Big data is everywhere, and as a result, visualization tools are in high demand. Data visualization allows you to easily spot trends and patterns that might otherwise go unnoticed.

The problem is there are so many different tools out there, so selecting the right one for your business can be challenging. If you’re looking for the best data visualization tool for your business, this guide will help you find it.

In this article, we’ll explore 15 of the top tools on the market along with examples of each to help you narrow down your options and make an informed decision. What Is Data Visualization? Data visualization is a way to convey information using visual elements like charts, graphs and maps.

The purpose is to take large amounts of data and present it in a way that’s easy to understand at a glance. It’s also an excellent way to communicate key messages across entire organizations.

Why Is Data Visualization Important? Data visualization is an essential part of any successful business strategy because it makes it easier for employees, clients and shareholders to understand complex data sets quickly. Effective data visualization allows you to better track progress toward goals, make smarter decisions based on real-time information and give team members actionable insights into their performance.

Data Visualization Tools – Introduction

Data visualization tools are a type of graphic and information representation that has the purpose of presenting data in a way that is easier to understand. They often include options to filter, sort, and compare data, as well as display it in a number of ways.

Their main purpose is to make analyzing large amounts of data much easier by reducing it to a visual representation that is not only easier for the brain to process, but also more engaging and interesting. Data visualization tools have become incredibly popular over the years, particularly with the advent of big data and its role in business.

As such, there are now many different types of tools available for different industries and purposes. Some examples include: Dashboards – these have become very popular as they display information from multiple sources in one place, usually with interactive elements like graphs or charts.

They’ve become so popular in fact that some refer to them as “the new spreadsheets”! Data Visualization Tools for Big Data – these are similar to dashboards but instead deal with big data specifically. This means they can handle massive amounts of data at once, including unstructured and real-time data.

Some companies use their own proprietary software while others use open source programs like Tableau Software’s

What Are the Best Data Visualization Tools?

Data visualization is the secret to good analytics. It’s easy to get lost in data, and it’s easy for it to look like a jumbled mess. Visualization is the key to making sense of it all.

But what tools should you use? There are plenty of options out there, and they vary widely in complexity and price. The right choice will depend on your experience, what you want to accomplish, and how much time you want to spend on it.

Here’s a quick rundown of some of the best data visualization tools available today, along with their relative strengths and weaknesses. Microsoft Excel This is where most people start, and there’s a good reason for that — Excel is easy to learn and has a lot of power.

It comes with many built-in templates for common types of visualizations, including line graphs, column charts and bubble diagrams. Best of all: Anyone can get it for free by signing up for Microsoft 365 Personal or Family.

For basic purposes like creating bar charts or heat maps, Excel can be totally sufficient. But if you need more advanced capabilities, like creating custom graphs on the fly or working with massive amounts of data without slowing down your computer, then you’ll

1. Zoho Analytics

Zoho Analytics is an online business intelligence (BI) and analytics platform to understand your business data better and make informed decisions. It allows you to transform your data into insights by creating interactive visualizations, intuitive dashboards, insightful reports, and engaging stories.

Zoho Analytics also helps you share your insights with others and collaborate on data analysis by allowing them to comment or edit the reports/dashboards. Zoho Analytics also comes with a mobile app that enables you to access your reports/dashboards in a mobile device, anytime, anywhere.

Integrate Zoho Analytics with other popular apps like Gmail, MailChimp, Google Drive, Google Calendar, Outlook, Salesforce etc., to get a unified view of your business data from all these applications. You can also integrate your databases like MySQL or any database that supports ODBC connection or JDBC connection.

Analytics Apps: – Zoho Analytics for Salesforce – Track your sales performance and visualize it on Zoho Analytics dashboards within Salesforce itself. – Zoho Analytics for MailChimp – Track the performance of your email campaigns in real time and improve the quality of leads generated from them.


Easy to use BI and reporting tool. Powerful data ingestion, modeling and enrichment.

Drag-and-drop report builder with multiple visualization options. Collaborate on reports through comments and annotations. Predictive analytics with machine learning models.

Embedded dashboards in Web and Mobile Apps. Powerful embeddable charts in your website or blog.


Zoho Analytics Pros There are a few features of Zoho Analytics that make it stand out in comparison to other options.

  1. Zoho Analytics offers a comprehensive, cloud-based data warehouse. There is no limit on the number of users, databases or queries with the unlimited plan.
  2. Zoho Analytics is an extremely affordable solution for businesses.

2. Databox

It’s not just for ecommerce. Databox was created to help businesses of all sizes measure the impact of their marketing and sales efforts across the entire company.

Gaining visibility into what is working (and what isn’t) is critical to improving your results and growing your business. One place to track everything that matters. Databox makes it easy to see and share the data you need to make better decisions.

We integrate with hundreds of apps so you can quickly roll up the most important data from across your organization in one place. We’re here to help you grow faster. Databox helps companies grow faster by making it easy for anyone in your company to see and understand the performance of their marketing, sales and operations efforts in real-time.

Databox transforms your business data into insights that lead to action. Transform all your KPI’s into a single business dashboard and get the insights you need to grow your business. Databox is the easiest way to track, visualize and share your key performance indicators.

Connect to over 50+ data sources, create unlimited custom metrics and build dashboards that matter to you and your team.


Databox offers a wide range of features to help you manage your marketing team and make better decisions. Analytics Integration: We offer integrations with all the major analytics, marketing, and sales platforms — Google Analytics, Facebook, HubSpot, MailChimp, Salesforce, and many more.

We are also one of the only analytics dashboards that support data from Amazon Redshift. Custom Data Sources: In addition to our native Google Analytics integration, we also support custom data sources that can include any data that can be pulled into a CSV file or spreadsheet.

In this way, you can track almost any metric you want including CRM reports, accounting reports, JSON files and more. Data Cleaning: Using our custom formulas feature, you can clean your data before it is displayed in your dashboard in order to remove unnecessary decimal places or add additional calculations.

