The Importance of Data Visualization Tools for Business

Heat Map Data Visualization

When you think “business success” key performance indicators might come to mind long before you consider the importance of data visualization tools. Yet, the more complicated and large a data set gets, the more we need smart software that can extract and visualize insights clearly and easily.

Data visualization tools achieve precisely that. By visualizing big data and transforming raw data into visually engaging and intuitive representations, data visualization empowers business leaders, managers, and data analysts to unlock the true potential of their data points.

In this comprehensive guide, we will delve into the role of data visualization in business decision-making. Whether you’re a seasoned data science professional or new to the world of data analysis, this resource will equip you with the knowledge and tools to harness the power of data visualization to make better, more informed decisions.

So, let’s embark on this journey together and unlock the power of big data and visualization!

Benefits of Data Visualization in Business Decision-Making

So why is data visualization important?

  1. Ability to enhance understanding of complex data. By transforming raw data into visual representations such as charts, graphs, and interactive dashboards, data visualization allows decision-makers to more quickly identify patterns, trends, and correlations.
  2. More accurate and informed decisions. And chances are, faster as well. Since the information is presented in a concise and intuitive format, decision-makers can use data visualization tools to quickly identify key insights and make timely choices.
  3. Effective communication of data insights. Visual representations are often more compelling and memorable than raw numbers in endless spreadsheets, making it easier to share findings with stakeholders, align teams, and drive action.

As you can see, the importance of data visualization boils down to empowering businesses to unlock the true potential of their data, resulting in improved decision-making processes and ultimately, better business outcomes.

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How Data Visualization Enhances Decision-Making

At its core, decision-making is the process of choosing between two or more options. Of course, there are many variables that can go into even the simplest decision–for example, if you’re trying to decide what to have for lunch you might be considering your budget, the proximity of various restaurants, any dietary restrictions, whether you’ll be going alone or with colleagues, if the options you are considering will hit your macros… or if you should just have that protein bar in your desk drawer and call it a day.

Once you escalate that same thinking process to decisions that deal with big data and can influence the trajectory and success of your team or business, it becomes even more complex. Plus, often enough, even when you’ve gathered all the necessary information and evaluated the alternatives, you might still be left without a clear-cut answer.

In that scenario, business analytics done through data visualization tools really are the superheroes of the data story. They play a crucial role in enhancing decision-making by providing a clear and concise representation of complex data.

  • In sales analysis, visualizing sales data through charts and graphs allows decision-makers to identify top-performing products, regions, or customer segments at a glance, enabling them to allocate resources and optimize strategies accordingly.
  • In financial analysis, visualizing revenue, expenses, and profitability over time helps executives identify cost-saving opportunities and make informed budgetary decisions.
  • In supply chain management, data visualization of inventory levels and demand patterns enables organizations to identify bottlenecks, optimize logistics, and improve overall efficiency.

In each one of those scenarios, data visualizations can help decision-makers to see what may have otherwise gone unnoticed in databases and spreadsheets, leading to more accurate insights and more effective decision-making.

Types of Data Visualization Tools

There is a wide array of data visualization tools available, and, as ever, the choice will likely depend on what you are trying to accomplish, or what issues you have that require data visualization methods or tools to resolve.


This data visualization tool allows business users to graphically represent sales, business, and geographic data by mapping locations, sales territories, or demographics. It is particularly useful for businesses that need to analyze data with a spatial component, such as customer distribution, sales territories, or market penetration.

Compared to other data visualization tools, Maptive stands out from the crowd because of its ease of use (no coding required), and incredible number of options to customize each element of your data visualizations. With so many stellar user testimonials, the proof, as they say, it’s in the pudding:

  • As our data visualization partners, Maptive has become an integral part of our operations—from Logistics to Project Tracking to Scheduling.
    • Miquel Fernandez, RMSI Retail Solutions
  • True insight into our data is vital to our success—and Maptive gives us exactly that.
    • Anjil, BRAC
  • I can finally visualize my business geographically! Maptive allows me to make sense of my data and visualize it in different ways. The platform has a variety of tools and it is easy to use.
    • Andrew B, G2 Crowd User Review

Data Visualization

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Charting & Graphing Tools

These include data visualization tools like Tableau, Power BI, and Google Data Studio. They offer a variety of chart types, such as bar charts, line graphs, scatter plots, and more.

They are a graphical format ideal for visualizing numerical data and trends, comparing different variables, and creating interactive dashboards.

