In today's data-driven business landscape, companies generate vast amounts of data that need to be analyzed to gain insights into their operations, customers, and competitors. With so much data available, it can be challenging to make sense of it all and extract useful information.
That's where business data visualization comes in - it provides a powerful tool for turning complex data into actionable insights. According to a survey by Dresner Advisory Services, data visualization is considered the most important business intelligence tool, with 98% of respondents saying it was important or very important to their organization.
The use of data visualization in business is crucial in modern business reporting, and companies that incorporate it in their operations are better positioned to make data-driven decisions and gain a competitive edge. Hence, in this article, we’ll get a better understanding on what is data visualization and the role it plays in business reporting.
What is Data Visualization?
Data visualization is representing data and information in visual forms, such as graphs, charts, and maps, to help people understand and analyze complex data. It allows large amounts of data to be presented concisely and easily understandable.
Business data visualization is essential for businesses to gain insights and make informed decisions based on data-driven insights. It helps identify patterns, trends, and outliers that may need to be apparent in raw data.
With the help of data visualization tools, organizations can explore data from different perspectives, compare data sets, and identify relationships between variables. It also aids in communicating insights to stakeholders and presenting data in an engaging and informative way.
Some Common Types of Data Visualization
Here are some of the most common types of data visualization:
- Bar charts
- Waterfall charts
- Scatter plots
- Pie charts
- Heat maps
- Gantt charts
- Histograms
- Box-and-whisker plots
- Maps
- Infographics
Importance of Data Visualization in Business
So, shy is data visualization important? Data visualization plays a crucial role in business, enabling decision-makers to understand and interpret complex data easily. It helps businesses to identify patterns, trends, and relationships within their data, allowing them to make data-driven decisions quickly.
Data visualization also provides an efficient way to communicate insights to stakeholders, making conveying the importance of certain data points easier.
Moreover, data visualization helps businesses to gain a competitive edge by enabling them to identify areas of improvement and opportunities for growth. It also enables organizations to track their progress toward achieving their goals and objectives.
By visualizing data, businesses can quickly identify what is working well and what needs to be changed, leading to more effective decision-making. Additionally, data visualization provides a way for businesses to present their data to customers and clients, making it easier to communicate complex information simply and engagingly.
Benefits of Data Visualization for Business
Mentioned below are some of the most prominent benefits of data visualization:
Instant absorption of large and complex data
Data visualization allows businesses to present large and complex datasets visually, making it easier for people to understand and absorb the information quickly. With data visualization in business, companies can condense large volumes of data into a single image or chart, highlighting the most critical points and trends.
This instant absorption of information can save valuable time and resources, enabling decision-makers to act quickly on insights.
Better decision-making based on data
Data visualization helps businesses make better decisions based on data-driven insights. With business intelligence visualizations, decision-makers can quickly identify trends, patterns, and outliers that might not be immediately apparent in raw data.
This enables them to make informed decisions quickly, leading to more effective strategies, increased efficiency, and improved profitability.
Audience Engagement
BI data visualization tools can engage viewers by presenting complex information visually appealing and engagingly. By using charts, graphs, and other visual aids, businesses can communicate insights to stakeholders in an easy-to-understand and interpretable way.
This engagement can lead to increased interest in the data, improved comprehension, and a better understanding of the presented information.
Reveals hidden patterns and deeper insights
Data visualization can reveal hidden patterns and insights that might not be immediately apparent in raw data. By visualizing data in different ways, businesses can identify correlations, trends, and outliers, leading to a deeper understanding of the data.
This can lead to new insights, strategies, and opportunities for growth and improvement. Additionally, data visualization enables businesses to identify potential problems before they become significant issues, enabling them to act proactively rather than reactively.
Data Visualization Best Practices for Business Reporting
Define your audience
It is essential to define your audience before creating any data visualization. This ensures that you create charts, graphs, and other appropriate visualizations for your intended audience.
Understanding the audience will help you choose the right data business intelligence visualization type, layout, and design to effectively convey your message.
Keep colors and fonts consistent
Consistency is key when it comes to data visualization. Using a consistent color scheme and font helps create cohesion and makes it easier for the audience to follow the information presented. It is essential to use colors and fonts that are easy on the eyes and do not clash with each other.
