Best Data Visualization Tools in 2024

What is Data Visualization?

Data visualization in most basic terms is the accurate representation of data in any visual form such as charts, maps and graphs. Being a key part of data analysis process, the method relies upon images for showing the relationship between data. As more and more facts get represented through data visualization tools, the easier it is to identify patterns and trends within any data set.

Data visualization tools are used for gathering insights from multiple datasets. These insights rely on the visualization data structure method to help make simplified information available right at your doorstep instead of complex rows of indiscernible spreadsheets. Moreover communicating information from visualized data is far easy and quick.

What are Data Visualization Tools?

Suppose there is a large set of data right in front of you and you have to draw critical business or market insights from it. In order to accomplish this, you would have to present this dataset in multiple formats like maps, graphs, charts and images so that every information communicated is easy to digest.

Data visualization tools do the exact same job of automating these visualizations for multiple data points. You would thus see paid and open-source visualization tools being exclusively used for generating sales insights, marketing reports, dashboards, investor's slide decks and other kinds of reports.

Data may be large and complicated, but analytics visualization tools are easy to use. With exceptional mapping capabilities and multiple import options, even those with no prior analytics expertise can use these applications.

How do we evaluate and select the Best Data Visualization Tools?

Data visualization tools are a type of software used to visualize and analyze data. You will find different types of tools in the market to visualize your data, but which one is right for you? To help you with your decision, we have compared some of the most prominent software based on multiple metrics such as features, pricing, usability, etc.

While comparison them, we have taken into consideration some important features like data visualization, real-time analytics, graphs visualization, real-time collaboration, etc. While some data visualization tools provide these features for free, others offer them under their paid plan.

Additionally, we have also compared data visualization tools depending on their free trial, free and paid plans. You will find multiple products in the list that provide a free version for beginners.

How Do Data Visualization Tools Work? 

Data visualization tools act like translators, transforming raw data into compelling visual stories. Here's the gist of their magic:  

1. Data Ingestion: Data visualization software connects to various data sources like spreadsheets, databases, live feeds and imports all the data. 
2. Data Preparation: The tool cleans and organizes your data. It fills in missing values, formats it, and removes irrelevant information.  
3. Chart Creation: Next, it lets you choose the chart type (bar, line, heatmap, etc.) that best represents your data and customizes its appearance with colors, labels, and layouts. 
4. Interactive Exploration: Next, you can filter data, drill down for details, and hover over points to uncover deeper insights. 
5. Collaboration and Sharing: You can share your visualizations with colleagues, add them in reports, publish them online, etc.  
6. Security and Governance: The data viz tool protects your sensitive data with user authentication, data encryption, access controls, etc., ensuring information security and compliance.  

Best Data Visualization Tools Comparison 

Let's look at the top data visualization tools based on their pricing, key features, integration, industry served, etc.  

Top Data Visualization Tools Comparison
Softwares	Data Visualization Tools Key Features	Data Visualization Tools Prices
Looker	Advanced analytics & data exploration, Extensive customization, Security & governance	Pricing details are available on request.
Google Charts	Simple charts & graphs, Embeddable data , Interactive dashboard	Free to use
Infogram	Infographics & reports, Design-focused templates, Version history	Free plan available, paid plans start from INR 2,072.38/month
Excel	Basic data visualization, Spreadsheet integration, Formulas & functions	Free, included in Microsoft Office 365

Features You Should Look for in a Data Visualization Tool 

Data visualization tools come with various features designed to help users effectively analyze and present data. Here are some common features you will find in data visualization tools:

1. Range of Chart Types: Data visualization tools often offer several chart types (e.g., bar, line, scatter, pie, heatmap) to represent different types of data and relationships.
2. Interactivity: Such tools provide multiple interactive elements like tooltips, filters, drill-down, and zooming to explore and interact with data easily.
3. Customization: Users can customize various aspects of data visualizations like colors, fonts, labels, axes, and annotations to suit their preferences and branding guidelines.
4. Data Connectors: Database visualization tools allow users to connect to various data sources like databases, spreadsheets, and APIs to import and visualize data directly.
5. Data Transformation and Preparation: There are several visualization tools that support data cleansing, transformation, and aggregation to prepare raw data for visualization without any additional software.
6. Sharing and Collaboration: Users can share their visualizations with others through various means such as embedding in reports, exporting to different formats, or sharing links for online viewing. Collaboration features allow multiple users to work on visualizations simultaneously.
7. Dashboard Creation: Such tools often include dashboard builders for assembling multiple visualizations into a single, interactive dashboard for comprehensive data analysis and presentation.
8. Geospatial Visualization: For data with geographical components, data visualization tools may offer mapping capabilities to create interactive maps and spatial visualizations.

How to Choose the Right Data Visualization Tool?