You can also use this feature to calculate the difference between two numbers or percentage change over time. Data Visualization: Databox offers a number of visualization options including line charts, column charts (both stacked and unstacked), pie charts and more. You can combine these types of visualizations within a single chart view as well as create multiple chart views within a single Metric


Databox pros: You can integrate with any data source. This means you can collect all the data you need to monitor your marketing performance in one place, rather than having to jump between different analytics platforms.

The interface is user-friendly and very easy to navigate. You can add as many metrics as you want and still have a clean dashboard.

You can easily customize the dashboards that you create. You can also share them with your team or clients using a private link. Databox Pros: You Can Integrate With Any Data Source

Databox allows you to integrate 100+ data sources, so you are not limited to tracking only Google Analytics and Facebook Ads. For example, you can connect your email marketing tool, Hubspot CRM, and even your accounting software.

This means that you don’t have to waste time jumping from one platform to another just to review your marketing performance. You get all the data that you need in one place.

Databox Pros: The Interface Is User-Friendly And Very Easy To Navigate Even if you want to add as many metrics as possible on your dashboard, it will remain clean and uncluttered because of the way the widgets are designed. Also, navigating through the app

3. Tableau

Tableau is a business intelligence software that allows anyone to connect to data, then visualize and create interactive, sharable dashboards. It’s easy enough that any Excel user can learn it, flexible enough to handle any amount of data, scalable enough to fit the needs of any organization, and powerful enough to analyze anything.

Tableau is a tool for everyone. It’s powerful without being complicated. It’s not just for analysts or techies anymore.

You don’t have to be a statistician or computer programmer. You don’t have to be an expert at writing SQL queries. You don’t need a degree in math or statistics

The Tableau product family starts with Tableau Desktop and Tableau Prep Builder, which are designed for individual use. When you want to share your work with others, you can publish it to Tableau Server or Tableau Online (cloud-based Tableau Server).

Tableau Desktop and Tableau Prep Builder allow you to connect directly to data stored on your computer or on a network drive (Local), or in the cloud (Cloud). When you publish your workbooks and data sources from these products to either of the two server products, you can share them securely with other people within your


Tableau is a data analytics and visualization tool that can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.

Tableau Desktop – This is a data analysis product, used by analysts to connect to files or databases and then analyze the data using common charts and graphs. Tableau Server – Used by organizations to share Tableau Desktop visualizations over the internet, this product allows for publishing of visualizations for others to see, as well as scheduling automatic updates of the data behind those visualizations.

Tableau Online – Similar to Tableau Server but hosted in the cloud by Tableau, it allows organizations without IT departments or IT resources to share Tableau Desktop visualizations. Tableau Reader – A free tool which allows users to read Tableau Desktop visualizations saved in .tde format.

Tableau Public – Also free, this tool is used by individuals to publish public data online in an interactive format.


Tableau is a great tool. It offers a wide array of functionality, and it is easy to use and learn. This post will highlight some aspects of Tableau that are particularly useful to me. Data Blending The ability to blend data in Tableau is a huge reason why I love it. The ability to blend on anything is invaluable.

It lets me combine data from multiple sources into one visualization. In my case, this can be useful for combining survey responses from Qualtrics or Survey Monkey with demographic data from the Census API.

Joining Data Joining is another neat feature that Tableau has. Although most of the time I prefer blending, joining is sometimes easier than setting up a data blend, especially if there are only 2 sources of data involved and one of the sources does not change very often (for instance, if you have survey responses from Qualtrics and an Excel file with demographic info about the survey respondents).

Calculated Fields Tableau allows for the creation of calculated fields based on other fields in your data set, as well as custom formulas (in addition to being able to summarize by any measure). To add more flexibility, calculations can be nested within each other.

In short, Tableau provides a lot of

4. Infogram

Infogram is a visualization platform that allows anyone to easily create charts, graphs and infographics. Create professional charts, maps and infographics in minutes. With Infogram, you can create beautiful charts and infographics with the help of over 400 interactive maps, 70 chart types and easy-to-use templates.

Our easy-to-use platform enables you to quickly share your data with colleagues, clients or on social media. You can also embed your visuals on website or blog. Infogram is used by more than 2 million users around the world; including government agencies, educational institutions and businesses of all sizes.

Infogram was founded in 2012 by Raimonds Kaže and Uldis Leiterts, who wanted to make it easy for anyone to create charts and infographics from data. In 2013, Infogram launched its first product – an online platform for creating visualizations.

Since then, Infogram has grown exponentially, now serving more than 2 million users from over 200 countries around the globe. Infogram’s mission is to democratize data visualization across the web.

Infogram is the easiest way to create and share beautiful infographics, reports, charts and maps. We empower organizations to tell their stories on any device or platform. Simply put, we make data beautiful.


Infogram provides a wide range of options for creating charts, maps, and infographics in minutes. You can also use our editor to upload and customize your own design or take advantage of one of our infographic templates.

Charts, graphs, and maps We offer a variety of different chart types to meet every need: bar graph, line graph, pie chart, area graph, stacked column, Venn diagram and more. All are custom-designed by professional designers to make your presentation stand out.

Presentations Create interactive presentations with Infogram in minutes. Make them embedded and shareable or download as a PDF file.

Infographics Use the Infogram editor to create beautiful infographics that combine images, text and charts into an eye-catching design. Or choose from hundreds of infographic templates that are ready to customize and go.


The Infogram Pro account is designed for users who need to: Create and edit charts and maps with additional customization options Consolidate all their charts under one account Get access to more data sources Make their charts private when embedding them on a website or blog Upload custom maps, images, and logos Access more fonts, templates, colors and themes Post unlimited posts to social media channels (Facebook, Twitter) directly from Infogram.

5. ChartBlocks

ChartBlocks is a lovely tool for creating charts and graphs on the fly, and any reasonably-experienced designer can get up to speed with it in less than an hour. The interface is straightforward and intuitive; once you’ve signed up for a free account (or paid one) you’re up and running.

You don’t need to install anything there’s no Flash or Java involved; everything runs in your browser. You can choose from a number of different chart types, including line, area, column and bubble charts.

There are also more specialist chart types such as sunburst, Venn diagrams and treemaps. Your data can be imported from Google Spreadsheets or Excel files; simply drag your files onto the interface to import data.

