20 Best Data Visualization Tools To Consider in 2025

Many businesses have begun capitalizing on the gigantic quantities of data they are collecting. But this can only be possible with the use of moden data visualization tools. Such tools give non-tech users within a company a complete understanding of the data and its insights.

Fortune Business Insights values the data visualization global market at USD 8.85 billion in 2019. This value is estimated to soar to USD 19.20 billion by the year 2027 at a CAGR of 10.2%. Growing internet use, advancements in Machine Learning, more cloud computing technologies and many other factors drives this market growth.

Let's understand the top data visualization tools that will shine in 2025.

What are Data Visualization Tools?

Tableau, QlikView, Power BI, Zoho Analytics, and Looker are some of the best Data visualization tools companies are using to visualize their data. These tools are different forms of software for visualizing data. Each tool's features and capabilities vary. At the basic level, however, they input a dataset to visually manipulate it. Many of them also come with built-in templates for generating basic visualizations.

20 Top Data Visualization Tools

There are endless data visualization tools out there. Data usage is changing from all sides and that calls for the need to have amazing tools by one's side. Each tool brings its own set of features and benefits to help the company using it. Here are the best data visualization tools to know about and learn in 2025.

1. Tableau

Tableau is amongst the most powerful and popular tools for visualizing data. There are two main reasons for this claim. One is that it is easy to use and second is that it is super powerful. It can be connected to different data sources for creating all sorts of maps and charts. Many big companies globally use Tableau, which Salesforce owns.

This tool has different versions - desktop, web-based and server. It also has some customer relationship management (CRM) software. Tableau efficiently creates visualizations from gigantic datasets that are constantly evolving. Artificial intelligence, big data and machine learning applications use these visualization tools. It also integrates well with advanced databases like Teradata, My SQL, SAP, Hadoop and Amazon AWS.

Benefits

The benefits of Tableau is quite long. Some of the main reasons behind its preference are -

• Excellent visualization capabilities.

• Top class performance.

• Easy to use.

• Mobile Responsive.

• Supports connectivity with different data sources.

• Informative community.

Limitations

Just like any other tool, Tableau has its cons -

• Limited data preparation tools and techniques.

• Costly as compared to other tools.

• Time-consuming custom formatting process.

• Shortage of editing and design features.

Explore igmGuru's Tableau training program to become Data Visualizaton experts.

2. QlikView

QlikView is a major player in the data visualization market. It provides bang on solutions to thousands of clients in hundreds of countries. Its data visualization tool enables customized and accelerated visualizations. It also incorporates many different solid features like enterprise reporting, business intelligence capabilities and analytics.

It integrates data from many different sources like spreadsheets, databases and much more. A single platform lets users access as well as analyze data spread throughout the company. It also comes with many advanced analytics features like data mining, statistical analysis and predictive analytics.

Benefits

There are many benefits of QlikView for any business that uses it.

• User-friendly interface.

• Great for complicated data analysis.

• Appealing and colorful visualizations.

• It has an associative data engineer.

• Trouble-free maintenance.

• Many built-in features for visualization.

• A cost-effective solution.

• Executes gigantic queries at a good pace.

Limitations

Here are some drawbacks of QlikView -

• Tedious to utilize for non-technical users.

• Poorly designed when it comes to sharing and reporting on emails.

• Unrefined and extensive product strategy.

• Unsatisfactory performance with respect to its intense speed.

• Complicated price structure.

Explore igmGuru's QlikView Developer Training program to learn more about QlikView.

3. Power BI

Power BI is Microsoft's easily usable data visualization tool. It is available for both on-premise installation as well as deployment on the cloud infrastructure. Power BI is a complete tool that supports many backend databases. This list includes Salesforce, Teradata, Oracle, PostgreSQL, Github, Google Analytics, Azure, Adobe Analytics, Excel and SQL Server.

It is an enterprise-level tool for creating stunning visualizations and delivering real-time insights. This tool has a transformative role in every industry and company it enters. It empowers the user by streamlining workflows, propelling the projects to greater heights and optimizing the decisions.

Benefits

A offers a good amount of benefits to anyone who uses it. These are some must know pros of Power BI -

• Specialized tech support not needed.

• Personalized and rich dashboard.

• Integrates easily with existing apps.

• No memory or speed constraints.

• High-grade security.

• Compatible with all Microsoft products.

• Real time access to information.

• Robust ETL and data modeling capabilities.

Limitations

Let's look at some cons of Power BI -

• It would not function without proper internet access.

• Not user-friendly for beginners.

• High-costs for getting access to its advanced tools.

• Not compatible with some tools.

• Restricted customization for visuals.

Related Article - Power BI Tutorial

4. Looker

Looker is a great open-source data visualization tool that gives detailed data and analyzes important insights. Its real-time data dashboards add more detailed analysis so that companies can instantly make decisions. It also has links with Snowflake, BigQuery, Redshift, and 50+ SQL dialects. This lets it connect easily to different databases.