Selecting the right data visualization tool involves considering factors like your data type, audience, required features, and your own proficiency. Here's a basic guide to choose the right data visualization software for you:  

1. Understand Your Data: Consider the type of data you have like numerical, categorical, spatial, etc., and what insights you want to extract from it.
2. Identify Your Audience: Know who will be viewing the visualizations and their preferences. Some tools are better suited for technical audiences, while others are more useful for non-technical users.
3. Evaluate Features: Look for tools that offer the features you need, such as interactivity, customization options, scalability, and compatibility with various data sources.
4. Ease of Use: Assess the tool's learning curve and how intuitive its interface is. You want something that your team can quickly adapt to.
5. Scalability and Performance: Ensure the tool can handle your data volume and complexity without significant performance issues.
6. Budget Considerations: Check the cost of the data visualization software and ensure it does not include any additional charges.

What are the Benefits of Data Visualization Software? 

Data visualization software can help represent your data in a simpler form and analyze the data trends. Similarly, it also helps in decision making by providing all the relevant data at your fingertips. Let's look at some other benefits of using this software:

Real-time data information

Data visualization tools simplify complex data into visual forms in real-time. All analyses and reports thus presented through visualization data structure processes present real-time scenarios for different metrics. Real-time data information helps analysts, leaders and managers make quick decisions based on the market situation and other competitive advantages.

Use case: Geographic map would be a good example here as it helps political parties generate data for visualizing voting patterns.

Simplified complex information

Big data visualization applications support complex data sets though single graphics and brief series. Fever charts and choropleth maps are some good examples of the same. With these simplifying mechanisms in place, the hassle of going through complicated chart types and static tables is greatly reduced.

Use case: In the healthcare industry, choropleth maps help determine key variables. For instance, checking the mortality rate from heart diseases across different regions.

Tracking connections

This is one of the prime uses of big data visualization software that end users can track connections between a business's performance and its overall operations. By using charts and graphs, it is easy to locate variances for spotting bottlenecks and improving the performance.

Use case: Scientists use data tools for getting insights from the available experimental data. This is critical for making scientific visualizations.

Identifying emerging market trends

Data visualizations are used to spot trends for performing well in a competitive environment. With support from paid or open-source data visualization tools, you can spot patterns for undertaking key marketing activities and making campaigning decisions accordingly. Even for making logistical decisions, the tools serve their function well.

Use case: For instance, a software company offering a 30-days free trial on signup can gauge its success with data presented in the visual form about conversions, not interested, registered for the trail but did not convert, etc. With support from paid or open-source visualization tools, you can spot patterns for undertaking key marketing and make campaign decisions accordingly.

Operational data

Data visualization tools help efficiently use operational data for understanding marketing indicators and checking performance in real-time. Heat maps are one good example where operational data is being used to assess data in multiple geographic locations.

Use case: Finance professionals use data visualization while buying or selling assets. This is critical for tracking how investment decisions perform over time.

Predictive & drill-down sales analytics

Analytics visualization or predictive analytics are being used to understand the lag in sales processes. Drill-down sales analytics are similarly used for finding a correlation between the underperformance of certain products and sales figures. Both methods are key procedures used for data visualization purposes.

Use case: Companies and organisations use predictive and drill-down analytics to understand the past sales record. This helps businesses predict how future sales would be in a period of time.

Consumer sentiment analysis

Those in the field rely on big data visualization tools for an accurate analysis of customer's sentiments. The entire mechanism of the data visualization system helps organizations delve into consumer's sentiments to see where their business would perform the best.

Use case: Sales & marketing teams use big data visualization tools for analyzing web traffic and planning their marketing efforts accordingly.

Who Should Use Data Visualization Tools?

Data viz tools are used in education to represent statistical information for making learning more engaging for students. Similarly, in healthcare, these tools are used to explain medical concepts to patients. Let's look at some more use cases of these tools below:  

1. Data analysts: Data analysts use tools to present data to their clients for better understanding of the products so that they can take data driven decisions.
2. Data scientists: Data scientists use data visualization tools to explore advancements in various fields.
3. Healthcare: Doctors can use visualizations to track patient trends, identify potential outbreaks, and explain complex medical concepts to patients. 
4. Education: Teachers can use visualizations to represent historical data, scientific discoveries, and statistical information, making learning more engaging for students. 
5. Finance: Financial analysts can use visualizations to track market trends, analyze investment performance, and communicate financial information to clients. 
6. Marketing: Marketers and advertisers can use data visualization to understand customer behavior, analyze campaign performance, and optimize marketing strategies based on data-driven insights. 
7. Government: Government can use track social and economic trends, analyze program effectiveness, and allocate resources efficiently based on data visualizations. 

