Importance of Data Visualization in Business Intelligence (BI)

As a business leader, you know that data has the potential to greatly impact–or even define–your future. Fortunately, many robust technologies and tools are available for storing and analyzing this data.

One of the most popular ways to store and analyze big data is with business intelligence (BI) software. Using a BI tool, your company can maximize the insights and the path to data-driven decisions based on your data. BI tools take your data and make it understandable. By ingesting, cleaning, and normalizing your data then allowing your team to visualize it, you can quickly gain insights into how different aspects of your business are performing and where you can take action based on your data. 

In this article, we’ll explore how BI tools can be used for business analytics. We will specifically focus on how data visualizations can maximize insights into your data.

What is data visualization in business intelligence

Data visualization is a way to transform raw data into insightful visuals. Doing this allows your team to get a more accessible and comprehensive understanding of complex information. While the raw numbers will hold important patterns and trends, it’s hard to see connections or uncover trends just looking at the numbers. 

As data scientists have discovered, it’s much easier to understand big data once it has been visualized. This concept is what drove the development of BI software, which allows you to turn raw data into meaningful charts and graphs that give actionable insights.

Using visualization tools like charts, graphs, and other elements helps your team see trends, patterns, and insights in a way that is easily understandable. This allows anyone on your team to more quickly understand and apply insights from your data, ensuring the right information is more accessible across your organization.

Why invest in visualization tools?

As you’re evaluating BI technology, make sure you’re keeping visualization at the top of your mind. While many tools are available to help gather and track raw data, knowing how you need to visualize and act on that data will help your team make a decision on how and why a business analytics tool could benefit your team. 

Not all visualization tools are created equal. Some are easy to use, while others can be downright confusing. If you’re looking to use simple pie charts and graphs for presentations, you might be fine just utilizing the tools in Excel or Google Sheets to visualize your data. But if your company is looking for data visualization in business analytics that pulls in information from a variety of tools and departments, combining and cleaning that data to ensure it’s accurate and usable, and then visualizing that combined data in ways that make sense for the information, you’ll need to consider more sophisticated tools. 

Some tools will allow you to combine data in really technical and advanced ways, creating beautiful graphics that can be interacted with. Others focus on more simple visualizations that are easy to create for even the most basic data users. Evaluate how your company needs to use your data, who will be creating visualizations, and how those visualizations will need to be utilized in your business as you consider the right visualization tool for your business and organizational needs. 

How can I extract business insights from visualizations?

Humans are naturally visual learners. Instead of overwhelming a user with tables containing thousands of rows of data, visualizations can be an easy vehicle for data insights. Visuals such as a bar chart or gauge graph (similar to the speedometer you see in your car) can be easily interpreted in seconds.

Visuals are also easy to interpret. With most business users being familiar with spreadsheet tools such as Excel, they will find it much easier to comprehend and consume visualizations created by BI tools.

When users want to extract even more insights, they can explore the data by drilling down into it. Starting at a high-level visualization that engages your audience is key. Once they understand the visual, they’ll start to ask questions that will prompt further insights and analysis into the data.

How can I use visualization in business?

If you want to get the most out of your customer data, it’s important to be able to visualize it. That way, you can quickly get a clear picture of customers’ behaviors and preferences.

In fact, visualization allows business leaders and other decision-makers across your organization to make more informed choices faster than ever before. By connecting business data to a BI platform, employees across the company can easily generate their own data visualizations and dashboards, thereby improving their individual department’s ability to act on data.

An important tip when getting started with data visualization in your business is to pick a department and identify some quick wins that can generate excitement. For example, your sales team might greatly benefit from visualizations that show their current sales pipeline and how certain prospects are progressing. Once that team has used their data visualization to improve their business processes, use those wins to get other teams excited about using data in their department.

Visualizations can have huge impacts on any department or job role. This includes everything from identifying revenue leaks that need plugging to pinpointing the best time and location for sales events. 

Types of data visualization in BI tools

Depending on your data and how you need to use it, different types of data visualization tools will work best. The good news is there is a vast supply of different types of visualizations that can help you get the most out of your data and provide different types of insights to interpret and analyze information. 