It is a part of the Google Cloud Platform (GCP). Being a part of such a huge platform reflects on the benefits it offers. It has its own dependency language called LookML, which is built around SQL. Thus professionals with SQL knowledge find it easy to get started with Looker.

Benefits

It has a long list of benefits. Some of the main pros of Looker are discussed below.

• Intuitive and easy to use.

• Easy creation and customization of dashboards.

• Responsive and supportive customer service team.

• Integrates well with databases and data platforms.

• Different attractive visuals.

• Real time insights into data.

Limitations

Some of the key disadvantages of Looker are as follows -

• It lags while working on larger projects.

• Insufficient customer support for free users.

• Sketchy pricing structure as there is limited information for the paid version.

• Not suitable for all businesses due to its cost.

Go through igmGuru's Looker Training program to learn Looker with industry experts.

5. SAP Analytics Cloud

SAP Analytics Cloud has the ability to perform intelligent data analysis for reviewing data and developing visuals for forecasting business consequences. It has some of the most updated modeling tools for delivering insights about any data mistakes. This tool categorizes different data metrics and dimensions with these modeling tools.

It suggests intelligent transformations to the data. This is counted as a top one on the list of the most used tools for data structure visualization. Customer satisfaction is achieved through natural language and artificial intelligence technology for any business questions about data visualization.

Benefits

This cloud-vase analytics tool is great for data visualization. Some of the top benefits of SAP Analytics Cloud are -

• Different visualization tools like tables, charts and graphs.

• Links and analyzes data from different sources.

• Uses ML and AI for connecting data.

• Integrates with other SAP products.

• Collaboration tools for sharing data stores, reports and dashboards.

Limitations

Here are few drawbacks of SAP Analytics Cloud -

• Unresponsive and not constructive technical support.

• Limited exporting capabilities.

• Complicated planning feature.

• Its predictive analytics features cannot compete with other opponents as it lacks advanced capabilities.

Explore igmGuru's SAP SAC Analytics Cloud Training program to start your career in data analysts.

6. Zoho Analytics

Zoho Analytics, one of the best data analytics and business intelligence tools, creates eye catching data visualizations based on the given data in no time. Zoho Analytics files can be exported in any format like Excel, Spreadsheet, PDF, etc.

Benefits

Going for this tool will give a number of benefits to its users. Take a look at some of these mentioned below.

• Its pricing model has low costs.

• Data is safe with its role based access controls.

• Simple interface for people with no tech skills to make reports, charts and dashboards.

• Other great features like report sharing and email scheduling.

• Can be used on any device.

Limitations

Zoho Analytics has its drawbacks despite its many advantages. Let's take a look.

• Excessive learning curve for beginners.

• Unclear and excessive technical assistance videos.

• Results in stagnancy while all apps are functioning.

• Restricted customer support.

7. Domo

Domo has different data visualization tools to give a stable platform for data analysis. This creates practical data visualizations for people to understand the data conclusions with ease.

Benefits

Users must know at least some points out of the long benefit list of Domo which are mentioned below.

• Cleanse, merge and analyze data from any or different sources.

• Identify and understand market trends in no time.

• Companies get the most value from their data with this tool.

• Make better business decisions.

• Proactive decision making.

Limitations

• Here are some must-know cons of Domo.

• Complicated pricing structure.

• It does not have advanced statistical computation capabilities.

• Not easy to navigate.

• Limited analytic capabilities.

8. Yellowfin

Yellowfin is very much well known in every part of the world. Its automation product is perfect for people who have to make decisions in less time. It solves analytical challenges and shows businesses what, why and how it happens.

Benefits

There are some amazing aids to get from this tool. Here are some of the best ones to find a reason to select this software out of other options.

• Expose concealed trends to find new perspectives.

• Makes appealing and engaging visualizations.

• Analyze complicated datasets in the dashboards.

• Gives industry based answers.

Limitations

Let's go through some of its cons to understand the tool better.

• It does not support multiple languages and is only available in english.

• It does not support other platforms.

• Expensive yearly subscription.

• Its support service does not include anything like a phone support or forum.

9. Infogram

Infogram does not need its users to have design skills to create striking infographics and charts in less time. It gives many design templates, icons, pictures, maps and charts options to customers.

Benefits

• A simple editor to modify the visualizations.

• Beautiful charts and graphics to insert in blogs and websites.

• Good amount of photos, icons and GIFs option to style the visualizations.

• Examine data with infogram tabs.

• Simple to make use of and understand for new users.

• Increases audience engagement.

Limitations

Some cons of Infogram are mentioned down below.

• The basic package doesn't let you change the font size or style for text editing.

• It has some pricing and paywall restrictions.

