include titles, captions, and annotations to explain the purpose of the visualization, the data sources used, and any relevant insights or conclusions.

Leverage Data Visualization With SOLTECH

Data visualization is your gateway to making informed business decisions, driving innovation, and placing your organization at a competitive advantage. But to do so, you need a partner who understands why data visualization is important. At SOLTECH, we specialize in technology consulting, software development, and IT staffing. Whether you need help implementing data visualization software, need a better handle on data visualization best practices, or help with staffing data scientists, we can help. Contact us today


What are data visualization tools?

Data visualization tools are software applications that help represent data visually through charts, graphs, and other visual elements. They enable users to analyze and understand complex datasets more easily.

How do you choose the right data visualization techniques?

Choosing the right data visualization techniques involves considering the type of data you have, your audience, and the purpose of the visualization. Factors like data complexity, relationships, and patterns determine whether to use charts, graphs, maps, or other visual forms.


Joe White

Solution Architect

joe-whiteJoe White is a Solution Architect at SOLTECH, leveraging his extensive expertise in the software industry for over 15 years. With a solid background as a software engineer, architect, and software engineering manager, Joe has honed his skills by contributing to companies of all sizes, ranging from fledgling startups to large enterprises, across diverse industries. His passion for tackling data-related challenges has led him to excel in various domains, including big data processing and warehousing, machine learning and artificial intelligence.

Throughout his career, Joe’s commitment to providing tailored solutions for clients has been unwavering. His passion in developing custom software that is not only deployable but also scalable and maintainable, ensuring that customers’ unique problems are efficiently addressed.

With a degree in Computer Science from Kennesaw State University, Joe White consistently strives to improve the world through innovative and effective technological solutions. Based on his vast experience, he shares his insights and knowledge by writing on topics ranging from data management and analytics to software architecture and development best practices.

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