Alternatively, you can type it out directly into the ChartBlocks interface (in which case you might want to keep a backup of your work saved locally). You can preview your data at any time by clicking the Preview tab. This can be especially useful if you’re working with large datasets that might be causing performance issues.


Unleash your creativity with our easy-to-use tool for creating charts. Our drag and drop interface gives you complete control over how your charts look and function. Choose from the best chart types. Our clean, modern design lets you pick from bar, line, area, pie and scatter charts. You can also create your own custom chart type with our tools.

Import data from anywhere. You can import data directly from Excel or Google Spreadsheets or upload a CSV or TSV file to create a chart. You can also import data directly from an API or database query via our DataSet system.

Bring your data to life with animation and interactivity. Add beautiful animations to your charts just by ticking a box. You can also add interactive features like tooltips and data tables allowing users to explore your data in more detail.


ChartBlocks Pros User friendly Easy to use and easy to share. Affordable Costs a fraction of the price of other services.

Unlimited data sets Add as many data sets as you like, with no restrictions on the size of your data. Customizable charts

6. Datawrapper

If you want to visualize data, Datawrapper is the tool for you. All it takes is a few clicks to create a line chart or bar graph and publish it on any platform.

Data visualization is a great way to communicate information in a simple, easy-to-understand format. It’s particularly useful for presenting insights from market research such as survey data.

Although there are many different tools you can use to create charts and graphs, they can be difficult to learn and turn out pixelated images that don’t look professional. Datawrapper solves these problems by offering easy-to-use tools that generate high-quality charts that scale well.

Datawrapper is a tool specifically designed to make the process of creating charts and maps as simple as possible. It is an open tool, and you can use it for free on the web.

Datawrapper is a web application that makes it easy to create charts and maps. Our mission is to make data visualization easier, not just for professional journalists, but for everyone.


Tables Highlight and compare values in a table A great way to show data in rows and columns. Tables are good for showing a lot of numbers, especially when you want to highlight certain rows or columns.

They’re also good for highlighting differences between your data. Bar charts The most popular chart type: Bar charts are simple and easy to understand Bar charts are the most common chart type. People easily understand how different bars compare to each other.

That’s why they’re the best choice if you want to show the relationship between different categories of data. Line charts Show trends over time with line charts Line charts can show a trend over time (or over any other category you have).

They work best when there’s a big difference between each value. Some examples: Number of people using your product, stock prices, temperature changes, birthrates, or the number of items sold per day/week/month/year.

Pie charts Show the distribution of one category with pie charts Pie charts are best used to show how much each group (or major part) contributes to an amount. For example, you can use pie charts to display how different categories of products contributed to total sales last year. Or you could use them to show howPros


  1. It is easy to use, and with some practice, I can make a great looking chart in minutes.You can upload data in multiple formats and can analyze your data right on the website.
  2. Great support resources and intuitive user interface. The charts are responsive and look great while being shared via social media or emails.
  3. You can add charts to your website directly using the embed code (You don’t have to be a programmer). It has a built-in functionality to share your chart online easily.

7. Plotly

Plotly is a free and open-source graphing library for Python. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.

Get started with Plotly’s Python graphing library to make interactive, publication-quality graphs online. Examples of how to make line plots, scatter plots, area charts, bar charts, error bars, box plots, histograms, heatmaps, subplots, multiple-axes, polar charts, and bubble charts.

Python has a number of powerful plotting libraries to choose from. Although many fundamental data processing functions exist in R, they have been a bit convoluted to date and have lacked consistent coding and the ability to easily flow and process data from one step of analysis to the next.

For this reason, I’ve recently switched my work over primarily to Python and will be working on creating more tutorials about my workflow. If you’re interested in learning more about python, I highly suggest checking out DataCamp’s free Intro to Python for Data Science course. The plot below was created by this code:

import plotly.plotly as py import plotly.graph_objs as go


Plotly’s Python graphing library makes interactive, publication-quality graphs. Online and offline plotting You can use Plotly’s python API to plot inside your Jupyter Notebook by calling plotly.plotly.iplot() or plotly.offline.plot().

Embedding Maps & Graphs in RMarkdown We have an R package for working with Plotly’s R API. See their documentation here. Embedding Maps & Graphs in IPython Notebooks IPython notebooks are great for interactive exploration, but they’re not the best choice when it comes to presentation or sharing your work. We have a Python package for working with Plotly’s Python API. See our documentation here to learn more!


Many users start with Plotly Express, but we recommend moving away from it and using the full Plotly Python package. Here are some reasons why: Plotly Express is a terse, consistent, high-level wrapper around that exposes a simple syntax for complex charts.

The chart-studio package can be used to upload plotly figures to Plotly’s Chart Studio Cloud or On-Prem services. is a separate library than plotly which provides an interactive graphing library for Python.

It is built on top of d3.js and plotly.js and can be used to create many different types of visualization including statistical charts, 3D graphs and more! This library can be installed with pip: pip install plotly .

Plotly provides online graphing, analytics, and statistics tools for individuals and collaboration, as well as scientific graphing libraries for Python , R , MATLAB , Perl , Julia , Arduino , and REST .

8. Visually

Visually is the easiest, most beautiful way to create and share powerful visuals. Create and market visual content that tells your brand story and increases audience engagement across devices.

We help you connect with your audience through visual storytelling by creating custom infographics, data visualizations, custom presentations, branded video and interactive content.

Our research (and experience) shows that visuals increase time on page by 94%, shares by 90%, views by 65% and engagement by 32%. Your eye is drawn to the bright red, and the blue and green. The text is white, so it pops off of the page.

The woman’s face and the color of her clothes make her stand out against the background. Your eye goes to what stands out. And that’s not a coincidence. This is how we’re wired — we notice what stands out in our field of vision because it could be a threat or an opportunity.

This is why images are so important on your website, presentations, social media posts, etc.


We are excited to announce that Visually is a finalist for the 2013 <a href=””>Crunchies</a> awards, the tech industry’s leading startup awards program.

