Data visualization is the graphic representation of data. It involves producing images that communicate relationships among the represented data to viewers of the images. This communication is achieved through the use of a systematic mapping between graphic marks and data values in the creation of the visualization. This mapping establishes how data values will be represented visually, determining how and to what extent a property of a graphic mark, such as size or color, will change to reflect changes in the value of a datum.

Graphical displays should:

·         show the data

·         induce the viewer to think about the substance rather than about methodology, graphic design, the technology of graphic production or something else

·         avoid distorting what the data has to say

·         present many numbers in a small space

·         make large data sets coherent

·         encourage the eye to compare different pieces of data

·         reveal the data at several levels of detail, from a broad overview to the fine structure

·         serve a reasonably clear purpose: description, exploration, tabulation or decoration

·         be closely integrated with the statistical and verbal descriptions of a data set.


1.       Chart studio :

Make charts, presentations and dashboards with this adaptable software. You can play out your analysis utilizing JavaScript, Python, R, Matlab, Jupyter, or Excel, and there are a few alternatives for bringing in the information. The perception library and online diagram creation tool permit you to make incredible looking illustrations.


2.       DataHero

DataHero enables you to pull together data from cloud services and create charts and dashboards. No technical abilities are required, so this is a great tool for your whole team to use. 


3.       Chart.js

Chart.js is the perfect data visualization tool for hobbies and small projects. Using HTML 5 canvas elements to render charts, Chart.js creates responsive, flat designs, and is quickly becoming one of the most popular open-source charting libraries. 


4.       Tableau (and Tableau Public)

Tableau has a variety of options available, including a desktop app, server and hosted online versions and a free public option. There are hundreds of data import options available, from CSV files to Google Ads and Analytics data to Salesforce data.

Output options include multiple chart formats as well as mapping capability. That means designers can create color-coded maps that showcase geographically important data in a format that’s much easier to digest than a table or chart could ever be.


5.       RAWGraphs

Open, customizable, and free to download and modify, RAWGraphs lets users create vector-based data visualizations. Data can be safely uploaded from apps to computers, plus it can be exported as an SVG or PNG and embedded in your webpage.

6.       Infogram

Infogram is a fully-featured drag-and-drop visualization tool that allows even non-designers to create effective visualizations of data for marketing reports, infographics, social media posts, maps, dashboards, and more.

Finished visualizations can be exported into a number of formats: .PNG, .JPG, .GIF, .PDF, and .HTML. Interactive visualizations are also possible, perfect for embedding into websites or apps. Infogram also offers a WordPress plugin that makes embedding visualizations even easier for WordPress users.


7.       ChartBlocks

ChartBlocks claims that data can be imported from “anywhere” using their API, including from live feeds. While they say that importing data from any source can be done in “just a few clicks,” it’s bound to be more complex then other apps that have automated modules or extensions for specific data sources.

The app allows for extensive customization of the final visualization created, and the chart building wizard helps users pick exactly the right data for their charts before importing the data.


8.       ZingChart

ZingChart is a JavaScript charting library and feature-rich API set that lets you build interactive Flash or HTML5 charts. It offers over 100 chart types to fit your data.


9.       FusionCharts

FusionCharts is another JavaScript-based option for creating web and mobile dashboards. It includes over 150 chart types and 1,000 map types. It can integrate with popular JS frameworks (including React, jQuery, React, Ember, and Angular) as well as with server-side programming languages (including PHP, Java, Django, and Ruby on Rails).

FusionCharts gives ready-to-use code for all of the chart and map variations, making it easier to embed in websites even for those designers with limited programming knowledge. Because FusionCharts is aimed at creating dashboards rather than just straightforward data visualizations it’s one of the most expensive options included in this article. But it’s also one of the most powerful.


10.   Polymaps

Polymaps is a dedicated JavaScript library for mapping. The outputs are dynamic, responsive maps in a variety of styles, from image overlays to symbol maps to density maps. It uses SVG to create the images, so designers can use CSS to customize the visuals of their maps.