10. Grafana

Grafana takes no money from its users to analyze and track data. It's a loved tool by developers and data enthusiasts for its flexibility and its ability to blend with other tools. It has tools to change time series database data into clear visualizations and graphs.

Benefits

• Users can ask questions, show data, set up alerts and look at metrics.

• This platform is fast, controlled and available.

• Sea of visualization options like grapes, geomaps and histograms.

• Set up alerts to detect an anticipated scenario.

Limitations

This tool also has some limitations-

• Challenging learning curve.

• Complications in creating reports.

• Lacks advanced security features.

• Complicated setup.

11. RAW

The other name for this tool is RawGraphs which works with data like TSV or CSV files. It gives a link to connect data visualization and spreadsheets. It has different layouts of all kinds from traditional to modern.

Benefits

This tool gives a myriad of awesome plus points to users who make the most out of it. Here are some plus points to get an idea -

• Speedy visual feedback.

• Simple interface and readability to get visual graphics.

• Good option for scalability.

• Arranges and reads user's data.

• Keeps the data safe.

Limitations

Now, let's look at a few pointers to highlight the cons of RAW.

• Limited interactions.

• Not suitable for large datasets as it results in lagging.

• Shortage of built-in data cleaning tools.

• It does not have scripting support.

12. Datawrapper

Data Wrapper is not only free but well known in the market . It is known for its deep rooted ability to present graphical statistics on big data. Users can create maps and charts that they can insert into reports.

Benefits

There is an endless list of bonuses for this tool and here are some of those -

• Features a simple interface.

• No installation needed to create charts.

• Free of cost to use and apply.

• Great option for beginners.

• Correct and consistent data,

• Understanding of customer behaviour.

Limitations

A few limitations of Data Wrapper are -

• Basic chart types.

• There aren't many customization options.

• To get some of the advanced features, you need to pay for a subscription.

13. JupyteR

Users can share and create documents which have visualizations, live code, narrative text and equations with this web application. It is a good one for interactive computing and statistical modeling. It gives hassle free cleansing and transformation of data.

Benefits

There are enough reasons to go after JupyteR to enjoy a number of benefits like the ones mentioned down below -

• Gives eye catching results.

• Trouble free sharing of data insights.

• Recognizes patterns, analyzes data and smooth memory retention.

• High speed prototyping.

• Interactive computing.

Limitations

Here are some disadvantages of the tool.

• Learning curve can be tough for newbies.

• Keeping track of different notebook versions can get tricky.

• It might use a lot of your computer's resources.

• It's not the best choice for larger software development.

• Dealing with dependencies can be extra work.

14. Dundas Bi

Dunbas Bi tool makes and shows animated dashboards and scorecards. Users can set up this platform however they want for data analysis in a flexible and open way.

Benefits

• It gives extraordinary flexibility.

• It has a good amount of data sources and charts.

• Features to display, modify and extract data with zero troubles.

• Supports complicated data environments.

• supports standard file formats.

• Connects to cloud storage and enterprise systems.

Limitations

Here are some limitations of this tool-

• Requires more built-in functions.

• Insufficient online support.

• Difficult to identify visualization filters.

15. Plotly

Plotly gives complete integration with programming languages which centres around analytics like Matlab, R and Python to create complicated visualizations. This tool supports easy cloud deployment and installation.

Benefits

These are some of the best benefits to convince oneself to get Plotly -

• It's mostly used for modifying, creating and sharing graphical data.

• It supports collaborative work.

• Users can edit charts online.

• Exports high quality images.

• It has an engaging interface.

Limitations

Here are some disadvantages of the tool

• Browser dependency and inability to function properly without JavaScript.

• Stagnancy while dealing with large datasets.

• Interoperability with other libraries.

16. Google Charts

Google Charts is a free API and JavaScript based charting library. It offers simple, engaging charts and enhances web applications with its engaging charting capability. It enables software development teams to envision their website data in the form of area charts, line charts, histograms, pie charts, pictographs and so on.

Benefits

• An extensive library offering a wide range of chart types.

• Easy to use for users with less coding knowledge due to its simple API.

• Adaptable chart options to change fonts, colours, etc.

• Users can form charts easily with built-in templates.

• User-friendly tools to animate data in a chart.

Limitations

The criticism against Google data privacy policies raises concerns for users to utilize a Google product.

Shortage of advanced capabilities and features.

This tool's customization options still remain somewhat limited in comparison with other libraries.

17. ChartBlocks

ChartBlocks is a robust no-code and cloud-based tool, curated for visualizing data. It visualizes data through a wide range of chart types. It has pre-made templates with a variety of colours, grids, sizes and fonts which can be easily edited. It prevents the requirement for coding or graphic design experience by enabling users to transform spreadsheet data into shareable graphics with ease.

Benefits

• Seamless collaboration with team members with shareable charts.

• Simple, easy-to use and efficient dashboard.