Context is key
Context is critical when presenting data visualizations. Providing context helps the audience to understand the data and the story that it tells. It is essential to provide labels, headings, and annotations to help guide the audience and make the information presented more meaningful.
Use formatting and sorting
Formatting and sorting are important when presenting data visualizations. Proper formatting helps highlight important information and make the data easier to understand. Sorting can reveal trends and patterns in the data that might not be immediately apparent.
Know when to hero tables
Sometimes, tables can be the most effective way to present data. Knowing when to use tables and how to format them is essential to make them easy to read and understand. It is crucial to keep the formatting consistent and use appropriate headings and labels when using tables.
Present values accurately
It is important to present values accurately when creating data visualizations. Misrepresenting data can lead to clarity and trust. It is essential to ensure that values are accurately represented and that the data is presented in a way that is easy to understand. This can include using appropriate scales, labels, and axes.
Top categories of data visualizations
- Bar charts: Used to show comparisons between different categories of data.
- Line graphs: Used to show trends and changes over time.
- Pie charts: Used to show the composition of different categories of data as parts of a whole.
- Scatter plots: Used to show the relationship between two sets of data.
- Heat maps: Used to show the density or concentration of data within a given area.
- Geographic maps: Used to show data on a map, typically showing variations in data across geographic regions.
- Tree maps: Used to show hierarchical data as nested rectangles.
- Bubble charts: Used to show three dimensions of data: the x-axis, y-axis, and size of the bubble.
- Histograms: Used to show the distribution of data within a range of values.
- Box and whisker plots: Used to show the distribution of data and identify outliers and variability within a dataset.
Some Data Visualization Tools You Should Be Aware Of
There are many data visualization tools available in the market, and we’ve provided basic information about the top tools:
Arena Calibrate
Arena Calibrate is a data visualization tool that allows users to create interactive and customizable visualizations of their data.
Pros
- User-friendly interface
- Powerful features for data analysis
- The ability to collaborate with others on visualizations
Cons
- Limited options for customization
Pricing
Arena Calibrate offers a range of pricing plans based on the number of users, the number of models being calibrated, and the level of support required. Interested users can contact Arena directly to discuss their specific needs and receive a customized quote.
Additionally, Arena Calibrate offers a free trial period for new users to test out the tool and determine which plan works best for their organization.
Tableau
Tableau is a powerful data visualization tool that has become popular for businesses and individuals looking to create interactive dashboards and reports. Here are some of the pros and cons of using Tableau:
Pros:
- User-friendly interface and drag-and-drop design
- Ability to handle large datasets and connect to various data sources
- Wide range of visualization options and customization features
- Ability to create interactive dashboards and reports
- Strong community support and resources for learning
Cons:
- High pricing compared to other data visualization tools
- The steep learning curve for advanced features and functionalities
- Limited collaboration capabilities in the lower-priced versions
- Difficulty in creating complex calculations or data transformations
Pricing:
Tableau offers a variety of pricing plans, depending on the features and capabilities needed. The pricing ranges from $12 per user per month for the Tableau Creator option to $70 per user per month for the Tableau Server option.
There are also additional costs for add-ons and upgrades. While the pricing may be a drawback for some users, the range of features and capabilities offered by Tableau may justify the cost for larger businesses or those with complex data needs.
Dundas BI
Dundas BI is a business intelligence and data visualization tool that provides interactive dashboards, reporting, and analytics.
Pros:
- Highly customizable with a drag-and-drop interface
- Good for complex data and analytics with a variety of data connectors and advanced features
- Responsive and mobile-friendly design
Cons:
- A steep learning curve for beginners
- Limited community support and resources compared to other tools
- Higher pricing compared to some other tools
Pricing:
Dundas BI offers a free trial, with pricing starting at $9,999 per year for a single user.
Zoho Reports
Zoho Reports is a cloud-based business intelligence and data analytics tool that provides a range of features, including data visualization, collaboration, and reporting.
Pros:
- Easy to use with a simple and intuitive interface
- Affordable pricing with a range of plans to suit different business sizes and needs
- Offers a variety of data connectors and integrations with other Zoho products
Cons:
- Limited advanced analytics features compared to other tools
- Limited customization options for dashboards and reports
- May experience slower performance with larger datasets
Pricing:
Zoho Reports offers a free trial, with pricing starting at $22 per month for two users and 50,000 rows of data. Higher-tier plans with more advanced features and larger data limits are available at higher price points.