We are in the running for Best Startup of the Year and Best Collaborative Consumption Service of the Year. We are up against some great companies and thought leaders, including: Best Startup of the Year

  • Dropbox
  • Etsy
  • Evernote
  • Pinterest
  • Square
  • Uber

Best Collaborative Consumption Service:

  • Airbnb
  • Airbnb for Work (new!)
  • Lyft
  • Sidecar


Visually Pros Easy to access: Visually is integrated with all major social media platforms and has a mobile app. This makes it very easy to access and share visually right from your phone.

Great tools: Visually has a variety of tools that make the creating process much easier including a storyboarding tool, inspiration boards, drag and drop design tool, and a content calendar.

Tons of templates: Visually has thousands of templates. This means you can find exactly what you’re looking for and then simply swap in your own photos/logo to customize it. High quality images: Visually has a huge library of images to choose from and high quality photographers.

You can also request specific images for your project if you don’t find what you’re looking for in the library. Large community: With over 100,000 creators on Visually all around the world, there are plenty of options for finding the right person to create what you need.

9. D3.js

D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG and CSS. D3’s emphasis on web standards gives you the full capabilities of modern browsers without tying yourself to a proprietary framework, combining powerful visualization components and a data-driven approach to DOM manipulation.

D3 allows you to bind arbitrary data to a Document Object Model (DOM), and then apply data-driven transformations to the document. For example, you can use D3 to generate an HTML table from an array of numbers.

Or, use the same data to create an interactive SVG bar chart with smooth transitions and interaction. D3 is not a monolithic framework that seeks to provide every conceivable feature. Instead, D3 solves the crux of the problem: efficient manipulation of documents based on data.

This avoids proprietary representation and affords extraordinary flexibility, exposing the full capabilities of web standards such as CSS3 and HTML5. With minimal overhead, D3 is extremely fast, supporting large datasets and dynamic behaviors for interaction and animation. D3’s functional style allows code reuse through a diverse collection of official and third party components.


D3.js Features: D3.js is a JavaScript library that allows data to be represented as a collection of nodes that are connected to one another. The strength of the connections between these nodes represents the magnitude of the relationships between data objects.

In this visualization, nodes can be clicked to expand and collapse them, and edges can be dragged to reposition them. Data objects can be filtered in and out of the visualization, which is useful for highlighting specific subsets of related objects.

These filters can also be nested to create arbitrarily complex graphs.


  1. D3.js is easy to learn
  2. D3.js can handle large datasets easily
  3. D3.js has a feature of dynamic property which allows you to execute data-driven transformation on a web page
  4. D3 library also offers great flexibility which means you can use it in conjunction with other JavaScript libraries and frameworks such as Angular, React and VueJS

10. Ember Charts

Ember Charts is a charting library built with the Ember.js and d3.js frameworks. It includes time series, bar, pie, and scatter charts which are easy to extend and modify. The out-of-the-box behavior these chart components represents our thoughts on best practices in chart interactivity and presentation.

Our goal with Ember Charts is to provide a library of standard chart types that can be composed into more complex visualizations. For example, imagine an “upgrade” button that changes a simple bar chart into an interactive time series chart. This composability is one of the primary benefits of this library

Ember Charts is a charting library built with the Ember.js and d3.js frameworks. It includes time series, bar, pie, and scatter charts which are easy to extend and modify. The out-of-the-box behavior these chart components represents our thoughts on best practices in chart interactivity and presentation.

The Ember Charts project is an attempt to build a common set of reusable charts and components for the Ember.js community to use.


Ember Charts is a charting library built with the Ember.js and d3.js frameworks. It includes time series, bar, pie, and scatter charts which are easy to extend and modify. The out-of-the-box behavior these chart components represents our thoughts on best practices in chart interactivity and presentation.

Ember Charts is designed to be customized: all the details can be changed by passing in a new options object when creating the chart. If you’re looking for something different, it’s easy to make changes:

Every component can be extended via Object Oriented JavaScript techniques or by using mixins. You can customize the appearance of each component by overriding CSS stylesheets that come packaged with the library.

Every component has options that customize its appearance and behavior in-depth.

Pros Pros of Ember Charts:

Ember Charts is a charting library built with the Ember.js and d3.js frameworks It includes time series, bar, pie, and scatter charts which are easy to extend and modify The out-of-the-box behavior these chart components represents our thoughts on best practices in chart interactivity and presentation

The charts are easily customizable using CSS. Ember Charts is based on the excellent work done by the D3.js community, including Mike Bostock’s D3.js and nvD3.js

11. NVD3

NVD3 is a data visualization library, and is used to create the charts you see on this website. NVD3 uses d3.js under the hood, and provides an intuitive interface for creating reusable charts and components.

If you’re not familiar with d3.js, it’s best to first check out our simple bar chart example and then take a look at the complex bar chart. If you’re familiar with D3, you won’t have any trouble using NVD3 in your next project.

The library also uses nvd3-community for commonly used chart types (such as linePlusBarChart) that are not included in the main library (lineWithFocusChart). VD3 Re-usable charts for d3.js This project is an attempt to build re-usable charts and chart components for d3.js without taking away the power that d3.js gives you.

This is a very young collection of components, with the goal of keeping these components very customizeable, staying away from your standard cookie cutter solutions. Built on top of d3.js and, Plotly.js is a high-level, declarative charting library. plotly.js ships with over 30 chart types, including scientific charts, 3D graphs, statistical charts, SVG maps, financial charts, and more.


The NVD3 library is amazing and super flexible. Here are some of the features you can use:

  1. Reusable charts
  2. Animated transitions
  3. Multiple X,Y axes
  4. Canvas and SVG Rendering
  5. Chart types: Line, Bar, Stacked Area, Pie, Donut and Scatter Plots
  6. Date formatting on the time scale
  7. Customizable tooltips (HTML)
  8. Mouseover highlights
  9. Zoomable area


NVD3 Pros For those of you who don’t know, NVD3 is a D3-based charting library for AngularJS and React.js that allows you to create reusable charts with a higher level of customization than most libraries offer. NVD3 comes with some great features:

Reusable charts Smooth transitions Customizable styles Easy to integrate with other libraries like Angular and React NVD3 Cons Despite the pros mentioned above, there are also some cons to NVD3. Here are a few common issues you’ll encounter when working with NVD3:

Difficult to customize and style certain chart components (e.g., tooltips, axis labels) out of the box. This means more time spent trying to figure out how these components work so you can customize them.