Modules of Data Visualization Software 

Data visualization software comes with multiple modules to streamline the data visualization procedure which includes

1. Data connection module: You can connect and ingest data from spreadsheets, databases, or live feeds. 
2. Data Transformation module: In this data is scrubbed and transformed, ensuring its readiness for visualization. With multiple chart types, you can select and customize charts, from familiar bar graphs to heatmaps, effectively representing your data.
3. Collaboration module: You get an option to work with other members on data in real-time. Moreover, with its predictive analysis module, you can recognize patterns in your data to gain valuable insights. 

Implementation of Data Visualization Tools 

To implement visualization tools, you need to decide what you want to achieve with visualization. Next, you need to select the right data viz tool and train your employees to use the software. Here is the step-by-step breakdown of the process to implement this tool in your organization.

• Define Your Goals: Start by clearly identifying what you want to achieve with data visualization. What questions do you want to answer? This will guide your tool selection and implementation strategy.
• Choose the Right Tool: Evaluate various data visualization tools based on metrics such as ease of use, data connectivity, chart types, customization options, cost, etc. You should also consider the skill level of your team and the complexity of your data.
• Train Your Employees: Before starting to use the software, make sure to train your employees properly so that they can use the data viz tool effectively.
• Prepare Your Data: Ensure your data is clean, accurate, and in a format compatible with the selected software. This might include tasks like data cleaning, transformation, and formatting.
• Design Your Visualizations: Select the right chart types to visualize your data effectively.
• Deploy and Share: Lastly, publish your visualizations on dashboards, reports, or websites depending on your target audience. Leverage collaboration features for team projects and secure access controls for sensitive data.

How Much Does a Data Visualization Tool Cost?

The cost of a data visualization tool depends on the features it offers to its customers. On average, data visualization software costs around INR 497.46/user/month. Most of the tools are available on a subscription basis, annually or monthly. However, you will also find multiple software vendors who offer lifetime licenses to use data visualization tools. 

The cost will also include the features it provides. For instance, visualization tools with basic features will cost less compared to the ones that come with more advanced features. Additionally, the cost of software maintenance and customer support will also be added to the software cost. Hence, it is important to look at the complete breakdown of costs before selecting any of them. 

Mention Some of The Best Data Visualization Examples

Visualization of data isn't a straight forward process as it may seem like. You need tools that discern well data sets with multiple entries for doing data visualization.

1. Looker: The best part about Looker is the real-time dashboard support for analyzing data. The software further supports SQL dialects for easily connecting with multiple databases. Integrated insights and business analytic intelligence help companies make effective data-driven decisions. What makes the software unique is the existing data science workflows as well as multi-cloud support.

   Key features of Looker:

   1. Extensible modeling language, Integration with messaging platforms
   2. Aggregate tables
   3. IDE redesign
   4. Code-based modeling process

2. FusionCharts

   FusionCharts supports multiple maps and chart format options for effective data visualization. You can use this application for developing data dashboards that highlight visualizations of datasets side by side. You can take advantage of its cross-browser capabilities as well as responsive charts function.

   Key features of FusionCharts:

   1. Data plots for comparing data points values
   2. Charts labels and title for understanding the data
   3. Number formatting for displaying numbers
   4. Interactive legends for chart data
   5. Tooltips for context-specific data
   6. Trend lines for highlighting landmarks in a data
   7. Axis & gridlines
   8. Chart loading for displaying messages

3. Datawrapper

   The best part about using Datawrapper is even those with no prior programming knowledge can use it. Easily add interactive maps and charts once data import is complete. In this tool, you are free to use visualizations such as scatter plots, area charts, choropleths, bar charts, election donuts and symbol maps.

   Key features of Datawrapper:

   1. Live updating graphics
   2. Collaborative workflow and shared folders
   3. CMYK palette for embedding graphics
   4. Custom styling for maps, tables and charts
   5. Integration with content management systems

4. ChartBlocks

   Use live feeds built-in within ChartBlocks data visualization tool for easily importing data from any available source. Additionally available are extensions and automated modules for particular data sources. You can also use the specific feature called the chart building wizard for importing data.

   Key features of ChartBlocks:

   1. Easy to embed charts
   2. Pulling data from multiple sources is easy
   3. Integration with social media platforms
   4. Vector graphics for responsive charts
   5. Chart builder

5. Infogram

   You can prepare effective data visualizations for social media posts, marketing reports, maps, or infographics by using infogram. You can easily export easily interactive visualizations and embed these into the website of your choice. Also available are several maps and chart types for embedded visualizations. Inbuilt within these applications is a drag and drop editor to import additional sources of data.

   Key features of Infogram:

   1. Version history for restoring previous data
   2. Easy to set permissions by role level
   3. Viewer demographics along with average on-screen rates
   4. Custom tracking links
   5. Responsive infographics for online content publishing
   6. Infographics for visitor engagement
   7. Interactive reports for sales figures and marketing reports
   8. Slide templates and shareable dashboards
   9. Mapmaker