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Best Open Source Data Visualization Tools

Data science is driving key decisions across every industry. Here are some open source data visualization tools that you can use to extract insights from your data.

6 October 2021

by Nimra Ejaz

It’s commonly said that approximately 90% total global data came into existence in just the past two years. Almost all offline processes have been switched to automated digital processes, resulting in consistent, transactional data generation and streams of data logs. Every organization now relies on tons of data to be fully operational and to compete for economic stability. In order to extract meaningful insights from data and make it valuable, it’s necessary to opt for cost-effective approaches that can be easily scaled.

Highlights

In this article, you will get to know about:

What is Data Visualization?

The representation of data or information in the form of some visuals (usually graphs or charts) is referred to as data visualization. It is considered to be an increasingly significant part of data analysis, as it communicates analytical details to the reader in an easy-to-understand manner.

Nowadays, decision making is dependent on the nature of data and how we use it. For that reason, machine learning advancements have introduced novel techniques to conduct predictive analyses using big data. Data scientists and data analysts can interpret the findings and predict meaningful trends or relationships from sparse data with the help of visualizations, in reduced time.

The significant steps involved in the visualization of data are mentioned below:

Data visualizations are not only helpful for data scientists and analysts; they also help businesses in nearly every sector sustain their growth and produce better outcomes. Data changes over time with varied frequency, so visual representations help in identifying correlations and analyzing value as well as risk associated with business. Consistent visualization offers flexibility to share the meaningful takeaways with non-technical readers without involving any rocket science.

Best Open Source Data Visualization Tools

Open source tools provide access to competitive features and integrations free of charge without depending on software vendors. They also possess key technical capabilities such as scaling, adaptability, and consolidation.

Let’s explore the best open source data visualization tools, along with their specific strengths and weaknesses.

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Candela

Candela is an open source data visualization tool that uses JavaScript. It includes a wide variety of features and aids in creating bar charts, line charts, boxplots, and other image types. It has earned a reputable position among robust data visualization tools thanks to its flexible visualization options.

Strengths:

Weaknesses:

Polymaps

Polymaps specializes in the visualization of maps. This tool generates interactive and dynamic maps, which are used for easily understandable analysis. It’s a perfect tool for displaying information from a country level to smallest unit. State-level data, population growth, and route mapping are some prominent instances of this type of visualization.

Strengths:

Weaknesses:

D3.js

D3.js is among the most effective visualization tools when we talk about functionality, features, and design creativity. D3 symbolizes data-driven documents. It is designed to exploit advanced search engines fully. Visualized data is created by implementing HTML, SVG, and CSS. D3.js employs a declarative approach and supports Document Object Models (DOM) manipulation.

Strengths:

Weaknesses:

Charted

Charted is a data visualization tool built by Medium’s Product Science team.  All a user needs to do is provide a link to the data files and then Charted outputs the required charts in a presentable manner. This resulted visualizations can be shared with others for analysis. It refreshes the data after every thirty minutes to keep the visual chart up-to-the-minute.

Strengths:

Weaknesses:

Data Wrapper

Data Wrapper is used by media professionals such as journalists to compile data in the required visual format. It allows layout customizations according to the user’s presentation and design requirements. It exports data (charts) in the form of PDF and PNG. The most appealing feature is that it provides live visual updates.

Strengths:

Weaknesses:

Leaflet

Leaflet is a well-known open-source JavaScript library that incorporates numerous features in order to create interactive maps. It supports desktop and mobile platforms as well as various plugins that can be integrated to extend its functionality. End-users can take advantage of features like multiple map scaling along with keyboard navigation.

Strengths:

Weaknesses:

RawGraph

RawGraph imports data large datasets such as CSV files or TSV files. Allowing the option to copy/paste, it serves as a bridge between files containing raw data and useful data visualization. It enables visual feedback in charts, graphs, and maps as well as custom layouts.

Strengths:

Weaknesses:

Plotly

Plotly is an open-source tool used to create sophisticated data visualizations possessing the capability to work with programming languages like Python, R, and Matlab. Plotly is adopted by users in order to manipulate and modify graphical data online without the need for coding skills. It creates, edits, and shares visualizations in the form of charts and maps in collaboration with team members. This feature enhances efficiency and speeds up the process of data representation.

Strengths:

Weaknesses:


Paid versions of these open source visualization tools can offer more advanced features depending upon the nature of the plan (such as basic, standard, premium, enterprise, etc.), but the plan that is right for you will depend on your business needs.

There also exist a wide variety of licensed tools which are contributing to the business growth of organizations at scale while ensuring data security. Tableau, PowerBI, and QuickSight are considered to be the most popular data visualization tools among licensed tools due to their simplicity of use, ability to handle vast datasets, meaningful visualizations, and productive dashboards.

Conclusion

Human eyes are more responsive to colorful patterns as compared to textual descriptions, which is why data visualization tools have become an essential part of the big data world. Apart from the above-mentioned tools, there still exist plenty of effective data visualization tools to use and explore. By employing pragmatic data visualization tools, professionals can customize and design charts, graphs, and maps as per their requirements. Useful insights achieved from these visualizations can help decision makers grasp complex concepts or identify new trends in order to strengthen business strategies.

If you’re looking to build a data visualization application for internal use or a consumer-facing app with automatically generated charts, Crowdbotics offers managed app development to deliver your build on time and within your budget. Get in touch with one of our experts today for a detailed quote and timeline.