File:Tableau Logo.png - Wikimedia Commons

Which Chart or Graph is Right for You? A guide to data visualization

Tableau Charts – Source: Tableau

Specialized Needs

Data visualization tools like D3.js and Plotly provide advanced customization options and support for creating interactive and dynamic graphics using JavaScript libraries. They require coding knowledge, so these tools are more suitable for data scientists, developers presenting data, and business analytics professionals who require highly customized and interactive data visualizations.

The right choice of data visualization tool depends on the specific requirements and data set being analyzed, as well as who needs to identify patterns. If the data has a geographical component, Maptive would be the most suitable choice. It is important to evaluate the features, ease of use, and compatibility of the data visualization tool of your choice with your data sources.

How To Create a Plotly Visualization And Embed It On Websites | by Elizabeth Ter Sahakyan | Towards Data Science

Plotly Visualizations – Source: Towards Data Science

How to Use Data Visualization for Business Decision-Making

Now that you understand the importance of data visualization, you also need to know how to use it to improve how you make your business decisions.

  • Step 1: Define your objective. What is the purpose of your analysis? What specific decision do you need to make? This will help guide your data visualization process.
  • Step 2: Choose the right data visualization. Select a type of data visualization that represents your data clearly and supports your objective. To figure that out, you might want to consider the type of data you have (numerical, categorical, temporal), the relationships you want to explore, and the key insights you want to communicate. Bar charts, line graphs, scatter plots, and heat maps are just a few examples of data visualization techniques to consider.
  • Step 3: Prepare and clean your data. This step may or may not be necessary depending on how your source and store your business data. For data analysis to be successful, you need to ensure that your data is accurate, complete, and well-structured.
  • Step 4: Create your data visualizations. Use data visualization tools or software to create your map, chart, or graph. You can also have some fun customizing your data visualization to effectively highlight the key insights and patterns you want to convey. Pay attention to labeling, color choices, and layout to ensure you are able to create data stories.
  • Step 5: Interpret the visualizations. This is where the magic happens. Take a step back and carefully analyze your data visualizations to extract meaningful insights. Identify trends, look for patterns, outliers, and correlations within the data. Consider the context and any relevant business factors that may influence the interpretation of your valuable insights.
  • Step 6: Make informed decisions. All your work can finally pay off. Use the insights gained from your data visualizations to inform your decision-making process. Consider the implications of the findings from the graphical representations you’ve created, weigh the risks and benefits, and identify potential actions or strategies based on your effective data visualization.
  • Step 7: Communicate and share your findings. Nobody exists in a vacuum, and chances are your team will benefit if you communicate data findings. Present your data visualizations and insights in a clear and concise manner to relevant stakeholders. Use storytelling techniques to effectively communicate the significance of the data points, pie chart, line chart, or other common data visualization you’ve chosen and its impact on the decision-making process.

Remember, data visualization is a tool to help you make better decisions, but it is pointless without everything you bring to the table, including your critical thinking, domain knowledge, and an understanding of data storytelling in the business context.


We hope that this comprehensive guide has made the importance of data visualization abundantly clear.

Data visualization is a critical skill for business leaders, managers, and data analysts. By embracing the power of data visualization–be it charts, graphs, maps, or dashboards– businesses can unlock the true potential of their data and gain a competitive edge in making informed and impactful decisions. So, embrace data visualization, explore its possibilities, and harness its transformative power to shape the future of your business.

As our world becomes more and more driven by complex data, being able to visualize that information and make decisions based on those insights will give you a unique competitive edge and keep you ahead of the curve.


Q1: What is data visualization?

Data visualization is the process of transforming data into visual representations, such as charts, graphs, and maps. This makes it easier to understand, analyze, and communicate insights from data.

Q2: How can data visualization help with business decision-making?

The importance of data visualization boils down to helping businesses make better decisions by:

  • Identifying patterns and trends
  • Facilitating faster decision making
  • Improving communication of data insights
  • Empowering organizations to make data-driven decisions

Q3: What are some examples of data visualization in business decision-making?

  • Line graphs to track sales performance over time
  • Pie charts to display market share percentages
  • Heatmaps to visualize customer preferences or website traffic patterns
  • Geographic maps to analyze sales territories or target markets

Q4: What are the best practices for using data visualization in business decision-making?

  • Identify clear objectives for visualization
  • Choose the appropriate visualization type
  • Ensure data accuracy and cleanliness
  • Maintain simplicity and clarity in visual design while providing proper context and labeling
  • Consider the target audience for the visualizations

Q5: How do I choose the right data visualization tool for my business?

When selecting a data visualization tool for your business, consider factors such as: cost, the type of data you work with, the complexity of visualizations required, its ease of use & compatibility with your data sources, and the customization options it offers.

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