Here are some common/popular types of data visualizations frequently employed in BI tools:

• Bar Chart: Displays data using rectangular bars to represent values, making it easy to compare quantities across different categories.
• Pie Chart: Illustrates the proportion of each category in a dataset by dividing a circle into slices, making it useful for displaying parts of a whole.
• Line Graph: Connects data points with lines, demonstrating trends and patterns over a continuous interval, showcasing changes over time.
• Area Chart: Similar to a line graph but with the area beneath the line filled, effectively emphasizing the cumulative magnitude of values over time or across categories.
• Scatter Plot: Utilizes points on a two-dimensional plane to depict the relationship between two variables, highlighting correlations or outliers.
• Heat Map: Represents data values in a matrix using colors, providing an at-a-glance overview of patterns and variations across two dimensions.
• Maps: Displays information based on regional or geographical data. Often shows data relationships over a specific geographic region. 
• Donut Chart: Displays information as a circle divided into sections, each of which represents a percentage of the overall chart. This chart type is almost identical to a pie chart; the only difference is that there is a hole in the center, so the sections appear as arcs rather than wedges.
• Gauge: Shows the degree of change between a previous value and a current value. This is typically a number or percentage, sometimes accompanied by colors or arrows indicating whether a change was positive or negative. 
• Bubble Chart: Enhances a scatter plot by adding a third dimension with varying sizes of bubbles, enabling the representation of three variables simultaneously.
• Histogram: Displays the distribution of a dataset by grouping data into intervals, making it valuable for understanding the frequency of occurrences within a range.
• Gantt Chart: Depicts project schedules or timelines by representing tasks or events along a horizontal bar, showcasing their start and end dates.

There are many more ways to visualize and display your data. If you’re interested, check out Domo’s list of chart types. 

Categories of Data Visualizations

Data visualizations are broadly categorized into distinct types based on their intended purpose and the nature of the information they convey. You can use these categories to help choose what type of visualization best suits your data and the information you need to gather from your data. 

• Comparison Visualizations: This includes visualizations like bar charts and line graphs. It helps you compare data against each other. The data you’re comparing can be sales across products, website visits across days, or production across warehouses. 
• Composition Visualizations: These visualizations typically show users how many parts make up a whole. You can use these visualizations to compare data against each other and see how many sales are for a specific product, track inventory availability across locations, or show the distribution of financial assets in a portfolio. 
• Time-Series Visualizations: These visualizations can include things like line graphs, Gantt charts, or calendar heatmaps. It helps you see the relationship between time and your critical data points. 
• Geospatial Visualizations: These visualizations are things like maps or bubble charts. You can use these visualizations to quickly understand how different regions compare to each other. For example, you can track store sales in a region or where website visitors are coming from. 

Examples of real-world visualization use cases

Data visualizations can have wide applications across a variety of industries. Organizations leverage data visualization to enhance decision-making processes, streamline operations, and unearth valuable patterns within their data. Let’s dive into the applications of data visualization across various industries, looking at how visualizations can help with informed decision-making and ensuring organizations have a deep understanding of critical trends and metrics.

Retail businesses

More retail companies are using data storytelling techniques like narratives and storytelling using dashboards customized for specific audiences (e.g., executives or store managers), use cases (e.g., equipment maintenance), and goals (e.g., growing revenue).

Online businesses

Visualization is becoming increasingly popular on eCommerce websites because it provides an engaging way for shoppers to interact with products, giving them the opportunity to explore items in more detail before making a purchase.

Customer service

Gathering data about customer sentiment and other trends can give your company’s support teams real-time information about issues affecting customers, helping them avoid costly problems by proactively offering assistance.

Healthcare organizations

The healthcare industry benefits greatly from visualization technology because it allows medical professionals across different specialties to access critical patient data quickly.
This helps doctors make accurate diagnoses and speeds up treatment times, resulting in better patient outcomes.

Transportation and logistics

With big data analytics, transportation & logistics companies are able to make smarter decisions related to demand management, supply chain optimization, network design, and more.

Just think of how it can help airlines decide where they should place flights or trucking companies decide the best time to schedule deliveries

How do I get started with a BI tool?

BI tools are extremely easy to use because they are built with the business users in mind. Where traditional software relies on technical teams such as IT and engineering, BI and data visualizations are meant for business professionals in departments such as sales, finance, and marketing.

It’s very easy to get started with data visualization. Once your data has been imported into the BI tool, it will help you visualize it using prebuilt visualizations such as a bar or line chart. These tools are incredibly intuitive and require minimal training.

Once you have incorporated visualizations into your everyday work, your employees will start to understand the value a BI tool can bring. You can start doing visualization and analytics in one department. As the company starts to see its success, other departments will soon want to follow.

Conclusion

There are many different types of visualization tools available, but deciding which one is right for your organization can be challenging unless you know what makes them tick.

In order to take full advantage of visualization data, it’s important to look beyond the surface and evaluate key factors such as cost, the time needed for implementation, and scalability.

The good news is there are plenty of resources available, including case studies from companies that have used visualization tools to improve their decision-making. This will help you make a more informed choice based on your specific goals and budget.