• Hassle-free data importation.

Limitations

• Limited free plan.

• Users cannot create or edit offline.

• Poor performance while dealing with large datasets.

18. FusionCharts

This is a web-based data visualization software, bringing a large number of benefits for all sizes of businesses. It utilizes JavaScript programming language to transform real-time data into comprehensive graphs for organizations. It offers about 2,000 region-specific data maps and over 50 statistical charts or other chart types.

Benefits

• Offers a wide range of fonts.

• Users can add customer annotations to the graphs.

• It's flexible and blends smoothly with different frameworks.

Limitations

• Inconsistent documentation for charts.

• Possible bugs within the software.

• Cannot deal with large amounts of data points without lagging occasionally.

19. Sisense

It's a data analytics and BI platform which provides assistance to companies in analyzing and visualizing data from distinct sources into workflows, dashboards, apps, reports, etc. This platform emphasizes businesses that require analytics capabilities but lacks adept professionals.

Benefits

• Outstanding technical support.

• Forms impactful and easily accessible dashboards.

• Extracts large amounts of data from distinct sources in no time.

• Connects seamlessly to all data storage platforms.

Limitations

• It's an expensive solution.

• Requires a reliable plan despite the many plans available.

• Seeking permissions is not hassle-free as only owners of dashboards and folders can make changes.

20. D3.js

D3 stands for Data-Driven Documents, and D3.js is a JavaScript library that helps you work with documents based on data. It's a solid choice for creating data visualizations. With D3, developers can build dynamic and interactive visual displays right in the browser using HTML, CSS, and SVG. Basically, data visualization is all about showing filtered data as images and graphics.

Benefits

• Highly interactive.

• A large community for support and resources.

• Handle large datasets with ease.

• Fabricates engaging visualization for users.

Limitations

• Complicated learning curve.

• Concerns with data security and privacy policies.

• Compatibility struggles with older versions of browsers.

How To Choose the Best Data Visualization Tool?

Effectively conveying information is regarded highly for the growth of a company. There are many different data visualization tools and techniques that play their unwavering role in turning complicated data into concise and actionable insights. But this long list of available tools can also lead to confusion. It all comes down to choosing the right data visualization tools and techniques for your needs. Here are certain pointers to keep in mind-

• Understand the Data

There is no dearth of amazing tools and techniques for visualizing data. Since there are many different types of data, the tools and techniques apt for visualizing it are also different. Understanding the kind of data one has at hands will directly influence which tool and technique is used.

1. Data Type - Data is often segregated as categorical or numerical. The first one includes customer segments or product categories, which is best represented through pie charts or bar charts. Numerical data includes sales figures or stock measurement. This is best represented through scatter plots or line charts.

2. Data Relationships - Network diagrams or scatter plots are best for showing the relationships between variables.

3. Data Volume - Gigantic datasets must be handled with advanced techniques like interactive visualizations or heatmaps.

• Follow Best Practices

Visualizations are supposed to effectively communicate the findings. This can only be done by following best practices, which also ultimately sways which tools and techniques are used. Some key best practices to always stick to are -

1. Simplicity - The visual should be clutter-free and without any unnecessary decorations to avoid any distractions.

2. Consistency - The complete visualization should maintain a consistent style, color theme and look.

3. Accessibility - The entire intended audience should be able to access and understand the visuals. This includes tech people, non-tech people and even those with any disability.

4. Clarity - Clear visuals mean better understandability with clear axes, labels and legends.

5. Interactivity - The interactive elements should be used carefully for engaging the audience thoughtfully.

6. Narrate a Story - Every visualization should have a strong narrative to it. Optimum insights and relevant context help in fulfilling this best practice.

• Experiment & Learn

Picking the right techniques and tools is highly dependent on what one finds to be useful over a period of time. This means that one has to learn through experimentation and analysis. See what works the best as per the data and intended audience.

Final Words

Many different job titles and roles today require the individual to have knowledge of best data visualization tools. Different factors affect which tools and techniques one picks for visualizing their data. All aspirants and learners should have good knowledge about these 20 best ones.

FAQs for Best Data Visualization Tools

Q1. What does one understand by data visualization tools?

Data visualisation tools are basically software that visualize information in different ways. One can find data patterns, extract valuable insights and make beneficial decisions with these visuals.

Q2. Why are data visualization tools important?

Such tools are very important as these are best for identifying data patterns and exploring complicated relationships. Business forecasting and making decisions use these findings.

Q3. Who uses data visualization tools?

Many industries like healthcare, retail, hospitality and finance use these tools. These also act as primary tools for data engineers, data analysts, business analysts and other job titles.

Q4. How to master data visualization tools?

Mastering these tools is a simple process. Anyone can master these tools with different methods like joining online courses, tutorials or training. Regularly using them will automatically lead to a high level of experience.

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