You can always refer to the documentation, but it’s not very extensive in some areas. I found myself looking for answers on Stack Overflow more often than I would have liked.

12. Google Charts

Google Charts provide a perfect way to visualize data on your website. From simple line charts to complex hierarchical tree maps, the chart gallery provides a large number of ready-to-use chart types.

The most common way to use Google Charts is with simple JavaScript that you embed in your web page. You load some Google Chart libraries, list the data to be charted, select options to customize your chart, and finally create a chart object with an id that you choose. Then, later in the web page, you create a <div> with that id to display the Google Chart.

To see this process in action, try out our Simple Column Chart example. n this documentation we’ll walk through how to create charts using Google Charts.

We’ll start by explaining how to create simple charts. Then we’ll go over some commonly used customization options for theming and modifying the chart layout. Finally we’ll discuss advanced topics for creating custom charts and scaling to thousands of data points.


Features Overview A chart that lets you render each series as a different marker type from the following list: line, area, bars, candlesticks, and stepped area. Interactive Candlestick Charts with Google Visualization API An example of a candlestick chart that allows the user to select a range in the chart using two vertical range markers.

The selected start and end points can be adjusted as well. Google Chart Tools – Google Developers Full information on how to use Google Charts on your site. Includes interactive demos that show how to set up your page and make charts work.


Pros: It is an open source tool. It is very easy to learn and use.

Very interactive, user can change the graphs without reloading the page. Google Charts supports a wide range of charts like bar charts, line charts etc.

It has a large collection of charts and maps.

13. FusionCharts

FusionCharts is a JavaScript charting library that enables you to create interactive charts, gauges, maps and dashboards in JavaScript. It works with all browsers (including IE6/7) and across devices, including iPhone, iPad, Android, Windows Phone 8 and modern desktop browsers.

FusionCharts is the industry leader in enterprise-grade data visualization products. At its core is FusionCharts Suite XT—the most comprehensive charting library available with over 90+ charts and 1000+ maps.

It also includes microchart widgets to visualize real-time data streams, Gantt charts for project planning & scheduling, JavaScript maps for interactive clickable maps, and FusionWidgets XT for real-time streaming dashboards.

FusionCharts Suite has been used consistently by over 10 million developers across 118 countries for the past 12 years. Why Choose FusionCharts? Faster Adoption: With a single line of code & smart defaults, FusionCharts offers faster chart adoption than any other solution.

 Chart Types: Supports over 9+ chart types ranging from line to financial charts. Plus it comes with 1000+ maps and microcharts for real-time monitoring Interactivity: Users can interact with the charts in various ways like hovering


FusionCharts Features With over 90+ chart types, hundreds of data-driven maps and 2000+ data-driven dashboards, FusionCharts is the most comprehensive JavaScript charting library.

Powerful & Lightweight FusionCharts is the most comprehensive JavaScript charting library that can be easily integrated with any web application. It comes with a wide variety of charts including line charts, spline charts, area charts, bar charts, pie charts and so on.

Moreover, it also supports 3D & 2D animations along with a drag-and-drop editor to make customized charts. Interactive & Responsive It renders fast and smoothly on all browsers including IE6 and mobile devices like iPhone, iPad, Android, Windows Phone and tablets.

The charts are highly interactive and support zooming, panning & real-time updates. It offers a range of features such as time navigator (for supporting time series data), annotations (to annotate events on web pages) & real-time updates (to stream live data).

Data Driven Dashboards FusionWidgets XT allows you to take your dashboards to the next level by providing conditional formatting options on your dashboard gauges. This allows you to create stunning dashboards


FusionCharts Pros Multiple types of charts Easy to use Customizable

14. Highcharts

Highcharts is a charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application. Highcharts currently supports line, spline, area, areaspline, column, bar, pie and scatter chart types.

It works in all modern mobile and desktop browsers including the iPhone/iPad and Internet Explorer from version 6. Standard browsers use the Canvas element and in some cases SVG for the graphics rendering. In Internet Explorer graphics are drawn using VML.

Highcharts is free for personal learning, school projects and non-profit organizations. For commercial sites we offer Highcharts with free support and updates for one year.

Highcharts is a charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application. Highcharts currently supports line, spline, area, areaspline, column, bar, pie and scatter chart types.

It works in all modern mobile and desktop browsers including the iPhone/iPad and Internet Explorer from version 6. Standard browsers use SVG for the graphics rendering. In legacy Internet Explorer graphics are drawn using VML.

Highcharts competes with commercial products such as MicroStrategy ($), Dundas Chart ($), Oracle Fusion Charts ($), InfoCaptor (€), ZoomCharts (€) and amCharts ($).


Highcharts provides a wide variety of charts. The following chart types are available: Area Chart Bubble Chart Column Chart Donut Chart Gauge Chart Line Chart Pie Chart Scatter Plot


  1. Highcharts is a pure JavaScript based charting library meant to enhance web applications by adding interactive charting capability. Highcharts currently supports line, spline, area, areaspline, column, bar, pie and scatter chart types.
  2. It works in all modern mobile and desktop browsers including the iPhone/iPad and Internet Explorer from version 6. Standard browsers use SVG for the graphics rendering. In legacy Internet Explorer graphics are drawn using VML.
  3. Highcharts is only free for non-commercial use and as such you will need to buy a license if you intend to use it in a commercial product. License fees start at $80 for a single application installation within your company or $400 for unlimited installations within your company.

15. Chart.js

Welcome to the Highcharts JS Options Reference. These pages outline the chart configuration options, and the methods and properties of Highcharts objects. Feel free to search this API through the search bar or the navigation tree in the sidebar.