Google Charts
Google Charts is a free and open-source data visualization tool that allows users to create interactive charts and graphs for web applications.
Pros:
- Free and easy to use, with a simple API for developers to integrate charts into web applications
- Wide range of chart types and customization options are available
- It can be integrated with other Google products, such as Sheets and Analytics
Cons:
- Limited customization options compared to other tools
- Limited support for advanced analytics features
- It may not be suitable for larger datasets
Pricing:
Google Charts is a free tool with no pricing tiers or subscription plans. However, additional fees may apply for usage of other Google services such as Google Sheets or Google Analytics.
Visually
Visually is a cloud-based data visualization and infographics platform that helps businesses create engaging visual content. One of its main strengths is its library of customizable templates that allow users to create high-quality infographics quickly and easily.
Pros:
- User-friendly interface
- Large selection of templates
- Collaborative features
- Option to hire a designer for custom work
Cons:
- Limited flexibility in design
- It can be expensive for custom work
Pricing:
Custom pricing based on the scope of the project.
RAW
RAW is a free and open-source web application for creating custom visualizations from data sets. It allows users to import data from various sources and create visualizations using a variety of chart types and customization options.
Pros:
- Free and open-source
- User-friendly interface
- Variety of customization options
- Ability to export visualizations as code for use in other applications
Cons:
- Limited functionality compared to more advanced tools
- Limited support and community resources
Pricing:
Free to use.
IBM Watson
IBM Watson is a cloud-based data visualization and business intelligence tool that offers advanced analytics and natural language processing capabilities.
Pros:
- It provides a wide range of analytical capabilities, including predictive analytics and machine learning, which can help businesses gain deeper insights into their data.
- It has a user-friendly interface and allows for easy integration with other IBM products and services.
- It supports a variety of data sources and can handle large amounts of data.
Cons:
- It can be quite expensive for small and medium-sized businesses and may only be worth the investment if the data needs are extensive.
- Some users have reported a steep learning curve when it comes to using the tool's more advanced features.
Pricing:
IBM Watson offers a range of pricing plans, with costs varying based on the specific features and capabilities needed. A free trial is available for those who want to test the tool's capabilities before committing to a subscription.
Sisense
Sisense is a business intelligence and analytics tool that allows users to prepare, analyze, and visualize complex data sets.
Pros:
- Sisense has a user-friendly interface and provides a variety of customization options for creating dashboards and reports.
- The platform allows for easy integration with a wide range of data sources, including cloud-based and on-premise databases.
- Sisense has a high-performance In-Chip technology that enables users to handle large volumes of data quickly and efficiently.
Cons:
- While Sisense offers a lot of flexibility, it may take some time for users to learn how to use the more advanced features of the platform.
- The pricing of Sisense can be relatively expensive compared to other BI tools in the market.
Pricing:
Sisense offers customized pricing plans based on the needs of individual businesses. The pricing is not publicly available, and interested users must contact the sales team to get a quote.
Plotly
Plotly is a web-based data visualization tool that allows users to create interactive charts, graphs, and dashboards. It offers a variety of chart types, including scatter plots, bar charts, line charts, and more.
Pros:
- Interactive and high-quality visualizations with animations and hover effects
- Offers both online and offline versions, which makes it more flexible
- Supports a variety of programming languages such as Python, R, and MATLAB
Cons:
- A steep learning curve, especially for beginners
- Limited customization options for free users
- Some features require a paid subscription
Pricing:
The pricing for Plotly ranges from a free basic plan to a paid professional plan starting at $49 per user per month. There are also custom enterprise plans available for larger organizations.
Conclusion
Data visualization is an essential aspect of business reporting. It enables businesses to understand complex data sets and make informed decisions quickly. By using appropriate visualization tools and techniques, businesses can present data in a way that is easy to understand and engage the audience.
Our product aims to simplify data visualization for businesses by providing a user-friendly interface and various visualization options. With our product, businesses can easily create interactive and engaging visualizations that enable them to extract insights and communicate effectively with stakeholders.
FAQs on Data Visualization for Business
What should I look for in a data visualization tool?