Use Highcharts to create charts in different styles like line, spline, area, areaspline, column, bar, pie, scatter, angular gauges, arearange, areasplinerange and columnrange. The chart types can be combined in one chart. You can add a legend and title to explain what is shown on the chart.

Highcharts supports 3D charts. See the 3D charts section for details. The library supports loading charts from local data or remote data via AJAX callbacks. The data can be also loaded from Google Spreadsheets.

Chart.js is a JavaScript library that allows you to draw different types of charts by using the HTML5 canvas element. Chart.js provides simple yet flexible JavaScript charting for designers & developers.

It weighs just about 38 KB of JS, and that’s because it is light and fast. The biggest advantage of this library is that you don’t have to worry about which browser is the visitor using; the chart will be rendered in all browsers


To get started with the Chart.js library, first include the library after including its dependencies. The library can be downloaded in two formats: Minified version: chart.min.js (5KB when gzipped)

Development version: chart.js (74KB when unminified) The minified version is designed for production and should always be used in a live site because it has been compressed and optimized for speed and size.

The development version is meant to be used during development and debugging, as it is not compressed or optimized. To install Chart.js, add a script tag to the <head> of your HTML page that points to the location of the downloaded Chart.js file on your server like so:


Chart.js Pros Chart.js is a free, open-source data visualization library, maintained by an active community of developers in GitHub, where it rates as the second most popular data visualization library.

It’s easy to get started with Chart.js. All that’s required is the script included in your page along with a single <canvas> node to render the chart. If you don’t see anything displayed, don’t panic! It just means there isn’t any data yet.

Chart.js provides simple yet flexible JavaScript charting for designers & developers. It runs across devices including iPhone, iPad, Android, Windows Phone, Microsoft Surface, Desktops, etc

16. Leaflet

Leaflet is the leading open-source JavaScript library for mobile-friendly interactive maps. Weighing just about 38 KB of JS, it has all the mapping features most developers ever need. Leaflet is designed with simplicity, performance and usability in mind.

It works efficiently across all major desktop and mobile platforms out of the box, taking advantage of HTML5 and CSS3 on modern browsers while still being accessible on older ones. It can be extended with a huge amount of plugins, has a beautiful, easy to use and well-documented API and a simple, readable source code that is a joy to contribute to.

Leaflet is developed by Vladimir Agafonkin (currently of MapBox) and other contributors. We have a quick start guide and lots of easy examples you can follow to get your first map up in no time!

Leaflet is an open source JavaScript library for mobile-friendly interactive maps. It is developed by Vladimir Agafonkin with a team of dedicated contributors.

Weighing just about 33 KB of gzipped JS plus 4 KB of gzipped CSS code, it has all the features most developers ever need for online maps.

Have you seen our example page? It contains dozens of examples with Leaflet Maps Mark


Leaflet is the leading open-source JavaScript library for mobile-friendly interactive maps. Weighing just about 38 KB of JS, it has all the mapping features most developers ever need. Extensibility Leaflet is a highly modular library, meaning that new features can be added relatively easily.

This makes it easy to develop new extensions and write plugins to support different data providers. Plugins are available for many application frameworks, including Django.

Support Leaflet offers support for tile layers, markers, popups, polygons and more while being lightweight, simple to use and easy to customize. There’s a plugin for every need; from MarkerCluster, an excellent resource for showing large amounts of data on your map efficiently; to Leaflet Draw which allows users to draw shapes on the map.

Mobile Support Leaflet works efficiently across all major desktop and mobile platforms out of the box with tons of examples when you need start creating your own maps.


Leaflet Pros A lot of plugins Light weight (only 33kB gzipped) Flexible and easy to extend No dependencies (other than a modern browser) Support for mobile devices Free and open source (BSD license) 

What is Data Visualization?

What Data Visualization is (and isn’t) Data visualization refers to the graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data.

In features like trend lines and histograms, they make relationships between data points easier to understand. In features like heat maps, they make it easier to find patterns within complex sets of data.

Data visualization is a general term that describes any effort to help people understand the significance of data by placing it in a visual context. Patterns, trends and correlations that might go undetected in text-based data can be exposed and recognized faster with data visualization software.

Business intelligence (BI) platforms like Tableau, Microsoft Power BI, Looker and Qlik are popular examples of tools that specialize in this. These platforms provide easy-to-use methods for turning raw data into useful visuals that reveal insights about customers or products.

Data visualization is often confused with information graphics or information visualization. While these terms are sometimes used interchangeably, they actually have distinct meanings.

Information graphics are graphic visual representations of information; these include charts, maps, diagrams and other visual forms that convey information.

How Do You Use Data Visualization Tools?

There are a lot of data visualization tools out there. But how do you know which one is right for your business? For one thing, it depends on what kind of data you want to visualize: unstructured, semi-structured or structured.

If you’re just starting out in the big data world, you may not know the difference, so let’s define those terms first. Unstructured data Unstructured data is the most basic type of data. It’s basically information that has no structure or organization.

For example, a Word document is unstructured because it’s not organized according to any schema. It’s just a bunch of words strung together. So is an email, a Facebook post and any other free-form text message.

Semi-structured data This type of data has some structure because it’s organized according to tags (for example, XML or JSON). These tags make it easier to search and filter through this kind of data than if you were looking at a jumble of unstructured information.

Semi-structured data also includes metadata (data that describes other data) and annotations (notes about the content). Structured This type of data has been formatted according to predefined schema (a

1. Using Data Visualization Tools Column Charts

Column charts illustrate values over time or compare values across categories. Column charts are useful for comparing data and determining whether a target has been met.

Column charts can be used to visually rank data and show values clearly. They can be used to compare multiple items at once, making them ideal for displaying information from surveys. The horizontal axis can display intervals of time, which makes them useful for tracking performance over time.

When to use a column chart: To compare discrete data To track changes over time (a variation called a “stacked column chart” is useful for showing the total of combined data) Column charts are useful for showing data changes over a period of time or for illustrating comparisons among items.

Column charts display vertical bars going across the chart horizontally, with the values axis being displayed on the left side of the chart. By default, column charts show horizontal gridlines for each tick / value on the y-axis, and no vertical gridlines.

There are many variations of column charts that you can make in Excel, including clustered columns, stacked columns, and 100% stacked columns.

2. Using Data Visualization Tools Bar Chart

A bar chart is an essential tool for any data analyst. It’s a simple, quick and effective way to show a distribution of categorical data. The good news is that there are many different variations of the bar chart and they are all extremely easy to make using Excel.

In this tutorial, we’ll start with the most basic of bar charts: the vertical bar chart, one where the bars grow in height representing numeric values, and one where each bar represents a single category. To begin, I will show you how to create a simple vertical bar chart in Excel 2016.

The screenshot below shows our sample data set. For this tutorial, we will create a bar chart that compares sales for each month in 2016.

In columns A through D, you will see our data set which includes four months of sales from cell B3 through D6. B3 indicates January sales while C3 indicates February sales and so on. In order to create a vertical bar chart in Excel 2016, follow the steps outlined below:

3. Using Data Visualization Tools Pie Chart

Data visualization is a form of visual communication that lets you see what’s happening in your business. It presents a whole new way to look at data to uncover hidden insights and make better decisions.

Data visualization can help you understand what your data means, discover important relationships between variables and get answers more easily than wading through spreadsheets and reports. Let’s say you’re the owner of a small business.

The only way to know how well your business is doing is to analyze your sales data. So every day, you pull up the sales report with all the numbers in rows and columns and read through it carefully. But if there’s a problem, would you be able to find it? There are so many numbers, so many rows — how do you know where the problem is?

Visualization tools let you look at data in an entirely new way by depicting information graphically as charts, graphs or maps. Visualization tools make it easier for you to understand what’s happening in your business.

They give you immediate insight into where the problem lies, so you can take action immediately and get on with running your business.

4. Using Data Visualization Tools Venn Diagrams

It’s important to remember that data visualization tools are not one size fits all. There is a right tool for the right job. A Venn diagram is a good fit when you need to communicate an idea or concept, but not necessarily any specific data.

A Venn diagram is named after John Venn, a 19th century mathematician who used circles to visualize the relationships between sets and subsets. The result is a circle within a circle within a circle.

The diagram allows for multiple groups, with the overlap of each group illustrated by the intersection of circles. Each circle represents a set, or different type of data.

For example, if you wanted to visualize your customers, you could have a set of customers who have purchased your product in the past and another set of customers who are currently subscribed to your service.

The overlap between these two sets would represent customers who have purchased your product in the past and who are currently subscribed to your service. This overlap can help you identify the best group to target with future marketing campaigns based on their shared characteristics.

5. Using Data Visualization Tools Gantt Charts

Gantt chart is a way of visualizing how your project will progress over time. It includes the tasks you’re planning to complete, and indicates their start and end dates.

It can also be used to show which of your resources are assigned to which tasks, as well as overlapping schedules. The Gantt chart is probably the best known type of data visualization tool.

It was first created by Henry Gantt in 1917, and has been widely used ever since. The purpose of the Gantt chart is to show the sequence of tasks that are needed to complete a given project, and how long each task is expected to take.

A Gantt chart can be used for anything from documenting an entire project schedule, to tracking the progress of a single task within a larger project. It can also be used at any level in an organization: by individuals trying to manage their own work; by small teams working on a common goal; or as part of a company-wide project management system.

One thing that all Gantt charts have in common is that they are visual representations of scheduled activities. When you look at one, you should be able to see what’s going on with the project at a glance.

6. Using Data Visualization Tools Line Charts

Line charts are used for visualizing trends and patterns in data over time. They can be used to display multiple variables, as long as these variables share a common time scale.

For example, you could use a line chart to compare the daily sales of two restaurants, or plot the daily stock prices for Amazon, Apple and Netflix. Line charts are one of the most basic and common types of data visualization tools.

They’re easy to understand and interpret, which makes them very popular with decision makers who don’t have much time to study charts. Even when dealing with more complex datasets, line charts can be used to show an overall trend.

A line chart can have multiple lines or series of data plotted on it. Each variable is given its own line, plotted against a shared time axis that makes it easy to compare values.

Line charts can also display multiple variables at once by using color or different shades of gray to distinguish between the various series in the chart. A line chart can be created using several different types of data visualization tool (e.g., Excel, Google Sheets) or programming languages (e.g., R and Python).

7. Using Data Visualization Tools Dashboard

There are many reasons why you might want to use a data visualization tool. You can quickly create a data visualization tool for various types of data such as financial, sales, customer, market, or operational.

It is an effective way to visually display and analyze your data in a format that is easily understood by everyone on your team. A dashboard is a user interface that allows you to interact with an application, website or operating system.

The dashboard brings all the information together in one place so you can access it easily. The following are just some of the tools that can be used to create a data visualization dashboard: Microsoft Excel – Most people use Microsoft Excel to keep track of their data.

It has several built-in functions that allow you to easily visualize your data without any additional software or coding knowledge required. Open Flash Chart – This is an open source charting library written in PHP and JavaScript.

It allows you to create charts and graphs with many customization options such as colors, fonts and more. Google Charts – Google charts are free charts created using Google’s open source library called Google Visualization API.

These charts have a variety of different styles including bar graphs, pie charts and line graphs among others!

What Should You Look for in Data Visualization Tools?

As with any technology, your data visualization tool should be a natural extension of your work rather than an obstacle to it. You have to live with these tools day in and day out, and you don’t want to hate your job.

So if you’re looking at a new data visualization tool for your company, here are some things to look for:

  1. It’s intuitive. The best data visualization tools are so intuitive that they need minimal training.
  2. You should be able to dive right in and easily figure out how to use the tool. If you spend more time learning how to use the tool than you do actually using it, then it’s not a good fit.
  3. It’s powerful without being overwhelming. A good data visualization tool doesn’t give you so many options that you feel paralyzed by choice or so few options that you feel limited in what you can do creatively.
  4. The best tools provide powerful functionality but also structure that functionality into logical groups, making the available options easy to understand and implement efficiently. You shouldn’t have to wade through endless drop-down menus or read the manual from cover to cover just because you want to get something done in a hurry.