There are several key factors to consider when looking for a data visualization tool. Here are some important things to look for:
- Ease of use: The tool should be intuitive and easy to use, with a user-friendly interface that allows you to create and modify visualizations quickly.
- Customizability: The tool should allow you to customize your visualizations to meet your specific needs, with options to change colors, fonts, and other elements.
- Compatibility: The tool should be compatible with the data sources and file formats you use and should be able to handle large data sets without slowing down.
- Interactivity: The tool should allow you to create interactive visualizations that allow users to explore the data and gain deeper insights.
- Sharing and collaboration: The tool should make sharing your visualizations with others easy, either through exportable files or by embedding them in web pages or other documents. It should also allow team members to collaborate, with features such as commenting and version control.
- Cost: Consider the cost of the tool, including any subscription or licensing fees, and whether the features it offers are worth the investment.
Considering these factors, you can find a data visualization tool that meets your needs and helps you communicate your data effectively.
How do you visualize business data?
Visualizing business data involves converting raw data into graphical or pictorial representations such as charts, graphs, diagrams, maps, and infographics. Here are the general steps to visualize business data:
- Collect and organize the data: Gather data from various sources, clean and organize it into a suitable format for analysis.
- Determine the objective: Define the purpose of the visualization and the questions it should answer.
- Choose the right visualization type: Select the appropriate data visualization type based on the objective and the data structure.
- Create the visualizations: Use a data visualization tool to create the charts, graphs, and other visuals that best represent the data.
- Analyze and interpret the data: Examine the visualizations and draw insights from them. The data should be analyzed for patterns, trends, correlations, and outliers.
- Communicate the results: Share the visualizations with stakeholders through presentations, dashboards, reports, or other communication channels.
- Iterate and refine: Continuously evaluate and refine the data visualizations to improve their clarity, accuracy, and relevance to the target audience.
What is the difference between business analytics and data visualization?
Business analytics and data visualization are two different but complementary aspects of data analysis.
Business analytics involves using statistical and quantitative methods to extract insights from data and make data-driven decisions that help organizations achieve their goals. It involves tasks such as data mining, data cleaning, data modeling, and data analysis.
Data visualization, on the other hand, is the process of presenting data in a visual format, such as charts, graphs, and diagrams, to help users understand the patterns and insights in the data. The goal of data visualization is to make complex data more accessible, understandable, and actionable for decision-makers.
In summary, while business analytics is concerned with the quantitative analysis of data, data visualization is concerned with the visual representation of data to make it more accessible and easier to understand. Both are essential components of data analysis and decision-making in modern businesses.
What are the 3 main goals of data visualization?
The three main goals of data visualization are:
- To communicate information effectively: The primary goal of data visualization is to present data in a clear and concise manner so that the audience can easily understand the information being conveyed.
- To identify patterns and relationships: Data visualization allows us to identify patterns and relationships that may not be immediately apparent in the raw data. By presenting data visually, we can more easily spot trends and outliers.
- To support decision-making: Data visualization can aid in decision-making by providing insights and highlighting key trends and patterns. Data visualization can help users make informed decisions based on data-driven insights when presented effectively.
What is the most important rule for data visualization?
The most important rule for data visualization is to keep it simple and clear. Data visualization aims to communicate complex information simply and understandably, so it is essential to avoid clutter and unnecessary details that can confuse or mislead the audience.
Good data visualization should be easy to read and interpret, with clear labels, appropriate use of colors and fonts, and a logical layout that guides the viewer's eye to the most important information.
How is data visualization used in business?
Data visualization is used in business for various purposes, such as:
- Identifying trends and patterns: Visualization tools can help businesses to identify trends, patterns, and outliers in large data sets. This can help in making informed decisions and strategies.
- Communicating insights: Visualization can help businesses to communicate insights and findings in a clear and easy-to-understand manner. This is important in decision-making processes and in presenting information to stakeholders.
- Tracking performance: Visualization tools can help businesses to track performance metrics and key performance indicators (KPIs) in real time. This can help in identifying areas for improvement and making data-driven decisions.
- Forecasting: Visualization tools can be used to create forecasts and predict future outcomes based on historical data.
Data visualization is a powerful tool for businesses to gain insights from their data, communicate findings effectively, and make informed decisions.