1. Data Visualization Tools Easy to Embed

Here are some of the data visualization tools that are easy to implement, and offer engaging ways to visualize data.

  1. Highcharts Highcharts is a charting library written in pure JavaScript, offering an easy way of adding interactive charts to your website or web application. Highcharts currently supports line, spline, area, areaspline, column, bar, pie and scatter chart types.
  2. Google Charts Google Charts is a powerful tool that lets you easily visualize data on your website. Developed by Google, this tool can be embedded using pure JavaScript. With Google Charts you can display live data on your site, gather user feedback and test your product with real users for free.
  3. Chartist Chartist is a simple responsive charting library built with SVG. Chartist works with inline-SVG and therefore leverages the power of the DOM to provide parts of its functionality. This also means we don’t have any dependencies like jQuery or PrototypeJS and it should run on all browsers where SVG is supported (yes even IE9).

2. Data Visualization Tools User Friendliness

Data visualization is useful when you want to show and explain your data in a simple and clear way. We are all aware that the human brain processes visuals 60,000 times faster than text.

Therefore, it’s no surprise that visual representation of data is so popular nowadays – it enables us to understand the data and their relations much faster than reading about them in plain text.

The most common type of data visualization is a chart or graph. This is because many forms of data can be easily represented by a graph. When it comes to creating graphs, there are two main ways to do it:

Create them manually using a software like Microsoft Excel or Google Sheets Use online tools to create graphs automatically from your data In this article, we will review 6 of the best free online data visualization tools you can use right now.

Data visualization is the process of taking raw data and converting it into a graphical representation to make it easier to understand. Businesses typically use data visualization tools to represent their raw data in the form of charts, graphs, infographics, dashboards, etc.

3. Data Visualization Tools Real-Time Collaboration

In the last few years, data visualization has grown to become an important tool for businesses of all sizes. However, several obstacles can make it harder for companies to take advantage of its benefits.

One such obstacle is that data visualization is often a collaborative process involving two or more teams within a company: one team working on collecting and organizing data from multiple sources and another team pulling that data together and creating compelling visualizations of it.

Doing so requires transferring information back and forth between these two teams, which can slow down the process. Fortunately, many tools are now available that make creating visualizations easier by allowing both teams to work together in real-time. Let’s take a look at some of the most poular ones.

With real-time collaboration, multiple users can work together on the same visualization at the same time. You’ll know whether your collaborators are viewing, editing or presenting your visualization.

Real-time collaboration is available in Tableau Desktop Professional and Tableau Server. Collaborators can be designated as editors, who can make changes to the visualization, or viewers, who can only view it.

If you have Tableau Server, you can also save your visualization to a server and share it with others in your organization.

4. Data Visualization Tools Scalability

When considering data visualization tools, scalability is an important factor in the decision-making process. How much data can you visualize? Can your company take advantage of data visualization to its full extent?

Data Visualization Tools Scalability The growth in data over the last few years has been exponential, and it isn’t going to slow down any time soon. IDC estimates that by 2025, the global datasphere will grow to 175 zettabytes — that’s 10 times the 16.1 zettabytes of data created in 2016.

If you want to gain a competitive edge and make sure your organization is getting the most out of its data analytics efforts, you need a tool that can scale with your needs. Y ou might not have a huge amount of data now, but how much do you expect to have access to in five years? Will your current tool be able to handle it all? If not, you need a better solution — one that can help you build visualizations from multiple datasets (even ones from different sources) and create dashboards that are easy for anyone in your company to use.

5. Data Visualization Tools AI-Integration

There are many tools for data visualization and analysis, but how does one decide what to use? This is a common question for many people and there are no “right” answers. The tools and techniques you choose depends on your business, the size of a project, the type and amount of data you work with, the resources you have, etc.

Listed below are some of the most commonly used business intelligence tools that offer good data visualization options: FusionCharts. FusionCharts Suite XT has been around for more than a decade and it is the oldest and most robust JavaScript charting library in the market. FusionCharts supports more than 100 chart types with an extensive list of customization options available.

It also offers maps in SVG format as well as live streaming charts. FusionCharts renders better on both desktop and mobile devices with over 10X improvement in performance on smartphones compared to other competitors.

The newest version of FusionCharts v3 offers several new features such as multi-level drilldown charts, support for JSON data sources, theme-based chart styling, complete localization support for 9 languages including RTL languages like Arabic & Hebrew, and much more.

Data Visualization Tools – Frequently Asked Questions

The most common questions we receive about our data visualization tools are below. What is a data visualization tool? It is a tool that reduces the manual work of creating charts. Users can use these tools to create dashboards, reports, visualizations, and so on in a very short span of time. Which data visualization tool is best for me?

The answer to this depends on your needs and preference. We provide a free version of our product, which you can try out here to see if it suits your requirements. Is there any cost involved in using data visualization tools?

Yes. Most data visualization tools will cost you some money, though some might be available for free. How do I choose the right data visualization tool? First and foremost make sure that the tool meets your requirement. Ask yourself these questions:

Do I need to share my dashboards with others? Whether it is publicly or privately shared, if you need to share the dashboards then you need to make sure that the tool supports it before making a decision.

Do I need to collaborate with others in creating my dashboards? If this feature is important to you then ensure that the tool offers it before making your purchase decision.

Best Data Visualization Tools – Wrap Up

After you read this list of data visualization tools and look at their strengths and weaknesses, you might be wondering which one is the winner. You’re probably expecting me to say “Tableau.”

It would be easy to just pick Tableau as the “best” data visualization tool. It’s a great tool that has been around for a long time, is robust and can do just about anything you want it to do. But there are a few reasons why I won’t give Tableau that title:

Tableau is designed for users with more experience in data analysis and data visualization. If you don’t know how to connect your database, or if you don’t know how to interpret the data, then Tableau isn’t going to make it easier for you. For example, if your database has a lot of calculated fields, then Tableau is going to have a hard time translating it into visualizations.

Tableau isn’t cheap. The license is quite expensive and there aren’t any free versions available. If you really want to get all of the features on offer, then it’s going to cost you a lot of money.